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INFLUENCE OF SEED PRIMING ON THE PERFORMANCE OF BARLEY VARIETIES UNDER LATE SOWN AND ABIOTIC

STRESS CONDITIONS

By

TAHIRA TABASSUMM.Sc. (Hons.) Agriculture (Agronomy)

2008-ag-2561

A thesis submitted in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

I N

A G R O N O M Y

DEPARTMENT OF AGRONOMY,FACULTY OF AGRICULTURE,

UNIVERSITY OF AGRICULTURE,FAISALABAD, PAKISTAN

2018

v

Dedicated To

My Respected

MY LOVING PARENTS, MY CARING HUSBAND DR. ALI ZOHAIB AND MY KIND TEACHER DR.

RIAZ AHMAD

WHO ALWAYS SUPPORTED AND HELPED ME TO ACHIEVE MY GOALS

A C K N O W L E D G E M E N T

First of all, I would like to thank the grace of Allah Almighty for completing this

work at this final shape. All respects are for the Holy prophet Muhammad (Peace be upon

him and his family), for enlightening our conscience with the essence of faith in Allah,

and for giving us the golden principles of Islam.

I owe a great depth of gratitude and appreciation for my supervisor Dr. Riaz

Ahmad, Professor, Department of Agronomy, University of Agriculture, Faisalabad for

his sympathetic attitude, step to step guidance, his supervision and choosing of this

research, his scientific guidance, providing the possible laboratory materials and

unwavering support during my academic and research endeavors.

My deepest and warm gratitude to advisory committee: Dr. Muhammad Farooq,

Associate Professor, Department of Agronomy, University of Agriculture, Faisalabad and

Dr. Shahzad Maqsood Ahmed Basra, Professor, Department of Agronomy, University

of Agriculture, Faisalabad. I am also grateful to Dr. Lee Tarpley, Professor, Department

of Soil and Crop Sciences, Texas A&M University, USA, for supervising me during

IRSIP research work. I am thankful for the guidance they provided me during my work

and evaluation of the work I did.

I am also highly appreciative to Higher Education Commission (HEC),

Government of Pakistan for granting me Indigenous Ph.D. fellowship during my

doctoral study. I really appreciate such fellowships as it is source of hope for students of

Pakistan who want to do something for their homeland.

Special gratefulness and appreciation to my colleagues and friends for assistance

and advices provided during my work. Last but not least, I would like to offer my special

thanks to my family especially my husband Dr. Ali Zohaib Randhawa whose utmost

efforts, endless support, love and prayers enabled me to complete this work and without

their support and kindness I wouldn't have been able to achieve this work and I cannot

find any word to express my sincere appreciation and gratitude to them.

(Tahira Tabassum)

vi

2.3.1. Drought stress 212.3.2. Salt stress 222.3.3. Cadmium stress 232.3.4. Heat stress 242.4. Management of abiotic stresses 252.4.1. Selection of stress tolerant varieties 252.4.2. Seed priming in abiotic stress tolerance 272.4.2.1. Osmopriming with calcium salt and abiotic stress tolerance 282.4.2.2. Biopriming with PGPBs and abiotic stress tolerance 292.5. Conclusion 303 MATERIALS AND METHODS 323.1. Experiment 1: Potential role of seed priming in improving

the resistance against drought in barley32

3.1.1. Experimental site and design 323.1.2. Experimental material 323.1.3. Experimental treatments 323.1.4. Crop husbandry 323.1.5. Imposition of drought stress 333.1.6. Procedures for recording data 333.1.6.1. Stand establishment 33i Final emergence (%) 33ii Time taken to 50% emergence (days) 33iii Mean emergence time (days) 34iv Emergence index 343.1.6.2. Morphological and allometric traits 34i Plant height (cm) 34ii Leaf area (cm2) 343.1.6.3. Proteomics 34i Total soluble proteins (mg g-1 FW) 343.1.6.4. Biochemical traits 35i Chlorophyll contents (mg g -1 FW) 35ii Free leaf proline (µmol g-1 FW) 35iii Leaf glycine betaine (µmol g-1 FW) 36iv Malondialdehyde (µmol g-1 FW) 36v Total soluble phenolics (µg g-1 FW) 36vi Cell membrane stability (%) 373.1.6.5. Water relation traits 37i Leaf relative water content (%) 37ii Leaf water potential (-MPa) 37iii Leaf osmotic potential (-MPa) 37iv Leaf pressure potential (MPa) 373.1.6.6. Grain analysis 38i Zinc content (µg g-1 DW) 38

viii

ii Manganese content (µg g-1 DW) 38iii Boron content (µg g-1 DW) 383.1.6.7. Yield and related traits 39i Number of tillers per pot 39Ii Number of productive tillers per pot 39iii Spike length (cm) 39iv Number of spikelet’s per spike 39v Number of grains per spike 39vi 100-grain weight (g) 39vii Grain yield (g pot-1) 40viii Biological yield (g pot-1) 40ix Harvest index (%) 403.2. Experiment 2: Potential role of seed priming in improving

the salt resistance in barley40

3.2.1. Experimental site and design 403.2.2. Experimental material 403.2.3. Experimental details 403.2.4. Crop husbandry 403.2.5. Imposition of salinity stress 413.2.6. Procedures for recording data 423.2.6.1. Stand establishment 423.2.6.2. Morphological and allometric traits 423.2.6.3. Mineral analysis 423.2.6.4. Proteomics 423.2.6.5. Biochemical traits 423.2.6.6. Water relation traits 423.2.6.7. Grain analysis 433.2.6.8. Yield and related traits 433.3. Experiment 3: Potential role of seed priming in improving

the resistance against osmotic and salt stresses in barley43

3.3.1. Experimental site and design 433.3.2. Experimental material 433.3.3. Crop husbandry and experimental details 433.3.4. Imposition of osmotic and ionic stress in hydroponics 433.3.5. Procedures for recording data 443.3.5.1. Seedling vigor 44i Shoot length of seedling (cm) 44ii Root length of seedling (cm) 44iii Shoot fresh weight (mg) 44iv Root fresh weight (mg) 44v Shoot dry weight (mg) 44vi Root dry weight (mg) 443.3.5.2. Proteomics 44

ix

3.3.5.3. Biochemical traits 443.3.5.4. Mineral analysis 453.4. Experiment 4: Potential role of seed priming in improving

the resistance against cadmium stress in barley45

3.4.1. Experimental site and design 453.4.2. Experimental material 453.4.3. Crop husbandry and experimental details 453.4.4. Procedures for recording data 453.4.4.1. Seedling vigor 453.4.4.2. Proteomics 463.4.4.3. Biochemical traits 463.4.4.4. Mineral analysis 46i Tissue cadmium content (μg g−1 DW) 463.5. Experiment 5: Potential role of seed priming in improving

the resistance against terminal heat stress in barley46

3.5.1. Experimental site and design 463.5.2. Experimental material 463.5.3. Experimental treatments 473.5.4. Crop husbandry 473.5.5. Procedures for recording data 473.5.5.1. Stand establishment 473.5.5.2. Morphological traits 473.5.6.3. Leaf chlorophyll contents 473.5.5.4. Leaf gas exchange characteristics 473.5.5.5. Leaf chlorophyll fluorescence attributes 483.5.5.6. Leaf estimated oxidative stress 483.5.5.7. Total phenolics content (mg g-1 FW) 483.5.6.8. Yield and related traits 483.6. Experiment 6: Influence of seed priming on the

productivity of late sown barley48

3.6.1. Experimental site and design 483.6.2. Experimental material 483.6.3. Seedbed preparation 493.6.4. Experimental details and crop husbandry 493.6.5. Irrigation 493.6.6. Procedures for recording data 493.6.6.1. Stand establishment 493.6.6.2. Allometric, phenological and morphological traits 49i Plant height (cm) 49ii Leaf area index 49iii Total dry matter (g m-2) 50iv Crop growth rate (g m-2 d-1) 50

x

v Grain filling rate (g spike-1 d-1) 50vi Grain filling duration (days) 503.6.6.3. Yield and related traits 50i Number of productive tillers m-2 50ii Spike length (cm) 50iii Number of spikelet’s per spike 50iv Number of grains per spike 50v 1000-grain weight (g) 50vi Grain yield (t ha-1) 51vii Biological yield (t ha-1) 51viii Harvest index (%) 513.6.6.4. Biochemical traits 51i Chlorophyll contents (a, b) 513.6.6.5. Grain proximate analysis 51i Grain protein content (%) 51ii Grain starch content (%) 513.7. Economic Analysis 513.8. Meteorological data 523.9. Statistical analysis 524 RESULTS AND DISCUSSION 564.1. Influence of seed priming in improving the resistance

against drought in barley56

4.1.1. Stand establishment 564.1.1.1. Final emergence percentage 564.1.1.2. Time taken to 50% emergence 564.1.1.3. Mean emergence time 564.1.1.4. Emergence index 564.1.2. Discussion 594.1.3. Agronomic attributes 594.1.3.1. Plant height 594.1.3.2. Leaf area 604.1.3.3. Total number of tillers per pot 604.1.3.4. Number of productive tillers per pot 614.1.3.5. Spike length 614.1.3.6. Number of spikelets per spike 614.1.3.7. Number of grains per spike 664.1.3.8. 100-grain weight 664.1.3.9. Grain yield per pot 674.1.3.10. Biological yield 674.1.3.11. Harvest index 674.1.4. Discussion 684.1.5. Chlorophyll contents 734.1.5.1. Chlorophyll a content 73

xi

4.1.5.2. Chlorophyll b content 744.1.6. Osmolytes accumulation 744.1.6.1. Total soluble phenolics 744.1.6.2. Total soluble proteins 754.1.6.3. Free proline content 754.1.6.4. Glycine betaine content 794.1.7. Lipid peroxidation 794.1.7.1. Malondialdehyde content 794.1.7.2. Cell membrane stability 804.1.8. Discussion 804.1.9. Water relations 854.1.9.1. Leaf relative water content 854.1.9.2. Leaf water potential 854.1.9.3. Leaf osmotic potential 854.1.9.4. Leaf pressure potential 864.1.10. Discussion 864.1.11. Grain nutrient content 904.1.11.1. Grain zinc content 904.1.11.2. Grain manganese content 904.1.11.3. Grain boron content 914.1.12. Discussion 914.2. Influence of seed priming in improving the salt resistance

in barley95

4.2.1. Stand establishment 954.2.1.1. Final emergence percentage 954.2.1.2. Time taken to 50% emergence 954.2.1.3. Mean emergence time 954.2.1.4. Emergence index 954.2.2. Discussion 984.2.3. Agronomic attributes 984.2.3.1. Plant height 984.2.3.2. Leaf area 994.2.3.3. Total number of tillers per pot 994.2.3.4. Number of productive tillers per pot 994.2.3.5. Spike length 1024.2.3.6. Number of spikelets per spike 1024.2.3.7. Number of grains per spike 1034.2.3.8. 100-grain weight 1034.2.3.9. Grain yield per pot 1074.2.3.10. Biological yield per pot 1074.2.3.11. Harvest index 1074.2.4. Discussion 1084.2.5. Chlorophyll contents 111

xii

4.2.5.1. Chlorophyll a content 1114.2.5.2. Chlorophyll b content 1134.2.6. Osmolytes accumulation 1124.2.6.1. Total soluble phenolics 1124.2.6.2. Total soluble proteins 1164.2.6.3. Free proline content 1164.2.6.4. Glycine betaine content 1164.2.7. Lipid peroxidation 1174.2.7.1. Malondialdehyde content 1174.2.7.2. Cell membrane stability 1174.2.8. Mineral analysis 1184.2.8.1. Na content 1184.2.8.2. K content 1184.2.9. Discussion 1234.2.10. Water relations 1244.2.10.1. Leaf relative water content 1244.2.10.2. Leaf water potential 1244.2.10.3. Leaf osmotic potential 1254.2.10.4. Leaf pressure potential 1254.2.11. Discussion 1294.2.12. Grain nutrient contents 1294.2.12.1. Grain zinc content 1294.2.12.2. Grain manganese content 1304.2.12.3. Grain boron content 1304.2.13. Discussion 1314.3. Influence of seed priming in improving the resistance

against osmotic and salt stresses in barley135

4.3.1. Seedling growth 1354.3.2. Chlorophyll contents 1354.3.3. Osmolytes accumulation 1364.3.4. Lipid peroxidation and sodium accumulation 1364.3.5. Discussion 1374.4. Influence of seed priming in improving the resistance

against cadmium stress in barley147

4.4.1. Seedling growth 1474.4.2. Chlorophyll contents 1474.4.3. Osmolytes accumulation 1484.4.4. Lipid peroxidation and cadmium content 1484.4.5. Discussion 1494.5. Influence of seed priming in improving the resistance

against terminal heat stress in barley158

4.5.1. Stand establishment 1584.5.2. Agronomic attributes 158

xiii

4.5.3. Gas exchange attributes 1584.5.4. Chlorophyll a fluorescence attributes 1644.5.5. Chlorophyll contents 1684.5.7. Biochemical attributes 1684.5.7. Discussion 1724.6. Influence of seed priming on the productivity of late sown

barley175

4.6.1. Stand establishment 1754.6.1.1. Mean emergence time 1754.6.1.2. Time taken to 50% emergence 1754.6.1.3. Emergence index 1754.6.2. Discussion 1784.6.3. Allometric traits 1784.6.3.1. Leaf area index 1784.6.3.2. Total dry matter 1814.6.3.3. Crop growth rate 1814.6.3.4. Grain filling rate 1864.6.3.5. Grain filling duration 1864.6.4. Discussion 1904.6.5. Agronomic attributes 1914.6.5.1. Plant height 1914.6.5.2. Number of productive tillers m-2 1914.6.5.3. Spike length 1944.6.5.4. Number of spikelets per spike 1944.6.5.5. Number of grains per spike 1944.6.5.6. 1000-grain weight 1964.6.5.7. Grain yield 1964.6.5.8. Straw yield 1974.6.5.9. Biological yield 1974.6.5.10. Harvest index 1974.6.6. Discussion 1984.6.7. Chlorophyll contents 2034.6.7.1. Chlorophyll a content 2034.6.7.2. Chlorophyll b content 2034.6.8. Discussion 2044.6.9. Grain proximate analysis 2064.6.9.1. Grain crude protein content 2064.6.9.2. Grain starch content 2064.6.10. Discussion 2074.6.11. Economic and marginal analysis 2074.6.12. Discussion 2105 SUMMARY 213

Future research thrusts 218

xiv

LITERATURE CITED 219

xv

LIST OF TABLES

Table No. Title Page No.3.1 Properties of experimental soil (Experiments 1, 2 and 6) 533.2 Properties of experimental soil (Experiment 5) 54

3.3 Weather data during the growing seasons of wheat at experimental site (Experiments 1,2 and 6)

55

4.1 Analysis of variance for the influence of seed priming on final emergence percentage and time taken to 50% emergence of barley

57

4.2 Influence of seed priming on final emergence (%) of barley 57

4.3 Influence of seed priming on time taken to 50% emergence (days) of barley

57

4.4 Analysis of variance for the influence of seed priming on mean emergence time and emergence index of barley

57

4.5 Influence of seed priming on mean emergence time (days) of barley

58

4.6 Influence of seed priming on emergence index of barley 58

4.7 Analysis of variance for the influence of seed priming on plant growth of barley under drought stress

62

4.8 Influence of seed priming on plant height (cm) of barley under drought stress (2014-15)

62

4.9 Influence of seed priming on plant height (cm) of barley under drought stress (2015-16)

62

4.10 Influence of seed priming on leaf area (cm2) of barley under drought stress (2014-15)

62

4.11 Influence of seed priming on leaf area (cm2) of barley under drought stress (2015-16)

63

4.12 Analysis of variance for the influence of seed priming on number of total and productive tillers of barley under drought stress

63

4.13 Influence of seed priming on total number of tillers per pot of barley under drought stress (2014-15)

63

4.14 Influence of seed priming on total number of tillers per pot of barley under drought stress (2015-16)

63

4.15 Influence of seed priming on number of productive tillers per pot of barley under drought stress (2014-15)

64

4.16 Influence of seed priming on number of productive tillers per pot of barley under drought stress (2015-16)

64

4.17 Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under drought stress

64

xvi

4.18 Influence of seed priming on spike length (cm) of barley under drought stress (2014-15)

64

4.19 Influence of seed priming on spike length (cm) of barley under drought stress (2015-16)

65

4.20a Influence of seed priming on number of spikelets per spike of barley under drought stress (2014-15)

65

4.20b Influence of seed priming on number of spikelets per spike of barley under drought stress (2014-15)

65

4.21a Influence of seed priming on number of spikelets per spike of barley under drought stress (2015-16)

65

4.21b Influence of seed priming on number of spikelets per spike of barley under drought stress (2015-16)

65

4.22 Analysis of variance for the influence of seed priming on number of grains per spike and 100-grain weight of barley under drought stress

69

4.23 Influence of seed priming on number of grains per spike of barley under drought stress (2014-15)

69

4.24 Influence of seed priming on number of grains per spike of barley under drought stress (2015-16)

69

4.25 Influence of seed priming on 100-grain weight (g) of barley under drought stress (2014-15)

69

4.26 Influence of seed priming on 100-grain weight (g) of barley under drought stress (2015-16)

70

4.27 Analysis of variance for the influence of seed priming on grain yield, biological yield and harvest index of barley under drought stress

70

4.28 Influence of seed priming on grain yield (g per pot) of barley under drought stress (2014-15)

70

4.29 Influence of seed priming on grain yield (g per pot) of barley under drought stress (2015-16)

70

4.30a Influence of seed priming on biological yield (g per pot) of barley under drought stress (2014-15)

71

4.30b Influence of seed priming on biological yield (g per pot) of barley under drought stress (2014-15)

71

4.31 Influence of seed priming on biological yield (g per pot) of barley under drought stress (2015-16)

71

4.32 Influence of seed priming on harvest index (%) of barley under drought stress (2014-15)

71

4.33a Influence of seed priming on harvest index (%) of barley under drought stress (2015-16)

72

4.33b Influence of seed priming on harvest index (%) of barley under drought stress (2015-16)

72

4.34 Analysis of variance for the influence of seed priming on 76

xvii

chlorophyll contents of barley under drought stress4.35 Analysis of variance for the influence of seed priming on total

soluble proteins and total soluble phenolics contents of barley under drought stress

76

4.36 Analysis of variance for the influence of seed priming on free proline and glycine betaine contents of barley under drought stress

81

4.37 Analysis of variance for the influence of seed priming on malondialdehyde and cell membrane stability of barley under drought stress

81

4.38 Analysis of variance for the influence of seed priming on leaf relative water content and leaf water potential of barley under drought stress

87

4.39 Analysis of variance for the influence of seed priming on leaf osmotic potential and leaf pressure potential of barley under drought stress

87

4.40 Analysis of variance for the influence of seed priming on grain mineral contents of barley under drought stress

92

4.41a Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2014-15)

92

4.41b Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2014-15)

92

4.42a Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2015-16)

92

4.42b Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2015-16)

93

4.43a Influence of seed priming on grain manganese content (µg g-1

DW) of barley under drought stress (2014-15)93

4.43b Influence of seed priming on grain manganese content (µg g-1






4.45a Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2014-15)

94

4.45b Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2014-15)

94

4.46a Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2015-16)

94

4.46b Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2015-16)

94

4.47 Analysis of variance for the influence of seed priming on final 96

xviii

emergence percentage and time taken to 50% emergence of barley

4.48 Influence of seed priming on final emergence (%) of barley 96

4.49 Influence of seed priming on time taken to 50% emergence (days) of barley

96

4.50 Analysis of variance for the influence of seed priming on mean emergence time and emergence index of barley

96

4.51 Influence of seed priming on mean emergence time (days) of barley

97

4.52 Influence of seed priming on emergence index of barley 97

4.53 Analysis of variance for the influence of seed priming on plant growth of barley under salinity

100

4.54 Influence of seed priming on plant height (cm) of barley under salinity (2014-15)

100

4.55 Influence of seed priming on plant height (cm) of barley under salinity (2015-16)

100

4.56 Influence of seed priming on leaf area (cm2) of barley under salinity (2014-15)

100

4.57 Influence of seed priming on leaf area (cm2) of barley under salinity (2015-16)

101

4.58 Analysis of variance for the influence of seed priming on number of total and productive tillers of barley under salinity

101

4.59 Influence of seed priming on total number of tillers per pot of barley under salinity (2014-15)

101

4.60 Influence of seed priming on total number of tillers per pot of barley under salinity (2015-16)

101

4.61 Influence of seed priming on number of productive tillers per pot of barley under salinity (2014-15)

104

4.62 Influence of seed priming on number of productive tillers per pot of barley under salinity (2015-16)

104

4.63 Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under salinity

104

4.64 Influence of seed priming on spike length (cm) of barley under salinity (2014-15)

104

4.65 Influence of seed priming on spike length (cm) of barley under salinity (2015-16)

105

4.66 Influence of seed priming on number of spikelets per spike of barley under salinity (2014-15)

105

4.67 Influence of seed priming on number of spikelets per spike of barley under salinity (2015-16)

105


xix

number of grains per spike and 100-grain weight of barley under salinity

4.69 Influence of seed priming on number of grains per spike of barley under salinity (2014-15)

106

4.70 Influence of seed priming on number of grains per spike of barley under salinity (2015-16)

106

4.71 Influence of seed priming on 100-grain weight (g) of barley under salinity (2014-15)

106

4.72 Influence of seed priming on 100-grain weight (g) of barley under salinity (2015-16)

106

4.73 Analysis of variance for the influence of seed priming on grain yield, biological yield and harvest index of barley under salinity

109

4.74 Influence of seed priming on grain yield (g per pot) of barley under salinity (2014-15)

109

4.75 Influence of seed priming on grain yield (g per pot) of barley under salinity (2015-16)

109

4.76 Influence of seed priming on biological yield (g per pot) of barley under salinity (2014-15)

109

4.77 Influence of seed priming on biological yield (g per pot) of barley under salinity (2015-16)

110

4.78 Influence of seed priming on harvest index (%) of barley under salinity (2014-15)

110

4.79 Influence of seed priming on harvest index (%) of barley under salinity (2015-16)

110

4.80 Analysis of variance for the influence of seed priming on chlorophyll contents of barley under salinity

113

4.81 Analysis of variance for the influence of seed priming on total soluble proteins and total soluble phenolics contents of barley under salinity

113

4.82 Analysis of variance for the influence of seed priming on free proline and glycine betaine contents of barley under salinity

119

4.83 Analysis of variance for the influence of seed priming on malondialdehyde and cell membrane stability of barley under salinity

119

4.84 Analysis of variance for the influence of seed priming on leaf mineral contents of barley under salinity

119

4.85 Analysis of variance for the influence of seed priming on leaf relative water content and leaf water potential of barley under salinity

126

4.86 Analysis of variance for the influence of seed priming on leaf osmotic potential and leaf pressure potential of barley under salinity

126

xx

4.87 Analysis of variance for the influence of seed priming on grain mineral contents of barley under salinity

132

4.88a Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2014-15)

132

4.88b Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2014-15)

132

4.89a Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2015-16)

132

4.89b Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2015-16)

133


DW) of barley under salinity (2014-15)133







4.92a Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2014-15)

134

4.92b Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2014-15)

134

4.93a Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2015-16)

134

4.93b Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2015-16)

134

4.94 Analysis of variance for the influence of seed priming on seedling growth of barley under osmotic and salt stress

140

4.95 Analysis of variance for the influence of seed priming on chlorophyll and total soluble phenolics contents in barley under osmotic and salt stress

140

4.96 Analysis of variance for the influence of seed priming on osmolytes accumulation in barley under osmotic and salt stress

144

4.97 Analysis of variance for the influence of seed priming on malondialdehyde and Na contents in barley under osmotic and salt stress

144

4.98 Analysis of variance for the influence of seed priming on seedling growth of barley under cadmium stress

151

4.99 Analysis of variance for the influence of seed priming on chlorophyll and total soluble phenolics contents in barley under cadmium stress

151


xxi

osmolytes accumulation in barley under cadmium stress4.101 Analysis of variance for the influence of seed priming on

malondialdehyde and cadmium contents in barley under cadmium stress

155

4.102 Analysis of variance for the influence of seed priming on emergence of barley

159

4.103 Influence of seed priming on emergence attributes of barley 159

4.104 Analysis of variance for the influence of seed priming on growth and yield related traits of barley under terminal heat stress

159

4.105 Influence of seed priming on plant height and number of productive tillers per pot of barley under terminal heat stress

159

4.106 Influence of seed priming on spike length and number of spikelets per spike of barley under terminal heat stress

160

4.107 Analysis of variance for the influence of seed priming on yield related traits, yield and harvest index of barley under terminal heat stress

160

4.108 Influence of seed priming on number of grains per spike and 100-grain weight of barley under terminal heat stress

160

4.109 Influence of seed priming on grain yield and biological yield per pot of barley under terminal heat stress

160

4.110 Influence of seed priming on harvest index (%) of barley under terminal heat stress

161

4.111a Analysis of variance for the influence of seed priming on gas exchange attributes of barley under terminal heat stress

161

4.111b Analysis of variance for the influence of seed priming on gas exchange attributes of barley under terminal heat stress

161

4.112a Analysis of variance for the influence of seed priming on chlorophyll a fluorescence attributes of barley under terminal heat stress

165

4.112b Analysis of variance for the influence of seed priming on chlorophyll a fluorescence attributes of barley under terminal heat stress

165

4.113 Analysis of variance for the influence of seed priming on chlorophyll contents of barley under terminal heat stress

169

4.114 Analysis of variance for the influence of seed priming on total soluble phenolics, malondialdehyde and cell membrane stability of barley under terminal heat stress

169

4.115 Analysis of variance for the influence of seed priming on emergence of barley under optimum and late sowing time

176

4.116 Influence of seed priming on mean emergence time (days) of barley under optimum and late sowing time

176

4.117a Influence of seed priming on time taken for 50% (days) 176xxii

emergence of barley under optimum and late sowing time

4.117b Influence of seed priming on time taken to 50% emergence (days) of barley under optimum and late sowing time (2014-15)

177

4.118a Influence of seed priming on emergence index of barley under optimum and late sowing time

177

4.118b Influence of seed priming on emergence index of barley under optimum and late sowing time (2014-15)

177

4.119 Analysis of variance for the influence of seed priming on grain filling duration of barley under optimum and late sowing time

189

4.120 Influence of seed priming on grain filling duration (days) of barley under optimum and late sowing time (2014-15)

189

4.121 Influence of seed priming on grain filling duration (days) of barley under optimum and late sowing time (2015-16)

189

4.122 Analysis of variance for the influence of seed priming on plant height and number of productive tillers per m2 of barley under optimum and late sowing time

192

4.123a Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2014-15)

192

4.123b Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2014-15)

192

4.124 Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2015-16)

193

4.125 Influence of seed priming on number of productive tillers per m2 of barley under optimum and late sowing time

193

4.126 Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under optimum and late sowing time

195

4.127 Influence of seed priming on spike length (cm) of barley under optimum and late sowing time

195

4.128 Influence of seed priming on number of spikelets per spike of barley under optimum and late sowing time

195

4.129 Analysis of variance for the influence of seed priming on number of grains per spike and 1000-grain weight of barley under optimum and late sowing time

199

4.130 Influence of seed priming on number of grains per spike of barley under optimum and late sowing time

199

4.131a Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2014-15)

199

4.131b Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2014-15)

200

4.132 Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2015-16)

200

xxiii

4.133 Analysis of variance for the influence of seed priming on grain yield and straw yield of barley under optimum and late sowing time

200

4.134 Influence of seed priming on grain yield (t ha-1) of barley under optimum and late sowing time

201

4.135 Influence of seed priming on straw yield (t ha-1) of barley under optimum and late sowing time (2014-15)

201

4.136 Influence of seed priming on straw yield (t ha-1) of barley under optimum and late sowing time (2015-16)

201

4.137 Analysis of variance for the influence of seed priming on biological yield and harvest index of barley under optimum and late sowing time

202

4.138 Influence of seed priming on biological yield (t ha-1) of barley under optimum and late sowing time (2014-15)

202

4.139 Influence of seed priming on biological yield (t ha-1) of barley under optimum and late sowing time (2015-16)

202

4.140 Influence of seed priming on harvest index (%) of barley under optimum and late sowing time

202

4.141 Analysis of variance for the influence of seed priming on chlorophyll contents of barley under optimum and late sowing time

205

4.142 Influence of seed priming on leaf chlorophyll a content (mg g-

1 FW) of barley under optimum and late sowing time205

4.143 Influence of seed priming on leaf chlorophyll b content (mg g-

1 FW) of barley under optimum and late sowing time205

4.144 Analysis of variance for the influence of seed priming on grain crude protein and starch contents of barley under optimum and late sowing time

208

4.145 Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2014-15)

208

4.146a Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2015-16)

208

4.146b Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2015-16)

209

4.147 Influence of seed priming on grain starch content (%) of barley under optimum and late sowing time

209

4.148 Economic analysis 211

4.149 Marginal analysis 212

xxiv

LIST OF FIGURES

Figure No. Title Page No.4.1 Influence of seed priming on (a and b) chlorophyll a and (c

and d) chlorophyll b contents of barley under drought stress77

4.2 Influence of seed priming on (a and b) total soluble phenloics and (c and d) total soluble proteins contents of barley under drought stress

78

4.3 Influence of seed priming on (a and b) free proline and (c and d) glycine betaine contents of barley under drought stress

82

4.4 Influence of seed priming on (a and b) malondialdehyde content and (c and d) cell membrane stability of barley under drought stress

83

4.5 Influence of seed priming on (a and b) leaf relative water content and (c and d) leaf water potential of barley under drought stress

88

4.6 Influence of seed priming on (a and b) leaf osmotic potential and (c and d) leaf pressure potential of barley under drought stress

89

4.7 Influence of seed priming on (a and b) chlorophyll a and (c and d) chlorophyll b contents of barley under salinity

114

4.8 Influence of seed priming on (a and b) total soluble phenloics and (c and d) total soluble proteins contents of barley under salinity

115

4.9 Influence of seed priming on (a and b) free proline and (c and d) glycine betaine contents of barley under salinity

120

4.10 Influence of seed priming on (a and b) malondialdehyde content and (c and d) cell membrane stability of barley under salinity

121

4.11 Influence of seed priming on (a and b) Na content and (c and d) K content of barley under salinity

122

4.12 Influence of seed priming on (a and b) leaf relative water content and (c and d) leaf water potential of barley under salinity

127

4.13 Influence of seed priming on (a and b) leaf osmotic potential and (c and d) leaf pressure potential of barley under salinity

128

4.14 Influence of seed priming on (a) shoot length (b) root length and (c) shoot fresh weight of barley under osmotic and salt stress

141

4.15 Influence of seed priming on (a) root fresh weight (b) shoot dry weight and (c) root dry weight of barley under osmotic and salt stress

142

xxv

4.16 Influence of seed priming on (a) chlorophyll a content (b) chlorophyll b content and (c) total soluble phenolics content of barley under osmotic and salt stress

143

4.17 Influence of seed priming on (a) total soluble proteins content (b) free proline content and (c) glycine betaine content of barley under osmotic and salt stress

145

4.18 Influence of seed priming on (a) malondialdehyde content and (b) Na content of barley under osmotic and salt stress

146

4.19 Influence of seed priming on (a) shoot length (b) root length and (c) shoot fresh weight of barley under cadmium stress

152

4.20 Influence of seed priming on (a) root fresh weight (b) shoot dry weight and (c) root dry weight of barley under cadmium stress

153

4.21 Influence of seed priming on (a) chlorophyll a content (b) chlorophyll b content and (c) total soluble phenolics content of barley under cadmium stress

154

4.22 Influence of seed priming on (a) total soluble proteins content (b) free proline content and (c) glycine betaine content of barley under cadmium stress

156

4.23 Influence of seed priming on (a) malondialdehyde content and (b) cadmium content of barley under cadmium stress

157

4.24 Influence of seed priming on (a and b) photosynthesis (PN) (c and d) stomatal conductance (gs) and (e and f) intercellular CO2 concentration (Ci) of barley under terminal heat stress

162

4.25 Influence of seed priming on (a and b) transpiration (Tr) (c and d) stomatal limitation (Ls) and (e and f) carboxylation use efficiency (CUE) of barley under terminal heat stress

163

4.26 Influence of seed priming on (a and b) minimal fluorescence (Fo) (c and d) maximal fluorescence (Fm) and (e and f) variable fluorescence (Fv) of barley under terminal heat stress

166

4.27 Influence of seed priming on (a and b) maximum quantum yield (Fv/Fm) (c and d) quantum yield of PSII (φPSII) and (e and f) electron transport rate (ETR) of barley under terminal heat stress

167

4.28 Influence of seed priming on (a and b) chlorophyll a content (c and d) chlorophyll b content and (e and f) total chlorophyll content of barley under terminal heat stress. DAT: days after heat stress treatment

170

4.29 Influence of seed priming on (a and b) total soluble phenolics (c and d) malondialdehyde content and (e and f) cell membrane stability of barley under terminal heat stress

171

4.30 Influence of seed priming on leaf area index of barley under (a) optimum and (b) late sowing time (2014-15)

179

xxvi

4.31 Influence of seed priming on leaf area index of barley under (a) optimum and (b) late sowing time (2015-16)

180

4.32 Influence of seed priming on total dry matter accumulation in barley under (a) optimum and (b) late sowing time (2014-15)

182

4.33 Influence of seed priming on total dry matter accumulation in barley under (a) optimum and (b) late sowing time (2015-16)

183

4.34 Influence of seed priming on crop growth rate of barley under (a) optimum and (b) late sowing time (2014-15)

184

4.35 Influence of seed priming on crop growth rate of barley under (a) optimum and (b) late sowing time (2015-16)

185

4.36 Influence of seed priming on grain filling rate of barley under (a) optimum and (b) late sowing time (2014-15)

187

4.37 Influence of seed priming on grain filling rate of barley under (a) optimum and (b) late sowing time (2015-16)

188

xxvii

LIST OF APPENDICES

Appendix No. Title Page No.

1 Fixed cost (Experiment 6) 253

2 Variable cost (Experiment 6) 254

xxviii

LIST OF ABBREVIATIONS

Abbreviation Complete% percent°C degree Celsiusµg micro gramµM micro molarABA abscisic acidANOVA analysis of varianceB boronBCR benefit cost ratioCa calciumCaM calmodulinCAT catalaseCd cadmiumCDPK calcium dependent protein kinasesCGR crop growth rateCi intercellular CO2 concentrationcm centimeterCRD completely randomized designCu copperCUE carboxylation use efficiencyDAA days after anthesisDAP diamonium phosphateDAS days after sowingDAT days after treatmentDW dry weightEC electrical conductivityETR electron transport rateFm maximal fluorescenceFo minimal fluorescenceFv variable fluorescenceFv/Fm maximum quantum efficiency of

PSIIFW fresh weightGR glutathione reductasegs stomatal conductanceGST glutathione -S-transferaseh hourha hectareHAMK heat-shock activated mitogen

activated protein kinaseIAA indole-acetic acidK potassiumkg kilogramL literLAD leaf area durationLAI leaf area indexHVA Hordeum vulgaris abundant protein

xxix

Ls stomatal limitationLSD least significance differencem meterM molarMAPK mitogen activated protein kinaseMDA malondialdehydeMg Magnesiummg milligrammL mili litermM mili molarmm milli metermmol L-1 milli mole per literMn manganeseMPa mega PascalMRR marginal rate of returnMT metallothioneinsN nitrogenNa sodiumNAR net assimilation rateNIR near infrarednm nano meterO* singlet oxygenO2− superoxide anionOH− hydroxyl radicalP phosphorusPb leadPC phytochelatinsPEG polyethylene glycolPGPB plant growth promoting bactariaPN photosynthesisppm parts per millionPSII photosystem IIQY quantum yield of PSIIRCBD randomized complete block designROS reactive oxygen speciesRs. RupeesSAR sodium absorption ratioSOD superoxide dismutaseSOP sulphate of potasht tonTBA thiobarbituric acidTCA trichloroacetic acidTDM total dry matterTr transpirationTSS total soluble saltsUSA the United States of Americaw/v weight by volumeZn zinc

xxx

ABSTRACT

Abiotic stresses affect plant productivity by modulationg various physiological and biochemical processes. Studies were performed to evaluate the influence of seed priming on the performance of barley varieties under late sown and abiotic stress conditions. For this purpose, a series of experiments was conducted in field and green house of University of Agriculture, Faisalabad, and glass house of Texas A&M University, USA. In first pot experiment, seeds of two barley varieties (viz. Haider-93 and Frontier-87) primed with water (hydropriming), CaCl2 solution (osmopriming) and Enterobacter sp. strain FD17 culture (biopriming) were sown in pots. After seedling establishment, drought levels (viz. 80, 60 and 40% water holding capacity) were imposed. In second pot experiment, same varieties and seed priming treatments were followed except after seedling establishment salinity levels (viz. 50, 100 and 150 mM NaCl) were imposed. Third experiment was carried out in hydroponics. Seedlings were raised in sand filled polythene bags by using same varieties and seed priming treatments. After stand establishment seedlings were transplanted in hydroponics then, osmotic (-0.8 MPa using PEG) and ionic (-0.8 MPa using NaCl) stresses were imposed. In fourth experiment, same procedure was followed as in the third experiment except cadmium (Cd) toxicity stress levels (viz. 0, 8 and 12 mg L-1 water) were imposed. In fifth experiment, seeds of USA cultivar Solum were primed with water (hydropriming) and CaCl2 (osmopriming), and sown in pots. At reproductive stage two levels of heat stress viz. control (25/18°C day/night) and heat stress (35/25°C day/night) were applied. In all pot and hydroponics experiments dry seed was taken as control. The pot and hydroponics experiments were carried out using completely randomized design (CRD) with factorial arrangement having four replications, except fifth experiment in which six replications were used. In sixth experiment, same varieties and seed priming treatments, as in first pot experiment, were followed and sown in field at November 30 and December 30. The experiment was conducted by using randomized complete block design (RCBD) with split-split plot arrangement having four replications. In first and second experiments, drought and salinity decreased plant growth, yield and chlorophyll contents, and perturbed the water and nutrient relations; while, increased accumulation of osmolytes and lipid peroxidation in both barley varieties, as compared to control. Moreover, salinity increased the sodium (Na) accumulation while decreased potassium (K) accumulation. However, seed priming improved plant growth, yield, tissue water status, cell membrane stability, chlorophyll contents and accumulation of phenolics, total soluble proteins, free proline and glycine betaine contents while decreased the malondialdehyde (MDA) content in both varieties under stressed conditions, as compared to unprimed control. The gretest improvement in yield under drought was caused by biopriming; whereas, under moderate and severe salt stress by biopriming and osmopriming, respectively. Moreover, biopriming improved the grain zinc (Zn), manganese (Mn) and boron (B) contents. In third and fourth experiments, osmotic, salt as well as Cd stress decreased the seedling growth and dry biomass in both varieties while increased the osmolytes and lipid peroxidation, as compared to control. Moreover, NaCl salt stress and Cd stress increased Na and Cd contents in barley, respectively. However, seed priming enhanced seedling growth, fresh and dry biomass, chlorophyll contents, phenolics, total soluble proteins, free proline and glycine betaine contents while decreased MDA, Na and Cd contents under stressed conditions, as compared to unprimed control. Under osmotic and Cd stress biopriming was most effective, while, under salt stress osmopriming was superior in improving barley performance. In fifth experiment, terminal heat stress hampered the plant growth, yield, leaf gas exchange and chlorophyll photochemistry while increased the phenolics and lipid

1

peroxidation, as compared to control. However, seed priming improved the photosynthesis, stomatal conductance, carboxylation use efficiency (CUE), quantum yield of photosystem II (QY), electron transport rate (ETR), chlorophyll contents, phenolics and cell membrane stability while decreased MDA content under terminal heat stress, as compared to unprimed control, and osmopriming was superior in this regard. In sixth experiment, late sowing caused a reduction in emergence, growth, grain yield, dry matter accumulation, grain filling duration, chlorophyll contents, and grain crude protein and starch contents in both barley varieties, as compared to optimum sowing time. However, seed priming improved emergence, plant height, crop growth rate (CGR), total dry matter accumulation (TDM), leaf area index (LAI), grain filling rate, yield and related traits, and grain crude protein and starch contents under both optimum and late sowing, as compared to unprimed control. The greatest improvement was caused by osmopriming followed by biopriming. The economic analysis showed that late sowing decreased economic returns as well as benefit cost ratio (BCR) which was improved by seed priming treatments. Among all, biopriming caused maximum improvement in BCR and marginal rate of return (MRR). In all pot and field experiments, variety Haider-93 performed better than Fronteir-87. In conclusion, abiotic stresses and late sowing decreased the plant growth and yield by negatively affecting plant physiological processes. However, performance of barley varieties was effectively improved by seed priming treatments under stressed conditions by improving the water relations, nutrient relations, osmolytes accumulation, photosynthesis, chlorophyll contents and decreasing the lipid peroxidation under stressed conditions.

2

CHAPTER 1INTRODUCTION

Barley (Hordeum vulgare L.), is an important cereal crop, which is cultivated for

human consumption as well as animal feed (Alazmani, 2015). It grows well on both

normal as well as marginal lands (Kafawin et al., 2005) and is tolerant to drought and

salinity due to expression of proteins such as Hordeum vulgaris abundant protein (HVA)

(Nguyen and Sticklen, 2013). However, the yield of barley is very low owing to poor

agro-management practices such as improper sowing time coupled with abiotic stresses

for instance high and low temperature, salinity, drought and heavy metal toxicity stress.

Optimum sowing time is important for achieving better crop yield and quality.

Early sowing affects yield potential by allowing a longer time for biomass accumulation.

However, too early or late sowing significantly reduces crop yield. Though early sowing

reduces the risk of heat stress during grain filling, it increases the frost risk during

flowering. While late sowing reduces crop yield and malting quality due to poor stand

establishment. Similarly, late sowing caused the cultivars to mature earlier which

indicated that maturity was forced because of high temperature (Samarah and Al-Issa,

2006), resulting in fewer tillers and number of grains per plant (Alazmani, 2015);

Furthermore, increase in temperature causes shortening of heading period under late sown

conditions (Razzaque and Rafiquzzaman, 2006). Alam et al. (2007) reported that late

sowing reduced the yield and yield components of barley. Late planted barley produced

less productive tillers, grain weight and grain yield than those of timely planted crop

(Samarah and Al-Issa, 2006). Therefore, by targeting the optimal sowing date, seasonal

risks can be minimized to harvest better crop yield.

Under field conditions, plants may face various abiotic stresses. Abiotic stresses

are the major limiting factors due to the potential influence of climate change on

temperature extremes and rainfall patterns, salinization of agricultural lands by irrigation

that reduces the agricultural productivity (Araus et al., 2002; Vinocur and Altman, 2005;

Tabassum et al., 2017). However, drought, salt, heat and heavy metal stresses are of

prime importance.

Drought is a most vital abiotic factor that negatively influences the crop growth

and production globally. It causes 15% of potential yield losses (Edmeades and James,

2008), and more than 50% plant growth problems to arable lands will occur by 2050

3

annually (Vinocur and Altman, 2005). Reduction in crop yield by drought may happen

due to less absorption of the photosynthetically active radiation (PAR) by plant canopy,

reduced radiation utilization efficiency and decreased harvest index of crop plants (Earl

and Davis, 2003). Reduced germination and stand establishment are the foremost

responses of crop plants to water deficit conditions (Kaya et al., 2006). Soil water deficit

at flowering stage usually causes barrenness due to limited translocation of assimilates to

developing kernels below the threshold level that is needed to attain optimum growth of

grains (Yadav et al., 2004). Drought stress causes an osmotic stress that results in loss of

plant turgor, disorganized membrane, more denatured proteins and production of high

amounts of reactive oxygen species (ROS) viz. hydroxyl radical (OH-), superoxide anion

(O2-) and hydrogen peroxide (H2O2) causing oxidative stress. As a consequence, it

disrupts the cellular structures and impairs key physiological process such as inhibition of

photosynthesis, metabolic dysfunctions and damage to cellular structures contribute to

growth perturbances, reduced fertility, and premature senescence that ultimately reduce

the crop yield (Mahajan and Tuteja, 2005; Fahad et al., 2017).

Salt stress is a worldwide problem covering more than 0.8 million ha of arable

land by either sodicity (434 million ha) or salt stress (397 million h) (FAO, 2005; Munns,

2005). It causes 20% reduction in yield potential (Ashraf and Harris, 2005). It is caused

by a combination of the osmotic and ionic stress due to high concentration of Na+ in the

plant rhizosphere (Hasegawa et al., 2000). Various physiological functions such as

biological nitrogen fixation, photosynthesis, respiration and starch metabolism are

adversely effected by salt stress that ultimately losses the crop productivity (Farooq et al.,

2015, 2017). Salt stress limits plant sink, reduces activity of acid invertase in the

developing grains that causes poor grain setting which ultimately leads to reduced grain

yield (Abdullah et al., 2001; Basra et el., 2005; Kaya et al., 2013) and number of grains,

that are responsible for decrease in grain yield (Schubert et al., 2009). Though, salt stress

induced declines in assimilate flux, are furthermore responsible for decreased grain

setting and grain filling, that eventually lowers the crop yield (Lohaus et al., 2000).

Heavy metal contamination is one of the serious environmental issues in the

present time which is increasing with unavoidable pace (Liu et al., 2010). Heavy metals

cause deleterious impacts on plant metabolism (Grimm et al., 2008), which move to

consumer’s body by soil-plant-food interaction that cause some severe deformities in

humans and animals (Chaney et al., 2004). Among these Cd is a broadly spread lethal

toxin for plants, animals and humans, that come into the environment mostly from 4

numerous industrial discharges and man-made activities, containing chemical fertilizers,

pesticides and herbicides application, or irrigation with polluted groundwater and is then

translocated to the food chain (Liu et al., 2010). Most important impacts of Cd toxicity in

plants are growth inhibition, cell membrane disruption, and alteration in enzyme activity

that ultimately reduces the crop yield attributes (Anjum et al., 2015). Cadmium toxicity

reduces the yield and dry weight which might be due to inhibited net photosynthesis

owing to reduced stomatal gas exchange and photosynthetic pigments, decline in

chlorophyll contents related to reduced chlorophyll biosynthesis and disrupted

translocation and accumulation of photosynthetic assimilates that destroys the

ultrastructure of chlorophyll under Cd stress (Anjum et al., 2017a).

Heat stress adversely effects the plant growth, development, physio-chemical

processes and yield (Hasanuzzaman et al., 2012, 2013). Its response varies with time,

duration, and severity of the heat stress (Barnabás et al., 2008). High temperature stress

causes severe heat injury or irreversible damage that leads to the increased production of

ROS which causes oxidative stress (Wahid et al., 2007). It causes changes in

photosynthesis and respiration thereby resulting in a decreased life cycle and crop yield

(Barnabás et al., 2008). Heat stress primarily alters the structure of chloroplast protein

complex and decreases enzyme activity (Ahmad et al., 2010). Heat stress at reproductive

stage lowers the development of morphological units that contribute to harvest index (HI)

(Barnabás et al., 2008). It reduces the number of productive tillers, spikelets and grains

per spike as well as grain weight in maize and wheat (Prasad et al., 2008a, b; Farooq et

al., 2011). According to an estimate every 1°C increase in daily minimum temperature

decreases the rice grain yield up to 10% (Peng et al., 2004). Pollens and anthers were

more sensitive to high temperature and becomes sterile at temperatures ≥30°C (Matsui et

al., 2000), that leads to lower pollen grains development and reduced in vivo pollen

germination (Prasad et al., 2006a; Jagadish et al., 2010).

To cope with abiotic stresses, plants adopt different physiological and biochemical

processes; such as under different abiotic stresses and salt stress the stress resistance is

achieved by selective inclusion or exclusion of ions, ionic compartmentalization,

hormonal regulation, induction of antioxidants, modifications in membrane structure,

production of compatible solutes (Parida and Das, 2005; Farooq et al., 2009a; Fahad et

al., 2017). Likewise, under low water potential the osmotic adjustment is a feature in

plants for the maintenance of tissue water contents (Flowers et al., 2010). Tolerant

genotypes of wheat accumulated greater amount of sucrose when exposed to salt and 5

drought stresses as compared to the sensitive genotypes (Kerepesi and Galiba, 2000). In

plants, resistance against abiotic stresses can be improved by transgenic approaches and

plant breeding. However, it is complex, difficult and time requiring process. Moreover,

genetically modified plants remain un-accepted for some areas of the world (Wahid et al.,

2007).

In this scenario, seed priming is an attractive option as it is a cost effective,

simple, low risk and short gun approach to overcome the salt and drought problems

(Farooq et al., 2009b). It is a controlled hydration process of the seed performed near a

level where the germination associated metabolic events start without actual germination

(Farooq et al., 2006a). It can be done with water (hydropriming), solutions containing

salts, hormones, osmolytes as well as microbial inoculants. Seed priming improves

germination as well as seedling growth under normal and salt stress areas (Basra et al.,

2005). Pre-sowing seed treatments with inorganic or organic substances and/or with high

or low temperature improve plant growth and yield under abiotic stresses (Cantliffe,

2003). Seed priming with KCl improves wheat yield under salt and drought stress

conditions (Ghana and Schillinger, 2003). Seed priming with hormones, inorganic solute,

or antioxidant composites improves water utilization efficiency under drought conditions

(Ajouri et al., 2004), enhance salt stress tolerance (Basra et al., 2005), and enhances

activity of catalase (CAT) and superoxide dismutase (SOD) which are responsible for

protection of plants from oxidative stress (Basra et al., 2004).

Plant growth promoting bactaria (PGPBs) have the potential to improve the

growth and physiological functions in stressful conditions such as microbes induce

several natural processes to maintain plant growth under stressed environments (Yang et

al., 2008; Vardharajula et al., 2011). Plant growth promoting bactaria efficiently

colonizes the different crops, and are capable for improving the stand establishment,

growth, development and yield through stress mitigation and improves the root growth

that ultimately increase the nutrient availability to plants (Hardoim et al., 2008; Naveed

et al., 2014a). Microbes produce certain hormones, which are responsible to control the

root growth and efficiency. Plant root exudates produce tryptophan; PGPBs use it as

precursor to produce auxin in the root zone that alters the plant root architecture, increase

the total surface area of roots, which subsequently increase the water and nutrient uptake

in plants (Somers et al., 2004; Miliute et al., 2015). Moreover, some PGPB strains

promote plant growth under normal and stressed conditions through triggering certain

mechanisms for instance induced systemic resistance, lowering the production of stress 6

induced ethylene and exopolysaccharides (Sandhya et al., 2009; Saharan and Nehra,

2011; Upadhyay et al., 2011). Ethylene acts as phytohormone which affects the plant

growth at low levels (Glick et al., 2007), and its concentration usually rises under stressed

conditions (Zapata et al., 2007).

Certain PGPB contains ACC-deaminase, which degrades ACC (precursor of

ethylene) into ammonia and α-ketobutyrate in root vicinity (Glick et al., 2007). In this

way the inhibitory effects of ethylene on root growth of plants are supressed by PGPB

(Barnawal et al., 2012; Chen et al., 2013a). Under saline conditions, plants face the

nutritional imbalance and specific ion toxicity, and a high K+/Na+ ratio is extremely

important (Hamdia et al., 2004). Some PGPBs produce exopolysaccharides that binds the

Na+ and produced biofilm help in maintaining the high ratio of K+/Na+ in plants (Khodair

et al., 2008; Qurashi and Sabri, 2012). Furthermore, PGPB produce exopolysaccharides

that induce desiccation tolerance in microbes as well as plants and enable them to keep

their growth in pace under drought stress (Sandhya et al., 2009).

Proper sowing time is important for higher barley productivity as there are

problems associated with early and late sowing rearding stand establishment and grain

filling. Furthermore, under field conditions abiotic stresses severely affect barley growth

and productivity. Seed priming is a low cost, simple and shotgun approach that improves

crop stand establishment, and ameliorates the effects of harsh climatic conditions and

abiotic stresses. Moreover, seed priming with inorganic salts and PGPBs can be a viable

technique to improve barley stress tolerance and enhance barley productivity. It was

hypothesized that seed priming will improve the barley performance by improving stand

establishment, and modulating physiological and biochemical processes under late sown

and abiotic stress conditions. However, there is limited knowledge on underlying

processes. Therefore, this study was conducted with objectives to (i) improve the

productivity of late sown barley by seed priming, (ii) evaluate the potential of seed

priming treatments in improving the performance of barley under drought, salinity, heat

and cadmium stresses, (iii) monitor the physiological, biochemical and proteomic basis of

priming-induced resistance against abiotic stresses in barley. Moreover, the role of seed

priming with water, CaCl2 as well as PGPBs in resistance against abiotic stresses in

barley was also studied.

7

CHAPTER 2

REVIEW OF LITERATURE

2.1. Sowing Time

Optimum sowing time has a very important effect on crop growth and

productivity; as early sowing gives high grain yield in barley while; in case of late sowing

after the 1st week of December significantly decreases the barley yield. It shortens the

growing period and crops are exposed to late season high temperature stress during grain

filling period (Hossain et al., 2003; Yau, 2003). Proper sowing time ensures a good stand

establishment that is the main factor affecting crop productivity (Hossain et al., 2003).

Chen et al. (2003) suggested that winter wheat planted earlier, had the high economic

yield while; late planted crop significantly lowered the wheat yield. Better crop yield due

to sowing at optimum time is attributed to better emergence and stand establishment that

results in greater productive tillers and spikes per unit area (Yau et al., 2010).

2.1.1. Emergence and stand establishment

Sowing time has a significant effect on emergence and stand establishment which

is mainly associated with variation in temperature. It has been observed that late sowing

causes a reduction in emergence and stand establishment due to prevailing low

temperature at the time of sowing (Farooq et al., 2008a). Temperature <12°C causes

uneven and decreased emergence and stand establishment (Timmermans et al., 2007).

Reduction in emergence reults in less number of plants and tillers per unit area resulting

in significantly reduced crop productivity under late sown conditions (Farooq et al.,

2008a). Akhtar et al. (2012) reported that late sowing of wheat caused a reduction in

percent of final emergence which resulted in less fertile tillers and grain yield.

2.1.2. Growth and development

Optimum sowing time is essential for better stand establishment and growth of

crop plants. Late sowing produced less plant height as compared to early sowing as high

temperature during vegetative stage reduced the plant height, tiller formation, and growth

and development (Choudhury and Wardlaw, 1978). If barley is sown at optimum time it

results in higher number of productive plants and grains per spike, as compared to late

sowing (Knapp and Knapp, 1978). Late planted barley may have more chances of heat

shock that leads to less number of productive tillers, lower grain weight and number of

grains per ear (Tashiro and Wardlaw, 1999). Recently, Alazmani (2015) had suggested

8

that sowing of barley from last week of November to 5th of December showed maximum

plant height, grain yield and harvest index. It was noticed that in case of late sowing

increase in the ambient temperature at late vegetative growth stage reduced the plant

growth that ultimately lowered the crop yield. Farooq et al. (2008a) reported that late

sown wheat had lower CGR, TDM and LAI that fetched in reduced biological and grain

yield.

2.1.3. Effect of sowing time on crop yield

Timely sown barley gives higher yield and net returns. To obtain better yield, the

sowing time should be chosen to ensure favorable climatic conditions during the whole

growing period. Late sowing had significantly reduced plant height, number of fertile

tillers, spike length and panicle length (Ehdaie and Waines 1992; Alisial et al., 2010).

Early planted crop experience optimum temperature during reproductive period and attain

greater grain yield than late sown crop (Musick and Dusek, 1980). However, late planted

barley crop may be exposed to high temperature during reproductive phase that reduces

the productive tillers, grain weight and number per ear. Nevertheless, increase in

temperature during reproductive phase shortens the growing period and grain filling

duration (Tashiro and Wardlaw, 1999). Wajid et al. (2004) described that every day delay

in sowing decreases the grain yield of wheat by 39 kg/ha. Early planted crop gave higher

number of productive tillers, grain number and weight, and grain yield as well than late

planting (Alam, et al., 2006; Alisial et al., 2010). Alam et al. (2006) observed that sowing

date significantly affected the yield and related traits. Moreover, Singh et al. (1989)

noticed that late sown barley had less grain yield than early sown crop.

Early planted barley exhibits better stand establishment that consequently leads to

greater number of tillers and spikes per unit area, and grain yield by 61% because plants

have longer growth period as compared to the late sown barley (Wajid et al., 2004;

Ozturk et al., 2008). Juraimi et al. (2009) observed that when sowing of teff was delayed

by 7 and 15 days reduced plant height by 23 and 32%, spike length by 46 and 55%,

biological yield by 34 and 36%, and grain yield by 60 and 68%, respectively. Similar

results were reported by Razzaque and Rafiquzzaman (2006) that yield and related traits

i.e. spikes per m-2, grains per spike and grain weight of barley were negatively influenced

by delayed sowing as compared to timely sowing.

2.1.4. Effect of late sowing on grain quality

Late sowing negatively influences the grain quality in cereals. It was observed that

late sowing caused increase in seed dormancy in barley as compared to optimum sowing 9

time (Samarah and Al-Issa, 2006). Early planted barley had more grain protein contents

due to healthier plants with longer root systems that caused higher uptake of residual

nitrogen and had more time for grain filling as compared to late sowing (Ozturk et al.,

2008). Seleiman et al. (2011) found that late sowing reduced grain carbohydrates, as

compared to early sowing.

Late sowing exposes the plants to terminal heat stress that shortens the grain

development period as a result poor quality and shriveled grains are achieved (Ehdaie et

al., 2006; Kaur and Behl, 2010; Farooq et al., 2011). Similar results were observed in

another study that in case of late sowing occurrence of high temperature during

reproductive stage negatively affected the anthesis and grain filling duration (Tashiro and

Wardlaw, 1990), which led to poor seed vigor and grain quality as compared to early

sowing (Gooding et al., 2003; Ehdaie et al., 2006). In case of late sowing the temperature

above 30 °C during grain development stage not only altered the composition and

functions of grains but also modified the size and distribution of starch granules.

Moreover, it also increased the ratio of amylose to amylopectin but decreased the ratio of

glutenin to gliadin ratio that negatively affected the dough elasticity (Hurkman et al.,

2003).

2.2. Abiotic stresses

Changing climate can severely hamper crop productivity as crop plants are

exposed to abiotic stresses. Plant exposure to abiotic stresses induce a disruption in plant

metabolism, threaten the plant survival and the production of biomass implying at

physiological costs, thus leading to a reduction in growth can reach up to 50% in most

plant species hence, threatening the world food security (Vorasoot et al., 2003; Thakur et

al., 2010). It has been observed that abiotic stresses concequences in 50% yield reduction

in major field crops (Bray et al., 2000). Salinity, high temperature, drought and heavy

metals toxicity stress especially Cd occurring in combination or one after another which

progress into oxidative stress and cause severe cellular injury (Wang et al., 2003; Fahad

et al., 2015).

2.2.1. Drought stress

Drought is a serious hazard to world food security (Somerville and Briscoe, 2001).

Its severity depends upon occurrence and distribution of rainfall, scarcity of water

resources and evaporative water demands (Wahid and Rasul, 2005). Water is essential for

plants as growth occurs by division, elongation and differentiation of cells. However,

water deficit conditions adversely affect all these processes because cell growth is 10

drought-sensitive caused by loss of turgor pressure of the plant (Taiz and Zeiger, 2006).

Under drought stress, lowered soil moisture content may rise the soil temperature that

shows deleterious effects on growth of plants (Sekhon et al., 2010; Anjum et al., 2017b).

Drought stress affects several yield determining physiological processes viz. plant water

uptake is inhibited that leads to loss of turgor pressure of plant as a result reduced the rate

of mitosis, elongation as well as expansion of cell occurs (Nonami, 1998; Taiz and

Zeiger, 2006).

2.2.1.1. Crop growth and development

Early effects of drought stress are poor germination and stand establishment

(Kaya et al., 2006). Water deficit impairs germination and seedling growth in pea plants

(Okcu et al., 2005). Another study also described, that alfalfa plants exposed to

polyethylene glycol induced drought stress inhibited germination, shoot elongation and

seedling fresh and dry weights, except root length (Zeid and Shedeed, 2006). Plants

exposed to drought stress leads to significant reduction in leaf water status, rate of

photosynthesis and transpiration, leads to a substantial rise in plant leaf temperature and

early leaf fall (Wahid and Rasul, 2005). Drought stress adversely affects the crop growth

and development as it lowers the plant height and leaf area (Kaya et al., 2006; Hussain et

al., 2008). Deficit water stress decreases the water uptake; as a result plants close their

stomata to save moisture content that confines the CO2 uptake by leaf stomatal openings

and transpirational losses. It causes reduction in photosynthetic rate and assimilates

translocation to the plant that is necessary for grain filling. It results in increased

production of ROS and lipid peroxidation that disturbs the structure and function of

macromolecules (Rio et al., 2006; Kaya et al., 2006).

Drought significantly decreases the production of productive tillers and grains

number per ear that leads to reduction in grain yield of barley. Though water deficit

conditions affect the plants throughout its life cycle but reproductive stage is more

deleterious to economic yield of plant (Samarah, 2005; Kaya et al., 2006). At pollination

stage drought stress decreased the pollen viability and germination in maize crop, while at

flowering stage it reduced economic yield up to 40-55% in pigeon pea (Nam et al., 2001).

It is known that water deficit conditions reduce grain filling period and economic yield in

different crop plants (Samarah, 2005; Estrada-Campuzano et al., 2008).

2.2.1.2. Water and nutrient relations

Water is essential for plant mineral nutrition and drought stress affects the nutrient

uptake. Optimum soil water status coupled with fertilizer application increases the crop 11

growth and yield. Similar findings were reported by Abayomi and Adefila (2008) that

fertilizer application significantly increased the achene yield of sunflower at optimum soil

water conditions. Likewise, water deficiency disturbs the nutrient metabolism i.e. inhibits

the activity of nitrate reductase and glutamine synthetase (Rizhysky et al., 2004).

Moreover, drought stress causes 50% reduction in calcium uptake that disrupts the cell

membranes and other structures in maize.

2.2.1.3. Root-shoot signaling

Plants can survive in a wide range of environment through signal transmission that

regulates the plant behavior and growth rate. Plants sense environmental stresses and

signal is transmitted from root to shoot thus growth and functions of both shoot and root

are limited (Novák and Lipiec, 2012). Some plants develop shallow root system that

restricts water loss from their roots and survive under drought stress. Plants responses to

drought stress depend upon the rate of water uptake, leaf stomatal conductance, water

potential and turgor pressure that ultimately lowers the leaf elongation (Clark et al.,

2005). Short term exposure to drought increases root growth but long term exposure

reduces the root growth due to limited production of assimilates (Muller et al., 2011).

Furthermore, long term exposure to drought stress also reduces cation exchange capacity

of roots, nutrient uptake and relative uptake of the polyvalent cations especially

aluminum and heavy metals is increased which induces specific ion toxicity that further

decreases root growth and increases mortality rate (Huang and Eissenstat, 2000; Sekhon

et al., 2010; Lukowska and Józefaciuk, 2013).

2.2.1.4. Metabolic and biochemical processes

Water deficit conditions alter the metabolic and biochemical processes of plants. It

increases the ROS production such as super oxide anoin (O2-), singlet oxygen (O*), H2O2

and OH- (Anjum et al., 2017c). This results in oxidative stress that damages the

membranes and proteins and inhibits the enzymes activity (Zlatev and Lidon, 2012). In

response to oxidative stress plants activate the antioxidant enzymes that detoxify the

ROS. Moreover, plants produce certain metabolites that maintain the plants structures and

functions under drought stress (Farooq et al., 2009a; Zlatev and Lidon, 2012). However,

prolonged water deficit condition causes anatomical deformations, root shrinkage, and

weakens the roots-soil contact that restrict the water and nutrient supply to plants.

Drought stress reduces the biosynthesis of photosynthetic pigments, damages the

photosynthetic machinery and decreases the activities of important enzymes (Fu and

Huang, 2001; Monakhova and Chernyadèv, 2002). It might be attributed to disturbed 12

balance between the generation and detoxification of ROS through poor antioxidants

defense system (Reddy et al., 2004). It degrades the chlorophyll contents and disturbs the

ratio of chlorophyll to carotenoids contents that further induces the leaf senescence in

various crops (Yang et al., 2002a). Wheat seedlings exposed to drought stress for 7 days

caused 13-15% decrease in chlorophyll pigments and 30-40% decrease in soluble proteins

content (Chernyad’ev and Monakhova, 2003; Nikolaeva et al., 2010).

2.2.1.5. Plant biomass and yield

Water deficit stress disrupts a number of biochemical as well as physiological

processes in plants, which results in reduced growth and yield of many field crops . Effect

of drought stress varies with intensity, duration and time at which crop was exposed to

stress conditions (Plaut, 2003). Under mild drought stress plant biomass production is

more affected as compared to photosynthesis (Verelst et al., 2012). However, the rates of

photosynthesis and transpiration are considerably decreased under severe drought stress

than control (Zhang et al., 2010). Both drought and heat stress reduces the duration of

developmental growth phases and light interception couples with shortened life cycle that

might be responsible for yield reduction in cereals (Barnabás et al., 2008). It lowers the

accumulation of plant biomass, shortens the first internode length, causes premature cell

death, early senescence, fruit discoloration and damages in several plants (Vollenweider

and Gunthardt, 2005; Zlatev and Lidon, 2012). It was observed on the basis of drought

susceptibility index and water stress index that grain yield decreased significantly under

drought conditions in maize and barley (Rizza et al., 2004; Abayomi et al., 2012).

Water deficit conditions cause a significant reduction in economic yield of barley

by decreasing number of productive tillers, shriveled and fewer grains per spike, and

reduced grains test weight. It might be since drought stress decreases duration of the grain

filling stage that further reduces the activities of sucrose synthase and starch synthase as

well as extent of assimilates partitioning. It increases the time duration between silking to

anthesis stage, which leads to reduced grain yield in maize crop (Cattivelli et al., 2008).

In cotton, drought stress enhanced the flower shedding and bolls abortion that further

reduced the seed cotton and lint yield (Pettigrew, 2004).

2.2.2. Salt stress

Saline soils have excess level of soluble salts or exchangeable sodium in plant

rhizosphere. Owing to high crop water demand, limited rainfall, combined by poor water

and soil management the salinity has come to be a grave hazard to global food security

(Munns, 2002). 13

2.2.2.1. Growth and development

Salt stress negatively affects growth and development of crop plants. Deletrious

effects of salt stress vary on the basis of time, severity, duration, type of plant tissues,

stage of plant growth, and either the stress occurs slowly or suddenly (Munns et al.,

2000). Chaum and Kirdmanee (2009) had reported that progressive increase in salt stress

gradually decreased the seedlings fresh and dry weights, and plant leaf area. Salinity

stress alters plant physiological and cellular processes which results in reduced plant

growth and development (Munns, 2002; Munns and Tester, 2008; Munns, 2011). Wheat

crop exposed to salinity at germination and seedling establishment negatively influenced

the crop stand establishment as well as early seedling growth (Munns et al., 2006).

Another study also reported the same results that excess salt concentration in rhizosphere

decreased the final germination percentage and seedling growth in wheat (Afzal et al.,

2006). It might be attributed to salinity induced osmotic or drought stress, ionic stress,

nutrient imbalance and oxidative stress (Munns and Tester, 2008).

Under salt stress both Na+ and Cl- ions accumulated in guava plants that resulted

in reduced growth (Ferreira et al., 2001). Plants show different types of responses

depending upon stage of crop growth and germination is the most sensitive growth stage

(Ahmad and Jabeen, 2005), as seeds are mostly unable to germinate in saline soils.

Another study also showed that salinity stress reduced the flowering and fruit set which

resulted in reduced yield and quality of produce (Ashraf and Harris, 2004).

2.2.2.2. Photosynthesis

Salt stress adversely influences vital processes taking place within plants such as;

photosynthetic rate, protein synthesis and lipid metabolism. It causes a reduction in

stomatal conductance, photosynthesis and enhances the accumulation of salts that exerts

adverse effects on plant growth. Accumulation of salts to toxic levels causes injuries to

the leaves and thereby reduces photosynthetic area by causing the premature death of

older leaves in plants (Munns and Tester, 2008). Moreover, it reduces the photosynthetic

ability, leaf area and CO2 assimilation of many crop plants which results in reduced plant

biomass and yield (Akram et al., 2002). Tolerance of photosynthetic system to salts stress

depends on the efficiency with which plants exclude or compartmentalize toxic ions.

Furthermore, salinity causes a decrease in biosynthesis of the photosynthetic machinery.

It was noticed that salt stress caused a decrease in chlorophyll a and b contents in wheat,

as compared to control (Hanaa et al., 2008). It might be because of increased degradation

14

or decreased biosynthesis of chlorophyll by higher level of Na+ ion and lower level of

Mg2+ ion in plants at severe salinity stress (Rubio et al., 1995).

2.2.2.3. Physiological and biochemical processes

Salt stress lowers the osmotic potential through sodium and/or chloride toxicity,

altering protein synthesis (Farsiani and Ghobadi, 2009), that ultimately reduces the seed

germination (Khaje-Hosseini et al., 2003). It disrupts the mineral uptake, cell membranes,

subcellular and cellular organelles thus decreasing the growth and causing anomalous

development even results in plant death (Yasmeen et al., 2013; Farooq et al., 2015). Salt

stress causes inhibition of cell division and expansion, osmotic imbalance, disturbs

enzyme functioning that leads to higher accumulation of ROS (Mahajan and Tuteja,

2005). Moreover, salt stress disrupts the ion uptake, synthesis of proteins and nucleic

acid, photosynthesis, hormonal balance, activities of enzyme and osmotic adjustment that

ultimately lead to growth retardation (Dumbroff and Cooper, 1974). Salinity lowers the

soil osmotic potential that reduces the root water uptake and plants close their stomata to

save water loss thus reduce the CO2 uptake. Decreased CO2 in mesophyll cells reduce the

rate of photosynthesis and enhances the production of ROS (Ashraf and Harris, 2004).

However, in response to salt stress plants accumulate compatible solutes and osmolytes to

maintain their tissue water status. Salinity reduced the chlorophyll a, b and a+b in sweet

maize plants due to the fact that high concentration of salt stress injury disrupts the plant

structures and functions (Chaum and Kirdmanee, 2009).

Salinity stress negatively affects the de novo synthesis of D1 and other important

proteins (Murata et al., 2007). Furthermore, it suppresses the activity of Rubisco, inhibits

the CO2 fixation and protein synthesis that disturbs the balance between ROS generation

and detoxification. Furthermore, high concentration of Na+ ion in plant tissues reduces the

activity of ATP synthase that decreases the level of intracellular ATP that is crucial for

protein synthesis (Allakhverdiev et al., 2005). It has been observed that, it induces the

photo-damage to PSII in barley, rye and sorghum (Sharma and Hall, 1991; Hertwig et al.,

1992). Another study also reported the similar findings that excess concentration of salt

stress either stimulated the photo-damage to PSII or repressed the repair of PSII (Murata

et al., 2007).

2.2.2.4. Plant biomass and yield

Salt stress affects numerous physiological functions and processes like respiration,

photosynthesis, nitrogen fixation, starch synthesis, and source-sink limitations which are

the main reasons of poor grain setting that ultimately lowers the grain yield (Hiyane et al., 15

2010; Turki et al., 2012). Studies have indicated that salinity stress causes considerable

decline in grain yield (Schubert et al., 2009; Kaya et al., 2013). Under salt stress the salt

concentration in plant parts and tissues is increased to toxic level that diminishes the plant

growth and yield (Ashraf and Harris, 2004; Franzen, 2007).

It has been observed that salinity causes a reduction in number of productive

tillers m-2 and spikelets as well as grains per ear, and biological and grain yield (Ahmad et

al., 2003; Saffan, 2008). Similarly, salinity severely affects the yield and related

parameters of wheat. It was observed that number of spikelets per spike were decreased

much more by salt stress as compared to number of grains and grain weight at maturity

(Salah et al., 2005). Rice seedlings exposed to different levels of salt stress showed

decreased shoot and root dry weight, number of productive tillers, panicle length, number

of kernels per panicle, grain weight and grain yield. Nonetheless, it was observed that

grain sterility was increased with an increase in Na+ accumulation in rice shoots

(Mahmood et al., 2009a).

2.2.3. Osmotic stress

Salt stress causes its deleterious effects in two ways viz. osmotic stress (decline in

water potential) and ionic stress (ionic imbalance and specific ion toxicity) (Parida and

Das, 2005). First and foremost outcome of salt stress is osmotic stress. It occurs

immediately due to the high concentration of salts in the rhizosphere that reduces the

growth of new leaves and shoots (Munns and Tester, 2008). Salinity affects the plant

growth through osmotic preservation of water which decreases plant’s access to water by

increasing the concentration of salt in external environment of plants (Afzal et al., 2006).

Salt stress inhibits the seed germination by limiting the water uptake which concequently

leads to decreased radical emergence (Al-Karaki, 2000). Salt stress affects the

germination of seeds by establishing lower osmotic potential in external environment of

seed which prevents the water imbibition (Khaje-Hosseini et al., 2003). Salt stress

induces both hyper-osmotic as well as hyper-ionic stress that result in a considerable

decrease in crop yield (Mahajan and Tuteja, 2005). High levels of salt stress cause decline

in soil water potential which renders the plants unable to acquire water and nutrients from

soil thereby decreasing growth and development of plants. Salt stress induced osmotic

stress decreases the seedling shoot and root growth (Munns, 2002).

2.2.4. Ion toxicity

The second and slow effect of salt stress is the specific ionic toxicity on

protoplasm which increases salt concentration in plant cells (Munns and Tester, 2008; 16

Tabassum et al., 2017). Salinity-induced ion toxicity perturbs the plant water relations,

disturbs the activity of enzymes, enhances the specific ion toxicity and disrupts the

balance of ROS production and detoxification (Farooq et al., 2015, 2017; Tabassum et

al., 2017). Salt stress affects crop plants at each growth stage beginning from the

germination upto maturity by ionic and/or osmotic stress (Al-Karaki, 2000). Salinity

affects the crop growth and yield by perturbing osmotic and ionic equilibrium within cells

(Mahajan and Tuteja, 2005). Ionic stress occurs over time due to inability of plant to

restrict the influx and enhance the efflux of Na+/Cl− ion in plant tissues (Munns and

Tester, 2008). Salinity effects the germination of seeds both through osmotic stress and

Na+/Cl− ion toxicity to the seeds during imbibition (Khaje-Hosseini et al., 2003). Ionic

stress enhances the senescence of older leaves (Munns and Tester, 2008). Ionic stress

causes deficiency or toxicity of essential nutrients and tissue injuries (Munns and Tester,

2008). Osmotic stress inhibits more shoot growth than root growth (Hsiao and Xu, 2000).

2.2.5. Heavy metals stress

Heavy metals are a set of semi metals (metalloids) and metals which are related to

pollution combined to potential toxicity (Granero and Domingo, 2002; Govil et al., 2008).

Owing to their variation in concentrations, toxicity levels, speciation and specifications,

they pose a severe risk to crop productivity, thus directing a widespread series of plants

(Arshad et al., 2008). Among several heavy metals that affect plants, Cd is most toxic

pollutant after lead (Pb). Depending upon its toxicity in plants which influence the plant

growth and development, different plant species and cultivars behave differently under

varied concentration of Cd as some cultivars are sensitive to even very low concentrations

while others are tolerant to very high concentrations (Fahad et al., 2015). Its easy uptake

and translocation within plants make it more toxic to affect several morphological,

physiological, biochemical and structural events of the crop plants (Xu et al., 2014; Fahad

et al., 2015). Cadmium toxicity increases the cell membrane permeability and leakage of

electrolytes following ROS production at cellular and sub-cellular levels that creates

oxidative stress. It enhances the lipid peroxidation and damages to macromolecules with

concomitant cell death that ultimately leads to stunted plant growth (Mahmood et al.,

2009b).

2.2.5.1. Seedling growth

High Cd concentration in rhizosphere causes reduced rate of photosynthesis,

evaporation, transpiration, cell metabolism, water and nutrient uptake, inhibition of

enzymes activities, deficiency of nitrogen and phosphorus. All these leads to inhibited 17

growth and accelerated maturity, even death of plant (Cheng and Huang, 2006).

Furthermore, Cd stress causes the osmotic stress. Cadmium stress reduced the seedling

growth and development in maize, when compared with control (Malekzadeh et al.,

2007). Tiryakioglu et al. (2006) observed similar results in barley that Cd toxicity stress

caused reduction in root and shoot elongation especially elevated level of Cd was more

deleterious to root growth than shoot growth. It might be because roots come in contact

directly to Cd as compared to shoot. Kumari et al. (2011) reported that Cd stress reduced

fresh and dry weight of Vigna radiata L seedlings. Similar results were observed in

another study due to its negative effect on the photosynthesis rate (Metwally et al., 2003).

Gradual decrease in seedling growth of Leucaena leucocephala was observed with

progressive increase in Cd concentration (Muhammad et al., 2008).

2.2.5.2. Morphological and biochemical processes

Cadmium directly and indirectly affects plant metabolism as it causes the

oxidative stress. It has been observed that chloroplast is sensitive to Cd toxicity (Sandalio

et al., 2001). It disturbs the balance between ROS production and detoxification as a

result inhibits the functions of photosystem II (PSII) (Sigfridsson et al., 2004). Cadmium

stress reduces the total carbohydrates content and increases the total soluble sugar content

in seedling of V. radiata L. as compared to control. Moreover, it has been observed that

Cd toxicity stress decreases the soluble proteins content in V. radiata L. seedlings (Verma

et al., 2012). Cadmium stress causes chlorosis, leaf rolling, necrosis, and reduces the

activity of enzymes that inhibit the photosynthesis and transpiration (Gouia et al., 2000;

Benavides et al., 2005). Aditionally, it disrupts the plant water status through lowered

relative water content, increased stomatal resistance and reduced root and leaf expansion

(Perfus-Barbeoch et al., 2002).

Cadmium stress disturbs the nutrient balance, modifies the genes expression and

enhances the production of ROS (Herbette et al., 2006; Sandalio et al., 2009).

Furthermore, it causes severe damages to cell constituents viz. DNA, RNA, proteins and

lipids that leads to decreased growth (Schutzendubel and Polle, 2002; Grara et al., 2012).

In response, plants had developed a complex antioxidant defense system (enzymatic as

well as non-enzymatic) to detoxify and scavenge these ROS and protect cellular

membranes and macromolecule (Pinto et al., 2003). A short term exposure to Cd stress

increases the activity of antioxidant enzymes but prolonged exposure decreases activity of

these enzymes (Sandalio et al., 2001).

2.2.6. Heat stress18

Rise in the ambient temperature beyond a threshold for time span which induces

permanent damage to growth and development of plants is reffered to as heat stress. It is a

complex function of intensity (in degrees) and the rate of increase in temperature, and

duration (Wahid et al., 2007). The magnitude to which heat stress ensues in a specific

climate zone depends on the likelihood and period of the high temperature which occurrs

during day and/or night. The heat stress caused by high ambient temperature is becoming

the serious menace for crop production all over the world (Hall, 2001). Generally, 10-

15°C sudden increase in temperature above ambient is termed as heat stress. An estimate

has been made that with every 1°C rise in atmospheric temperature soil temeperature

could increase by 1.5°C (Ooi et al., 2012). Severe cell damages and/or even death could

be caused by short-term exposure to very high temperature within a short time (Schoffl et

al., 1999); while, it might take a long time until cellular damages under moderate high

temperature. The denaturation and/or aggregation of proteins with concomitant increase

in fluidity of cell membrane lipids are the direct harms caused by high temperature stress.

However, slower or indirect injuries due to heat stress consist of enzyme inactivation in

the mitochondria and chloroplast, protein degradation, inhibition of the protein

biosynthesis and decreased stability of cellular membranes (Howarth, 2005).

2.2.6.1. Growth and development

Heat stress adversely effects the growth and development of crop plants. Mild

heat stress speed up the growth rate but severe heat stress causes reduction in rate and

duration of growth in wheat plants. It causes seedling growth inhibition, leaf abscission,

leaf chlorosis and necrosis, which results in reduced biomass and economic yield

(Vollenweider and Gunthardt, 2005). High temperature from the germination to grain

formation shortens the plant life cycle (Wollenweber et al., 2003). Spring wheat sown at

high night temperature significantly decreased the duration of three important growth

stages (flowering, grain formation, and maturity) (Prasad et al., 2008a). Heat stress

decreased the shoot length, leaf number and dry weight in wheat. Furthermore, it reduced

the spike bearing tillers m-2, floral organs, grain formation and grains per spike (Yang et

al., 2002b; Prasad et al., 2008a).

2.2.6.2. Photosynthesis and transpiration

Optimum temperature is very important for photosynthesis and transpiration.

However, rise in temperature from 22 to 32°C lowers the rate of photosynthesis and

transpiration (Zhang et al., 2010). Furthermore, it has been observed that both heat and

drought stress reduces the stomatal conductance and photosynthetic activity (Crafts-19

Brander and Salvucci, 2002; Ashraf and Harris, 2013). Abrupt rise in leaf temperatures (>

38°C) is more deleterious for net photosynthesis rather than gradual increase in

temperature (Crafts-Brander and Salvucci, 2002). It might be attributed to a decrease in

internal CO2 concentration, activity of enzymes that were responsible for photosynthesis

and ATP synthesis (Zlatev and Lidon, 2012).

Among various physiological processes photosynthesis is the most sensitive one

to high temperature. As a short term exposure to high temperature disables the activity of

Rubisco and oxygen-evolving complex of PSII (Haldimann, and Feller, 2004; Suleyman

et al., 2007). Heat stress suppresses the efficiency of photosystem (PSII) through limiting

the transport of electrons, external proteins degradation/removal, and release of Mg2+ and

Ca2+ from their binding sites (Wahid et al., 2007; Barta et al., 2010). As a result, reaction

center of chlorophyll (PSII) produces singlet oxygen which concequently damages the D1

and D2 proteins in chloroplast (Yoshioka et al., 2006). Heat stress disrupts the balance

between damage and repair to PSII complex of photosynthesis. Moreover, it suppresses

the de novo synthesis of D1 and other essential proteins (Murata et al., 2007).

2.2.6.3. Molecular and biochemical processes

Heat stress denatures the proteins; increased fluidity of membrane bounded lipids,

inactivates the enzymes, reduces de novo protein synthesis and disrupts the membrane

integrity (Howarth, 2005; Kozlowska, 2007). If plants are exposed to moderate heat stress

they may face severe cellular injury, decrease in biosynthesis of chlorophyll, increase in

amylolytic activity, dissolution of the thylakoid grana and interruption of the assimilate

transport or even death at short term exposure to very high temperature (Kozlowska,

2007; Wahid et al., 2007). Furthermore, it reduces the ion fluxes and enhances production

of ROS and toxic compounds that may harm cells (Howarth, 2005).

2.2.6.4. Yield and yield related traits

Heat stress affects the plants from flowering to grain filling stage that leads to

often reduced crop yield due to limited growth of grains (Guilioni et al., 2003). Heat

stress prevailing during grain formation modifies seed nitrogen contents in grains of

legume crops (Sekhon et al., 2010). Furthermore, it reduces the grain protein content,

starch granules and oil contents in maize and wheat (Wilhelm et al., 1999). It also affects

the grain formation and baking quality of the flour in cereals (Balla et al., 2011).

Moreover, heat stress when combined with drought stress shows more deleterious effects

on grain yield and quality compared with alone heat stress (Balla et al., 2011).

20

Under heat stress abnormal ovary formation combines with poor pollen tube

development causing shriveled pollens and reduced grains per spike (Saini and Aspinall,

1982; Saini et al., 1983). Another study had shown that pollens are highly sensitive to

high temperature as it reduced the floret sterility, pollen germination and viability (Prasad

et al., 2006a). Similar results have been observed in rice (Prasad et al., 2006b), wheat

(Prasad et al., 2008a), peanut (Prasad et al., 2011a), barley (Sakata et al., 2000) and

sorghum (Prasad et al., 2011a) that heat stress diminished the formation, viability and

longevity of pollens that ultimately leads to pollen shedding and poor grain setting. Heat

stress induced leaf senescence decreases the activity of starch synthase, assimilates

translocation and partitioning to the developing grains that results in smaller and shriveled

grains (Prasad et al., 2006b, 2008b). Yang et al. (2002a) and Prasad et al. (2008a)

described that heat stress 10°C above ambient temperature (20/15°C) causes up to 50%

decline in final grain weight and 70% in grain yield of wheat plants.

2.3. Mechanisms of abiotic stresses tolerance

2.3.1. Drought stress

Plants respond to drought stress alterations in morphological, biochemical and

physiological attributes (Farooq et al., 2009a). Change in leaf and root architecture,

stomatal closure to avoid water loss, production and accumulation of compatible solutes,

osmotic adjustment, and production of abscisic acid (ABA), and induction of the

dehydrins are few mechanisms which have been evolved by plants to tolerate drought

stress by maintaining high leaf water potential and tissue water status (Turner et al.,

2001). The drought resistance is capability of crop plants to maintain better growth and

produce biomass with limited water supply or deficit water conditions (Passioura and

Angous, 2010).

Osmotic adjustment is an essential drought tolerance mechanism which assissts

the plants in surviving under dehydration conditions (Farooq et al., 2009a). It is

accomplished by accumulation of a variety of osmotically active ions or molecules such

as proline, glycine betaine, sugar alcohols, soluble sugars, sorbitol, trehlose, glutamate,

citruline, organic acids, K and Ca ions (Folkert et al., 2001; Serraj and Sinclair, 2002;

Farooq et al., 2008b; Farooq et al., 2009a). Under drought stress, plants accumulate these

solutes which lowers their osmotic potential and consequently water moves into cells

from the surroundings thereby maintaining the cell turgor and continue metabolic

activities in cells. With osmotic adjustment, activities of cytoplasm and cell organelles

continue normally which help the plants to maintain better growth, photosynthetic 21

activities and assimilate partitioning to developing grains (Ludlow and Muchow, 1990;

Subbarao et al., 2000).

Membrane stability is an important index for drought tolerance (Folkert et al.,

2001). In plants, the ROS are produced as a byproduct in response to numerous metabolic

activities (Rio et al., 2006). These ROS may serve as damaging, signaling or protective

elements depending on the equilibrium in synthesis and detoxification. The osmolytes

produced by plants rescue the cellular membranes from ROS (Folkert et al., 2001; Farooq

et al., 2009a). Moreover, antioxidants are produced by plants for protection from ROS in

response to abiotic stresses (Gill and Tuteja, 2010). Plants accumulate free leaf proline in

greater concentrations under drought which acts as osmoprotectant and/or compatible

solute, and induces drought tolerance in plants (Yamada et al., 2005). Molecular

mechanisms for drought tolerance include the production of ABA, and expression of

stress responsive genes and some transcription factors which are responsible for induction

of stress tolerance in plants (Farooq et al., 2009a).

Abiotic stresses prompt the expression of groups of two types of genes. First type

of group of genes are accountable for the protection of cells by enancing the osmolytes,

detoxifying damaging compounds, protecting and recycling proteins, and maintaining the

stability of cellular membranes (Shinozaki and Yamaguchi-Shinozaki, 2000); whereas,

econd type of group of genes involves expression of regulatory genes under stressed

conditions (Seki et al., 2003). Proline, an osmolyte, which is enhanced in response to

drought in the transgenic plants carries the gene coding for the osmolytes, thus making

the mechanism of protection against the oxidative-stress rather than osmotic-adjustment

(Vendruscolo et al., 2007). Wheat plants respond to drought by efficient assimilate

remobilization from the stem to grains by synchronized gene-expression which may

protect the premature cell death of wheat stem (Bazargani et al., 2011).

2.3.2. Salt stress

Water status, hormonal regulation and the availability of photosynthates are main

controlling elements in saline or drought conditions; while, in saline soils the hormonal

balance is more critical than water status (Munns, 2002). Salt resistance may be defined

as the genetic potential of a plant to withstand the damaging effects of salt stress in their

leaves and/or rhizosphere while avoiding the disturbance in their normal functioning

(Shannon and Grieve, 1999). Osmotic adjustment is an important echanism in plants

which are adapted to low water potential induced by salinity (Flowers et al., 2010).

Compatible solutes are osmoticum produced for safer accumulation but it requires energy 22

and hence the plants have to suffer the decreased growth rate (Munns and Tester, 2008).

Ionic balance is an important tool to maintain the normal plant metabolism under salt

stress. Plants control the expression of H+ pumps, and Na+ and K+ transporters to enhance

the uptake of ions which act as osmolytes and/or osmoprotectants such as K+, Mg+2 and

Ca+2 while restrict uptake of Na+ and Cl- ions by roots (Zhu et al., 1993).

Primarily, plants employ different mechanisms to tolerate the salinity stress such

as to avoid the entry of Na+ and Cl- ions in high concentrations in different plant parts but

if salts enter in plants then plants try to protect the plant tissues through ion exclusion

from roots or compartmentalization of these ions into cell vacuoles (Silva et al., 2010).

Another study also described the same adaptive mechanism for salt tolerance that plants

either exclude the salt from roots or store them in their vacuoles (Munns and Tester,

2008). Plants generate the proton motive force and exchange the Na+ with H+ ions

through plasma membrane H+-ATPase. Similarly, plants use the tonoplast H+-ATPase and

H+-pyrophosphatase proteins for vacuolar compartmentalization (Rodríguez et al., 2009;

Ye et al., 2009; Leidi et al., 2010; Pasapula et al., 2011). Salt tolerant plants develops the

high concentration of Na+/H+ antiporter (NHX1) to limit the sodium and chloride ion

inclusion (Pasapula et al. 2011). Plants overexpress the salt tolerance responsible

AtNHX1genes to sequestrate high concentration of Na+ and Cl- ions (Leidi et al., 2010;

Silva et al., 2010).

For long time exposure to salt stress plants produce or accumulate high

concentration of osmolytes like; proline, glycine betaine, polyols, sugars (fructose and

sucrose), polyamines and organic acids (malate, oxalate) (Valliyodan and Nguyen, 2006).

Production of ROS possess secondary stress in saline condition (Chaves et al., 2003) and

plants produce such substances which detoxify these detrimental species. Some enzymes

act as scavengers of these destructive oxygen species. Garratt et al. (2002) has mentioned

these enzymes such as CAT, SOD, glutathione reductase (GR) and glutathione-S-

transferase (GST). Plants manipulate these enzymes to synthesize osmolytes and

osmoprotectants which helps in osmotic adjustment and scavenging of ROS (Krishnan et

al., 2008; Chen and Murata, 2008). Another study also supports the same concept that

under salt stress plant accumulates high concentration of proline that not only helps in

osmotic adjustment but also maintain the cellular activities under salt stress conditions

(Verdoy et al., 2006).

2.3.3. Cadmium stress

23

Cadmium is potentially toxic for both plants and animals even at very low

concentrations can cause severe damages. Plants have developed several mechanisms to

resist/tolerate the Cd stress such as; lower uptake as well as accumulation of cadmium in

plant parts. Among the tolerance mechanisms plants use the metal chelation and

sequestration through particular ligands. For that purpose, plants accumulate both Cd and

metal-binding ligands such as; phytochelatins (PCs) and metallothioneins (MTs) in their

vacuoles (Hall, 2002; Cobbett and Goldsbrough, 2002). Plant accumulates phytochelatins

to bind the cadmium ions through PC-Cd or Cd-malate complexes in their vacuole

(Cobbett and Goldsbrough, 2002).

Hyperaccumulation is another adaptive and complex phenomenon to accumulate

high metals concentration in their shoots such as edible leaves and maintain a low metal

concentration in their roots (Kramer, 2010). Hyperaccumulation is the ability of some

metal tolerant plants to safely store high metal levels in their tissues without facing any

cellular damage. Metal hyperaccumulation is the molecular mechanisms for the

development of phytoremediation and biofortification technologies (Kramer, 2010; Shao

et al., 2010). It includes the transport of metal across the plasma membrane of root cells,

xylem loading and translocation, metal detoxification and sequestration at plant and

cellular levels (Lombi et al., 2002).

Cadmium toxity stress causes oxidative stress and plants synthesize and

accumulate high concentration of glycine betaine, proline, sugars, organic acids, polyols,

amino acids, and peptides and polypeptides (Rauser, 1999; Gill and Tuteja, 2010).

Another study also described the similar results that under Cd stress, plants use PCs to

detoxify the ROS (Maier et al., 2003). Furthermore, plants detoxify or scavenge the ROS

through enzymatic (SOD, CAT, ascorbate peroxidase and glutathione peroxidase) and

non-enzymatic antioxidants (α-tocopherol and ascorbate) (Pinto et al., 2003).

2.3.4. Heat stress

Under heat stress plant adopt several mechanisms to survive in such lethal

conditions. Heat tolerant plants acquire thermo-tolerance mechanism through pre-

exposure to sub-lethal temperature to cope with heat stress (Wahid et al., 2007). Plants

use heat-shock proteins (HSP32 and HSP101), ABA signaling, regulate gene expression

and systematic acquired pathway to protect plant cellular structures against heat stress

(Larkindale and Huang, 2005; Charng et al., 2006). Stress perception and signal

transduction is another adaptive mechanism for heat stress tolerance (Chinnusamy et al.,

2004). Plants use Ca2+ signaling pathway, plant stress related hormones (ABA, ethylene) 24

and redox system that activates the genes responsible for heat shock proteins and alters

the membrane fluidity and ratio of saturated to unsaturated fatty acids (Joyce et al., 2003;

Suzuki and Mittler, 2006).

Another study described that, under heat stress, the plants transduce signal to

mitogen activated protein kinase (MAPK) and as a heat shock response the cytosolic Ca2+

concentration increases sharply (Larkindale and Knight, 2002; Kaur and Gupta, 2005).

Plant uses the Ca2+ influx, heat-shock activated MAPK (HAMK), calmodulin (CaM)

related genes and Ca-dependent protein kinases (CDPK) to alleviate heat stress (Sangwan

and Dhindsa, 2002; Liu et al., 2003). It has shown that cytosolic Ca2+ concentration raises

that regulate the plant responses to increase the activity of antioxidants and maintain

turgor pressure in guard cells (Wahid et al., 2007).

Sung et al. (2003) reported that as a heat shock response the plants use heat shock

proteins, dehydrins, chaperone, antioxidants enzymes, osmolytes and osmoprotectants in

their cytoplasm to protect the structures and functions of essential proteins and

macromolecules. Heat shock proteins ensure the three dimensional structure of cell

membrane proteins to maintain the cellular structures and functions against heat stress

(Wahid et al., 2007). Another study has shown the same results that barley seeds pre-

treated with glycine betaine improved the cell membrane stability, rate of photosynthesis;

shoot dry mass and leaf water potential as compared to control (Wahid and Shabbir,

2005).

2.4. Management of abiotic stresses

Tolerance to abiotic stresses by plants follows a complex mechanism, and plants

use a series of adaptive mechanisms to withstand it. For example, under saline soil

conditions plants modulate a number of physiological processes viz. stomatal regulation,

osmotic adjustment, maintenance of tissue water status, hormonal balance, ion

homeostasis and activation of the antioxidant defense system (Hichem et al., 2009; Kaya

et al., 2010; Jafar et al., 2012). Similarly, in response to drought stress plants produce

certain antioxidants (enzymatic and non-enzymatic) for protection against ROS (Gill and

Tuteja, 2010). Furthermore, plants maintains more negative water potential than

surrounding soil and accumulates compatible solutes viz. proline, sugars, polyols, glycine

betaine, mannitol and sorbitol that assist in drought tolerance though act as ROS

scavengers and chemical chaperones (Taiz and Zeiger, 2006). Tolerant plants manage the

abiotic stress conditions by using the strategies such as osmotic adjustment, ion exclusion

through roots, ionic compartmentalization, maintenance of tissue water status, nutrient 25

balance, higher synthesis/accumulation of osmolytes/osmoprotectants and higher

detoxification or scavenging ability (Athar and Ashraf, 2009). Scientist also suggests that

abiotic stresses can be managed through good cultural practices. Among these the

possible strategies/cultural practices are selection of abiotic stress tolerant varieties,

timely sowing to avoid heat stress at reproductive stage and seed priming are more

important ones.

2.4.1. Selection of stress tolerant varieties

Drought stress effects the crop growth and development; depending upon the

intensity of stress and yield potential. As high yielding varieties are more preferred under

mild drought stress, whereas; high drought tolerant varieties would be more beneficial

under severe drought stress (Panthuwan et al., 2005; Rizza et al., 2004). Zhao et al.

(2014) compared two rice varieties based on plant height, leaf relative water content, leaf

and root K+ and Na+ concentration, root length, root weight, sugars and proline contents in

leaf and root tissues under normal and salt stress conditions. It was observed that salt

tolerant variety performed better for all these traits except leaf and root Na+ concentration

which was accumulated more in salt sensitive variety. In another study relative water

content, chlorophyll fluorescence, leaf gas exchange characters and RNA-Sequencing

were used to evaluate the drought tolerant and susceptible sorghum varieties (Fracasso et

al., 2016). Under normal and drought stressed conditions, two barley varieties were

differentiated for their resistance or susceptibility by using traits viz. plant height and

biomass, number of spike bearing tillers, spikelets and grains per spike, grain yield and

grain protein content.

It was observed that resistant genotype gave better results for all above mentioned

traits as compared to susceptible genotypes. Furthermore, drought tolerant genotype

accumulated more sugars, leaf proline, leaf glycine betaine and carbohydrate contents

under stressed conditions compared with drought susceptible genotypes (Chmielewska et

al., 2016). Amanullah et al. (2011) compared two barley and six wheat varieties under

water deficit and normal conditions. Based on yield and related traits, wheat varieties

were recommended for cultivation in dryland areas as compared to barley cultivars. In

soybean, there exists a genotypic difference to drought tolerant and susceptible varieties.

Varieties with more leaf proline accumulation and better root traits are preferable to

cultivate under drought conditions (Mwenye et al., 2016).

Kumawat et al. (2017) compared ten lentil varieties for their salt

tolerance/sensitivity based on dry matter yield and stress tolerance indices and stress 26

susceptibility index. Varieties with higher economic yield coupled with lowered values of

stress tolerance indices were preferred for salt stressed conditions then other varieties.

Similarly, under water deficit conditions drought tolerant variety of wheat gave higher

productive tillers and grain yield than susceptible ones (Matsunaka et al., 1992; Yasin et

al., 1993). In another study four wheat cultivars were compared against drought stress at

vegetative and reproductive stages and cultivar with higher leaf relative water content and

water potential was recommended than other ones (Siddique et al., 2000). Moreover,

Dhanda et al. (2004) screened the 30 wheat varieties against drought stress and varieties

with higher seed vigor index, germination percentage, shoot and root length were

preferred for cultivation under water deficit conditions.

2.4.2. Seed priming in abiotic stress tolerance

Abiotic stresses can be managed in plants through conventional breeding,

molecular engineering of specific genes and their introduction into crop plants. However,

these approaches need more time and resources coupled with the complex process to

stress tolerance and genetic characters into environment interaction, it is very difficult to

understand the key molecular mechanisms associated with stress tolerance. However,

seed priming is the most viable approach and has the potential just to overcome abiotic

stresses (Farooq et al., 2009a).

Seed priming is a low cost, easier, and low risk practice and an alternate method

used to overcome abiotic stresses. It has been observed that seed priming improves the

germination and seedling growth in normal (Khan, 1992) as well as salt stressed

conditions (Basra et al., 2005). Pre-sowing seed treatments with water (hydropriming),

salts (osmopriming) and microbes (biopriming) stimulate the germination processes and

gene expression for osmolytes and antioxidants to protect the plants from oxidative

damage under abiotic stress conditions (Cantliffe, 2003; Afzal et al., 2006). Pre-sowing

seed treatments enhance the seed germination and stand establishment in stressed

environments (Farooq et al., 2009b). Janmohammadi et al. (2008) stated that

hydropriming improved the final emergence percentage, germination index and growth of

maize seedlings under salinity stress. Primed seeds took less time for germination and

gave good stand establishment (Harris et al., 2002). Seed priming stimulates mobilization

of inorganic solutes/essential metabolites to germinating seeds (Taiz and Zeiger, 2002).

27

Enhanced germination rate and uniform germination which are the consequences

of seed priming have been employed to overcome drought stress in crop plants (Farooq et

al., 2007, 2009b). Seed priming allows pre-germination metabolic activities to happen

within seeds upto the level limited to that instantly precedes radicle emergence. Seed

priming improves growth and yield of crop plants under normal and stressed conditions

as well. Higher grain yield of wheat was observed by seed priming with KCl under saline

and water deficit conditions (Ghana and Schillinger, 2003). Seed priming with 4% KCl

solution and saturated CaHPO4 solution improved final germination, crop stand

establishment and crop yield under drought stress (Harris et al., 2002). Similarly, seed

priming with arginine solution improved growth, grain and biological yield, harvest

index, and grain soluble sugars, amino acids and protein contents in wheat (Amir and

Qados, 2009).

Seed priming has been found to improve the germination and water use efficiency

of wheat under drought stress (Ajouri et al., 2004). It helps in improving the drought

resistance by its beneficial effects such as faster and uniform emergence, early flowering

and improved grain yield (Kaur et al., 2005). Osmopriming of wheat seeds improved the

grain yield in field and glass house environments (Eivazi, 2012). When seeds were

primed with organic/inorganic salts, plant growth regulators and compatible solutes then

seedlings’ growth and development was improved (Afzal et al., 2006; Pill and Savage,

2008). It has also been observed that seed priming caused an increase in the CAT and

SOD activities (Basra et al., 2004). Therefore, seed priming with inorganic or organic

substances may be used to improve germination and stand establishment under abiotic

stresses.

2.4.2.1. Osmopriming with calcium salt and abiotic stress tolerance

Calcium is a main component of plant signaling transport pathway. It stabilizes

the structure of cell membranes and proteins that are embedded in membranes. It

regulates a number of plant processes such as cell growth (cell division, elongation and

differentiation), photomorphogenesis, cell polarity, cytoplasmic streaming, plant defense

system and thigmotropism under normal as well as stressed conditions (Nayyar, 2003).

Under stress conditions Ca2+ acts as secondary messenger that stimulates the expression

of genes that were responsible for osmolytes production (White and Broadley, 2003).

Furthermore, it improves the plant growth by regulating the mitotic activities, cell

membrane stability and integrity, and structural strength of cell walls (Hepler, 2005).

Exogenously applied calcium through seed priming helps the plants in ameliorating the 28

damaging effects of salinity by declining the Na+ ion influx and enhancing the K+ ion

efflux through non-selective cation channels (Shabala et al., 2006; Rathod and Anand,

2016).

Seed priming with CaCl2 increases the accumulation of osmolytes in wheat plants

exposed to salt stress from stand establishment to maturity (Tabassum et al., 2017). For

instance, seed priming with CaCl2 improved germination and seedling establishment of

rice in greenhouse study (Ruan et al., 2002a, b). Moreover, seed priming with CaCl2

improved the protein contents under salt stress conditions as calcium protects the cell

membrane (White and Broadley, 2003; Mahboob et al., 2015). Likewise, more 1000-

grain weight for rice was obtained through seed priming with CaCl2 followed by KCl

(Farooq et al., 2006b). Calcium enhances the production and accumulation of compatible

solutes (proline, glycine betain, sugars and polyols) and helps in osmotic adjustment

(Girija et al., 2002). Exogenous application of Ca2+ alleviates the deleterious effects of

salt stress on crop plants, as it stimulates uptake of K+ than Na+ ion (Hasegawa et al.,

2000). Seed priming with 1.5% solution of CaCl2 improved the leaf area, leaf relative

water content, leaf water potential, leaf osmotic potential, number of grains per spike,

grain weight and grain yield in wheat under salt stress (Tabassum et al., 2017).

2.4.2.2. Biopriming with PGPBs and abiotic stress tolerance

Plants face numerous abiotic stresses under field conditions. When plants fail to

avoid or tolerate primary stresses (drought, salinity, heat and heavy metals stress) then

secondary stress (oxidative stress) occurs that leads to production of ROS. Although

ROS have some benefits at low concentrations as they act as signaling compounds under

stress conditions but at high concentrations they interact with cell membranes and

macromolecules such as lipids, proteins and DNA (Munne-Bosch and Penuelas, 2003;

Reddy et al., 2006). Reactive oxygen species impair the normal functions of cells through

oxidative damage. Plants produce compatible solutes (proline, glycinebetaine,

polyamines), certain antioxidants (enzymatic and non-enzymatic) and activate various

defense systems to scavenge and detoxify these ROS (Gill and Tuteja, 2010).

Plant growth promoting bacteria acts as an alternative to chemicals. These

microorganisms ensure accessibility of necessary nutrients to crop plants, improves

nutrient utilization efficiency, seed germination, root development and abiotic stress

tolerance of crop plants (Dobbelaere et al., 2003; Khalid et al., 2009; Mitter et al., 2013).

Proposed ways by which PGPBs enhance growth and nutrition of plants under normal

and stressed conditions are phytohormones production, biological nitrogen fixation, plant-29

microbe symbiotic associations, inhibition the ethylene production, along with improving

the availability of macronutrients like Fe, P and other microelements, and growth

improvement by volatile composites (Hardoim et al., 2008; Mitter et al., 2013).

Plant related bacteria may release osmolytes such as proline, trehalose, glycine

betaine, mannitol and sorbitol in response to the stress combined with other PGPB traits

may act symbiotically with other plant-made osmolytes that enhance the plant growth

under less than optimal growth conditions (Paul and Nair, 2008). Seed priming with

endophytic bacterial strains develops a more efficient root architecture that improves the

relative water contents of plants under water stress conditions (Fisher et al., 2000; Lucy

et al., 2011; Dodd et al., 2010). Stress stimulated ethylene production was decreased

through inoculant strains containing 1-aminocyclopropane-1-carboxylate (ACC)

deaminase activity resulting in more proliferated roots systems, which help the water

uptake from deeper soil layers (Dodd et al., 2010; Vardharajula et al., 2011). Seed

priming with enterobacter spp. strain FD17 have the potential to efficiently colonize the

plant rhizosphere and considerably improves the biomass production, leaf area, number of

leaves per plant and economic yield up to 39, 20, 14 and 42%, respectively. Similarly, in

maize plants it improved the time to flowering and photochemical efficiency of PSII

(Vance et al., 2011; Naveed et al., 2014a,b).

Plant growth promoting bacteria improves the growth of main as well as lateral

roots which enhances the water uptake in plants raised from microbial seed priming.

Additionally, biopriming helps in mediating water transport and partitioning through

symplastic and apoplastic pathways fetched into improved plant growth under abiotic

stress conditions. Plant growth promoting bacteria modulates the plant metabolism such

as; production of indole-acetic acid (IAA), activity of ACC deaminase, production and

accumulation of antioxidant compounds, and nitrogen fixation (Glick, 2005; Dimkpa et

al., 2009; Bashan and de-Bashan, 2010). Moreover, it enhances the accumulation and

production of compatible solutes which helps in osmotic adjustment (Dimkpa et al.,

2009). Plants treated with Azospirillum and Bacillus helps in upregulating the genes

expression for heat shock proteins (HSP17.8) under heat stress conditions (Lee and

Vierling, 2000). Similarly, barley plants treated with Azospirillum gave lowered activity

of CAT and POD under salt stress. It might be attributed to improved growth and

photosynthetic activity that lowered the production of ROS in treated plants as compared

to control (Omar et al., 2009).

30

Seed priming with PGPB can be used to improve the crop performance under

optimum and stressed conditions (Mahmood et al., 2016). Plant growth promoting

bacteria successfully colonize the seeds and plants when employed through seed priming.

Saber et al. (2012) used various bacterial species for seed biopriming including Bacillus

lentus, Azospirillum spp., P. putida, B. subtilis and Pseudomonas fluorescens. Biopriming

with these bacterial spp. improved the growth and yield traits of wheat. Moreover, the

wheat plants produced from bioprimed plants exhibited decreased need for N and P than

plants from untreated seeds. In barley, biopriming with consortium of Azospirillum

lipoferum and Azotobacter chroococcum improved the dry matter production, yield and

harvest index (Mirshekari et al., 2012). Similarly, Sharifi (2012) reported an increase in

CGR, dry matter production, heads per plant, number of grains and grain weight, yield

and seed oil content in safflower.

2.5. Conclusion

Late sowing and abiotic stresses not only limits the crop productivity but also

cause a serious threat to world food security. Late sowing as well as abiotic stresses

decreases crop yield and quality through alteration in various morphological,

physiological and biochemical processes taking place in plant body. Seed priming with

water and inorganic salts such as CaCl2 can be a useful approach and has the potential to

improve barley performance under late sown and abiotic stress conditions. Moreover,

microbes may also play important role in promoting the growth through enhancing seed

germination, total root biomass and nutrient availability under normal and stressful

conditions. Therefore, it might be a useful approach to prime seed with inorganic salts

and microbes to mitigate the effects of abiotic stresses and enhance abiotic stress

tolerance in plants.

31

CHAPTER 3

MATERIALS AND METHODS

Study was conducted during 2014-17 to investigate the influence of seed priming

in improving the performance of barley varieties under late sown and abiotic stress

conditions. A series of experiments were performed in the green house and field

conditions.

3.1. Experiment 1: Potential role of seed priming in improving the resistance against

drought in barley

3.1.1. Experimental site and design

A pot experiment was carried out in the greenhouse of Faculty of Agriculture,

University of Agriculture, Faisalabad during 2014-15 and 2015-16 to investigate potential

of seed priming in improving the resistance against drought stress in barley. The

experiment was carried out by using completely randomized design (CRD) in factorial

arrangement with four replications.

3.1.2. Experimental material

Seed of two barley varieties, Hiaider-93 and Frontier-87, used in this study was

obtained from Ayub Agriculture Research Institute, Faisalabad, Pakistan.

3.1.3. Experimental treatments

Seed of both barley cultivars was subjected to four seed priming treatments viz.

control (dry seed), hydroprimed, osmoprimed with 1.5% solution of CaCl2 and bioprimed

with Enterobacter sp. strain FD17. Seed was soaked for 12 h in aerated 5% (w/v) solution

of microbes and CaCl2 for biopriming and osmopriming, respectively. Seed was soaked in

water for hydropriming; keeping seed and solution ratio of 1:5 (w/v). Aquarium pump

was used providing aeration. The seed was washed with distilled water for 2-3 times after

removing from the respective solution and dried back to its original weight by enforced

air at 27oC ± 2, then stored in refrigerator at 5oC after putting in polythene bags until used.

The crop was sown as per treatments. After stand establishment drought stress viz. 80%

(well-watered), 60% (mild drought) and 40% (severe drought) water-holding capacity

were applied.

3.1.4. Crop husbandry

Two barley cultivars viz. Haider-93 and Frontier-87 were sown manually in the

soil filled earthen pots (45 cm × 30 cm) on November 03, 2014 and November 07, 2015.

32

The soil properties are given in Table 3.1. Fertilizer dose was calculated per weight basis

of soil from recommended dose of NPK. Urea (containing 46% N), diamonium phosphate

(DAP) (containing 46% P2O5 and 18% N), sulphate of potash (SOP) (containing 50%

K2O) were used as sources of fertilizers. All NPK was applied at sowing. Fifteen seeds

per pot were sown, after stand establishment six plants per pot were maintained. Crop was

harvested on April 05, 2015 and April 10, 2016 at maturity, manually threshed and yield

traits were recorded.

3.1.5. Imposition of drought stress

Field capacity of soil used in this experiment was determined by taking three soil

samples (each of 100 g) while filling pots. Samples were placed in oven at 105°C± 5 for

24 h. Afterwards, samples were weighed to determine total moisture content. Amount of

distilled water used in making paste was measured to calculate saturation percentage of

soil samples. Field capacity of soil was calculated according to following formula:

The weight of soil containing pots and moisture content was known at sowing

time; therefore, weight of filled pots having moisture contents equilent to 60, 80 and

100% water holding capacity were calculated and maintained representing as drought

treatment.

3.1.6. Procedures for recording data

Procedures for recording data for different traits during the period of experiment

are given as follows;

3.1.6.1. Stand establishment

The seedlings were counted daily after emergence to determine stand

establishment traits by using the method given in Handbook of Association of Official

Seed Analysts (1990). The data on following stand establishment traits were recorded;

i) Final emergence (%)

The seedlings emerged were counted from each replication on daily basis till

constant value. The emergence percentage of final count was computed as a ratio of the

seedlings emerged to the total seeds sown and expressed in percentage.

ii) Time taken to 50% emergence (days)

33

Time taken for completion of 50% emergence was computed by using formula

given by Coolbear et al. (1984) and revised by Farooq et al. (2005);

Where,

N = Number of emerged seedlings

ni, nj = Accumulative number of the emerged seedlings at each adjacent count at

time ti and tj, while, ni < N/2 < nj

iii) Mean emergence time (days)

The mean emergence time was computed by using the formula given by Ellis and

Robert (1981);

Where,

n = Seedlings emerged on day D

D = Days from initiation of the emergence

iv) Emergence index

Emergence index was determined using the formula of Association of Official

Seed Analyst (1990);

3.1.6.2. Morphological and allometric traits

i) Plant height (cm)

The plant height was measured from three selected plants from all replications.

Plant height was measured using a meter rod from soil surface to tip and averaged.

ii) Leaf area (cm2)

Leaves of one selected plant from all replications were detached and the leaf area

was determined with digital leaf area meter (JVC TK-5310) and averaged.

3.1.6.3. Proteomics

i) Total soluble proteins (mg g-1 FW)

The total soluble proteins content was ascertained from flag leaves at booting

stage as follows;

Total soluble proteins extraction

34

Fresh leaves (0.5 g) were ground by adding extraction buffer having pH 7.2 (1

mL) to extract the total soluble proteins followed by addition of 1 µM cocktail protease

inhibitor. The phosphate buffer saline (10 mM Na2HPO4, 2 mM KH2PO4, 1.37 mM NaCl,

2.7 mM KCl) was used with pH 7.2 adjusted by HCl and volume made upto 1 L. It was

followed by autoclaving (Sambrook and Russell, 2001). Centrifugation of ground leaf

material was carried out at 12000 x g upto 5 min. Then supernatant was poured in the

separate tubes.

Determination of total soluble proteins (mg g-1 FW)

The method of Bradford (1976) was followed to ascertain the total soluble

proteins. Standard curve was prepared by using bovine serum albumin at different

concentrations (10, 20, 30, 40 and 50 µg mL-1) by addition of dye (400 µL) and distilled

water. Spectrophotometer was used to read absorbance of samples and blank at 595 nm.

Total soluble proteins content was ascertained using standard curve.

3.1.6.4. Biochemical traits

i) Chlorophyll contents (mg g -1 FW)

Chlorophyll contents were determined by taking fresh flag leaves (0.5 g) sample

at booting stage. Samples were soaked overnight in of 80% acetone (5 ml). Absornaces

were taken with spectrophotometer. Concentrations of chlorophyll were determined by

following the formulae of Arnon (1949);

Chlorophyll ‘a’ (mg g-1 FW)

Chlorophyll ‘b’ (mg g-1 FW)

ii) Free leaf proline (µmol g-1 FW)

Fresh flag leaves samples were obtained at booting stage and free leaf proline

content was determined according to Bate et al. (1973). Homogenation of samples was

performed in 3% sulfosalcyclic acid (10 mL) followed by filteration. Filterate (1 mL) was

poured in ninhydrin solution (1 mL) (prepared by adding 1.25 g ninhydrin in 20 mL of

6M orthophosphoric acid and acetic acid) and glacial acetic acid (1 mL). Mixture was

incubated upto 1 h at 100°C and cooled in the ice bath. Afterwards, toluene (5 mL) was

added to mixture, vortexed upto 5 min and then removed from the aqueous phase.

35

Absorbance was recorded at 520 nm and toluene was used as blank. Concentration of

proline was calculated as follows;

iii) Leaf glycine betaine (µmol g-1 FW)

Fresh flag leaves samples were taken at booting stage and free leaf glycine betaine

was assayed following Grieve and Grattan (1983). Leaves samples (1 g) were ground in

distilled water (10 mL) and filtered. Afterwards, filtrate (1 mL) was added in 2M HCL (1

mL) and incubated upto 1 h at 4°C. Potassium tri iodide (0.1 mL) was added to the

mixture and incubated upto 1 h at 4°C. In cooled mixture, 1,2-di-dichloroethane (10 mL)

and chilled water (2 mL) were adde and vortexed upto 5 min and absorbance of organic

layer was read at 365 nm. Concentration of the glycine betaine was calculated against

standard curve.

iv) Malondialdehyde (µmol g-1 FW)

Flag leaves samples were taken at booting stage for measuring MDA content

according to Cakmak and Horst (1991). Homogention of leaves samples (1 g) was done

in 0.1% trichloroacetic acid (TCA) solution (3 mL). Centrifugation of the homogenate

was performed upto 15 min at 20000 × g. In supernatant (0.5 mL), 0.5% thiobarbituric

acid (3 mL) made in 20% TCA was poured. Mixiture was heated upto 30 min at 95°C in

water bath and then cooled. The samples were centrifuged upto 10 min at 10,000 × g.

Absorbance of supernatant was observed at 532 and 600 nm. Malondialdehyde content

was determined as follows;

Where,

A = Absorption coefficient valued 155 mmol-1 cm-1

v) Total soluble phenolics (µg g-1 FW)

Extraction method

For determining the total soluble phenolics, the flag leaves samples (0.5 g) were

taken at booting stage, soaked in 80% acetone (5 mL) overnight and filtered. The filtrate

was made upto 10 ml by adding acetone.

Bioassay

Total soluble phenolics content was assayed by using the Folin-Ciocalteu method

of Ainsworth and Gillespie (2007). A 20 µL of sample, calibration solution and blank

36

were taken, and water (1.58 mL) and Folin-Ciocalteu-reagent (100 µL) were added,

mixed and waited upto 30 sec. Then, Na2CO3 solution (300 µL) was poured and kept upto

2 hours at 25oC. Absorbance of the mixture was recorded at 760 nm. Total soluble

phenolics content was determined using the standard curve prepared by gallic acid (25-

250 ppm).

vi) Cell membrane stability (%)

Fresh flag leaves samples were taken at booting stage to determine the cell

membrane stability. Leaves samples were weighed (0.2 g) and equal sized five segments

made, washed and soaked in distilled water (20 mL) upto 12 h. Electrical conductivity of

the solution (EC1) was determined and solution heated in water bath upto 30 min and

cooled at room temperature. Conductivity of the solution was determined again (EC2).

Cell membrane stability was calculated following Blum and Ebercon (1981).

3.1.6.5. Water relation traits

Flag leaves samples were taken at booting stage to determine the plant water

relation attributes.

i) Leaf relative water content (%)

Leaf relative water content was determined following Barrs and Weatherly

(1962). Fresh weight (Wf) of leaves was determined. The samples were soaked in

distilled water upto 4 h period to record saturated weight (Ws). After recording Ws, the

leaves were oven dried at 70oC to detrmine the dry weight (Wd). Leaf relative water

content was calculated as follows;

ii) Leaf water potential (-MPa)

Water potential apparatus was usded to determine leaf water potential according

to Scholander et al. (1964). Compressed gas was applied on leaf sealed in pressure bomb

untill xylem sap appeared at cut surface of leaf. The reading was recorded as leaf water

potential. Sampling was done between 6:00 a.m. to 8:00 a.m. to avoid evaporation.

iii) Leaf osmotic potential (-MPa)

37

Same leaf, utilized for the determination of water potential, was frozen in freezer

at -20°C for one week, thawed and cell sap was extract by pressing leaf with rod. Osmotic

potential wa determined with a vapor pressure osmometer.

iv) Leaf pressure potential (MPa)

Leaf pressure potential was computed as difference between water potential and

osmotic potential.

3.1.6.6. Grain analysis

i) Zinc content (µg g-1 DW)

Concentration of zinc in barley grains was determined according to the method of

Estefan et al. (2013). The digestion was carried out by using the following method:

Digestion

Ground grains (1 g) and di-acid mixture (10 mL) (nitric acid and perchloric acid in

2:1 ratio) were added in digestion tubes. The digestion tubes were heated at 150°C upto 1

h and then at 235°C on block digester untill fumes disappeared and solution became

colorless. Tubes were cooled, few drops of distilled water were added. Volume of

solution was made upto 100 mL with distilled water and filtered. A blank was also

included in batch for digestion.

Zn+2 concentration determination

Standard curve was prepared by running series of standards of Zn (0.2, 0.4, 0.8,

1.0 and 1.2 ppm). The filterate was used to determine zinc concentration by using atomic

absorption spectrophotometer. The Zn concentration was computed as follows;

Where,

V = volume of digest (mL)

W = weight of plant sample (g)

ii) Manganese content (µg g-1 DW)

Method of Estefan et al. (2013) was used to determine the concentration of Mn in

grain samples. Digestion of grains samples was done similarly as for Zn determination.

Standard curves was prepared by running series of standards of Mn (0.2, 0.4, 0.8, 1.0 and

1.2 ppm). TheMn concentration in filterate was determine by using atomic absorption

spectrophotometer. The Mn concentration was determined as follows.

38

Where, V = volume of digest (mL)


iii) Boron content (µg g-1 DW)

Grain B contents were determined by dry ashing (Chapman and Pratt 1961). Dry

ashing of ground grains was done at 550°C for 6 h in furnace. Then extraction form ashed

samples was done with0.36 N H2SO4 (10 mL), filtered and volume was made upto 50 mL

with distilled water. Buffer solution (4 mL) (1.5% EDTA, 12.5% Acetic acid, 25%

ammonium acetate) and solution (4 mL) containg containing 1% ascorbic acid and 0.45%

azomethine-H was added to filterte (2 mL). Color was developed for 30 min. Standard

curve of B (0.5-3.0 ppm) was prepared, absorbance was read at 420 nm with

spectrophotometer and B concentration was determined as follows (Bingham 1982; Ho et

al., 1986; Malekani and Cresser 1998);

Where,

V = volume of digest (mL)


3.1.6.7. Yield and related traits

Parameters on the yield and related traits were recorded by using following

procedures;

i) Number of tillers per pot

At maturity, number of tillers was counted from selected three plants from each

pot.

ii) Number of productive tillers per pot

At maturity, the number of tillers having spike was counted form selected three

plants from each pot.

iii) Spike length (cm)

From each pot, the spikes were collected from selected three plants and spike

length was measured by using a measuring scale and averaged.

iv) Number of spikelet’s per spike

From each pot, the spikes were collected from selected three plants and the

number of spikelet’s on all spikes was counted and averaged.

39

v) Number of grains per spike

At maturity, spikes were collected from selected three plants from each pot.

Grains per spike were counted after threshing spikes manually and then average was

calculated.

vi) 100-grain weight (g)

From each replication grains were collected after threshing the spikes of selected

three plants and 100-grains were counted manually. The weight of 100 grains was

recorded in grams using an electronic balance.

vii) Grain yield (g pot-1)

The spikes of selected three plants from each pot were threshed manually. Grain

weight from each replication was noted by an electric balance in grams.

viii) Biological yield (g pot-1)

The selected three plants were harvested from each pot and total biomass was

noted from all replications using an electric balance in grams.

ix) Harvest index (%)

Harvest index was computed as follows;

3.2. Experiment 2: Potential role of seed priming in improving the salt resistance in

barley


A pot experiment was conducted in greenhouse of Faculty of Agriculture,

University of Agriculture, Faisalabad during 2014-15 and 2015-16 to investigate the

potential of seed priming in improving the resistance against salt stress in barley. The

experiment was carried out by using completely randomized design (CRD) in factorial



Experimental material was same as mentioned in section 3.1.2.

3.2.3. Experimental details

Seed priming treatments and barley cultivars were remained same as in 1st

experiment. After uniformity of stand establishment salinity viz. 50 mM NaCl (control),

100 mM NaCl (mild salt stress) and 150 mM NaCl (severe salt stress) was applied. 40


In both years, crop was sown manually in soil filled earthen pots (45 × 30 cm) on

November 06, 2014 and November 11, 2015. Soil properties are given in Table 3.1.

Fertilizer dose was calculated per weight basis of soil from recommended dose of NPK.

Urea (46% N), DAP (46% P2O5 and 18% N), SOP (50% K2O) were used as fertilizer

sources. Whole quantity of NPK was applied as basal dose. Fifteen seeds were sown in

each pot and after stand establishment six plants per pot were maintained. Crop was

harvested on April 08, 2015 and April 13, 2016 at maturity and was threshed manually to

record yield traits.

3.2.5. Imposition of salinity stress

The original EC of the soil was 1.01 dS m-1. The 5 dS m-1 was used as control for

comparison because of high salt tolearance ability of barley.

Procedure of ECe measurement

To record ECe, 250 g of dry soil sample was taken from the soil that was used for

pots. Soil paste was made by adding distilled water in it and placed for 24 hours. After 24

hours, the water from paste was extracted with the help of extractor. The ECe of water

was measured with ECe meter.

Saturation percentage (%)

To record saturation percentage, 250 g of soil sample was collected in petri dish

and distilled water was added to make pasty mass. After pasty mass, 10 g of soil saturated

paste was taken in china dish and put in oven for 24 hours to get its constant weight. The

saturation percentage was calculated using following formula;

Salinity development

After weighing the soil in one pot, the salinity level was developed artificially by

adding the NaCl salt in the soil. The salt was added according to the weight of the soil.

The soil weight and salt quantity was measured. The NaCl was added in pots, thoroughly

mixed in pots and salinity levels were developed at 50, 100 and 150 mM. To develop

salinity levels, following procedure was adopted. The original ECe of the soil was used

for this study. Whole procedure is written below in mathematical form.

Saturation percentage of soil = 27%

5 dS m-1 = 50 mM41

Original ECe = 1.67 dS m-1

Required ECe = 5 dS m-1

Difference = 3.33 dS m-1

TSS = EC × 10 = 3.33 × 10 = 33.3

ECe = TSS × Eq. wt. × Saturation percentage/100

= 33.3×58.5 × 27.00/100 = 525.97 mg salt/kg of soil

= 5259.7 mg salt/10 kg of soil

= 5.260 g salt/10 kg of soil

= 13.379 g of NaCl / per pot

To develop 5 dS m-1, 13.379 g of NaCl was applied in each pot and soil was well

mixed to develop salinity. Same procedure was used to develop 10 dS m-1 and 15 dS m-1

salinity levels in respective pots.


Procedures for recording the data on various traits during course of

experimentation are given as follows;


Same as described in section 3.1.6.1.

3.2.6.2. Morphological and allometric traits


3.2.6.3. Mineral analysis

Flag leaves samples were taken at booting stage for determining the Na and K

ions.

Digestion

Digestion of ground dry leaves samples was carried out as described for Zn

determination.

Sodium concentration in plants

Sodium content in digested material was determined by using the flame

photometer according to Estefan et al. (2013). Standardization of instrument was done

with Na standard solutions (2, 4, 6, 8, 10, 15 mg L -1). Sodium concentration was

determined using the standard curve.

Potassium estimation

42

Potassium content was assayed with flame photometer according to Estefan et al.

(2013). Concentration of element was determined by using standard curve prepared by K

standard solutions (2, 4, 6, 8, 10, 15 mg L-1);

3.2.6.4. Proteomics



Fresh flag leaves samples were taken from each replication at booting stage and

biochemical attributes were recorded following procedure as described in section 3.1.6.4.

3.2.6.6. Water relation traits

Flag leaves samples were taken at booting stage and data regarding leaf water

relation traits were recorded as described in section 3.1.6.5.

3.2.6.7. Grain analysis

Grain B, Mn and Zn contents were determined according to section 3.1.6.6.


Yield and related traits were recorded by using the procedures given in section

3.1.6.7.


osmotic and salt stresses in barley


To ascertain potential of seed priming in improving resistance against osmotic and

salt stresses in barley, a hydroponics experiment was carried out in green house of the

Faculty of Agriculture, University of Agriculture, Faisalabad, during 2016. The

experiment was conducted by using completely randomized design (CRD) in factorial




3.3.3. Crop husbandry and experimental details


experiment. The untreated and primed seeds of barley varieties were sown in sand filled

polythene bags on November 10, 2015. Afterwards, fifteen days older seedlings were

transplanted in hydroponic solutions and grown in plastic tubs (length × width × height =

45 × 45 × 25 cm3) containing 1/2 strength Hoagland’s nutrient solution. Then, three stress

levels viz. control (no stress), osmotic stress (-0.8 MPa) by using PEG-8000 and ionic 43

stress (-0.8 MPa) by using NaCl were applied. The nutrient solution used for hydroponics

was a modified Hoagland's solution recipe (Hoagland and Snyder, 1993) and contained 5

mM NH4NO3, 0.5 mM KH2PO4, 3.5 mM K2SO4, 0.5 mM MgSO4.7H2O, 1.5 mM

Ca(NO3)2.4H2O, 25 μM H3BO3, 50 μM Fe-EDTA, 2 μM MnSO4.4H2O, 0.5 μM

H2MoO4·2H2O, 2 μM ZnSO4.7H2O, 0.5 μM CuSO4.5H2O dissolved in water. The nutrient

solution was refreshed after every five days and was aerated by aquarium pumps. An

individual plant was considered as a single replicate and plants were harvested thirty days

after transplanting.

3.3.4. Imposition of osmotic and ionic stress in hydroponics

Ionic stress was maintained through NaCl according to the method of Sosa et al.

(2005). Osmotic stress in hydroponics was maintained by using polyethylene glycol with

8000 molecular weight (PEG-8000) according to the following formula of Michel (1983):

Where, C=PEG concentration

T=Temperature

OP= Osmotic potential

After mixing the required quantity of NaCl and PEG-8000 in water the osmotic

potential of solutions were checked in a vapour pressure osmometer 1kg calibrated in mili

osmol (Osmette, Japan), and was added in the hydroponics solution of the respective

treatment.


Following observations were recorded during the course of investigation;

3.3.5.1. Seedling vigor

i) Shoot length of seedling (cm)

At the end of experiment, the shoot length of all seedlings was measured using

measuring scale and expressed in cm. Then average shoot length was calculated.

ii) Root length of seedling (cm)

At the end of experiment, the root length of all seedlings was measured using

measuring scale and expressed in cm. Then average root length was calculated.

iii) Shoot fresh weight (mg)

Shoot fresh weight of all seedlings was weighed with electric weighing balance

after detaching from roots, averaged and expressed in mg.

iv) Root fresh weight (mg)

44

Detached roots of all seedlings were weighed with electric weighing balance,

averaged and expressed in mg.

v) Shoot dry weight (mg)

Shoots of all seedlings were dried in oven at 70 o C, averaged and expressed in

mg.

vi) Root dry weight (mg)

Detached roots of all seedlings were dried in oven at 70 o C, averaged and

expressed in mg.

3.3.5.2. Proteomics

A harvest leaf samples were taken and total soluble proteins were determined by

the same procedure as described in section 3.1.6.3.


Fresh leaf samples were taken from each replication at harvest and biochemical

attributes were recorded following procedure as described in section 3.1.6.4.


Fresh leaf samples were taken from each replication at harvest, and Na+

concentration was determined according to the section 3.2.6.3.


cadmium stress in barley


To investigate the potential of seed priming in improving resistance against Cd

stress in barley, a hydroponics experiment was carried out in greenhouse of Faculty of

Agriculture, University of Agriculture Faisalabad, during 2016. The experiment was

conducted by using the completely randomized design (CRD) in factorial arrangement

with four replications.



3.4.3. Crop husbandry and experimental details


experiment. The untreated and primed seeds of barley varieties were sown in sand filled

polythene bags on November 15, 2015. Afterwards, fifteen days older seedlings were

transplanted in hydroponic solutions and grown in plastic tubs (length × width × height =

45 × 45 × 25 cm3) containing half strength Hoagland’s nutrient solution. Then, three Cd

stress levels viz. control (no stress), moderate stress (8 mg Cd L-1) and severe stress (12 45

mg Cd L-1) were applied. The nutrient solution used for hydroponics was a modified

Hoagland's solution recipe (Hoagland and Snyder, 1993) and contained 5 mM NH4NO3,

0.5 mM KH2PO4, 0.5 mM MgSO4.7H2O, 3.5 mM K2SO4, 1.5 mM Ca(NO3)2.4H2O, 25 μM

H3BO3, 50 μM Fe-EDTA, 2 μM MnSO4.4H2O, 2 μM ZnSO4.7H2O, 0.5 μM

H2MoO4·2H2O, 0.5 μM CuSO4.5H2O dissolved in water. The nutrient solution was

refreshed after every five days and was aerated by aquarium pumps. An individual plant

was considered as a single replicate and plants were harvested thirty days after

transplanting.


Following observations were recorded during the period of experimentation;

3.4.4.1. Seedling vigor

Seed vigor was recorded following the procedure given in section 3.3.5.1.

3.4.4.2. Proteomics

At harvest leaf samples were taken and total soluble proteins were determined by

the same procedure as described in section 3.1.6.3.


Fresh leaf samples were taken from each replication at harvest and biochemical

attributes were recorded following procedure as described in section 3.1.6.4.


i) Tissue cadmium content (μg g−1 DW)

At harvest the leaf samples were collected and concentration of cadmium contents

was determined by following the procedure of Meuwly and Rauser (1992).

Digestion

Digestion of ground dry leaves samples was carried out as described for Zn

determination.

Tissue cadmium content estimation

Cadmium content was determined by atomic absorption spectrophotometer. The

Cd concentration was calculated as follows;

Where, V = volume of digest (mL)


46


terminal heat stress in barley


To evaluate potential of seed priming in improving resistance against terminal

heat stress in barley, a pot experiment was carried out in greenhouse of Texas A&M,

Agrilife Research Center, Beaumont, Texas, USA which is the principal research and

crop production site of Texas A&M University, USA. The experiment was conducted

during 2017. The experiment was laid out in completely randomized design (CRD) in

factorial arrangement with six replications. Soil physico-chemical properties are given in

Table 3.2.


Seed of USA barley cultivar Solum used in this study was obtained from School

of Plant Sciences, The University of Arizona, USA.

3.5.3. Experimental treatments

Seed priming treatments were same as in 1st experiment except biopriming which

was not included in this experiment. The seeds were sown as per treatments. Mean

day/night temperatures in the greenhouse were observed by using standalone

sensor/loggers (HOBOs, Onset Computer Corporation, Bourne, Massachusetts, USA) and

maintained at desired level. At reproductive stage two levels of heat stress viz. control

(25/18°C day/night) and heat stress (35/25°C day/night) were applied. The heats stress

was applied by using the continuously controlled infrared heaters (1100 W, Chromalox,

Ogden, UT, USA).


Seeds of barley cultivar Solum were manually sown in soil filled plastic pots (25

cm × 15 cm) on January 21, 2017. Fertilizer dose was calculated per weight basis of soil

from recommended dose of NPK. Urea (46% N), DAP (46% P2O5 and 18% N), SOP

(50% K2O) were used as fertilizer sources. Whole of the NPK was applied at sowing as

basal dose. Six seeds per pot were sown, after stand establishment four plants per pot

were maintained. Crop was harvested on June 03, 2017 at maturity and was threshed

manually to record yield traits.


47

Procedures for recording data on various traits during period of experimentation

are as follows;


Stand establishment was recorded following the procedures as described in section

3.1.6.1.

3.5.5.2. Morphological traits

Plant height and number of productive tillers per plant were recorded as

mentioned in section 3.1.6.2.

3.5.6.3. Leaf chlorophyll contents

Leaf chlrophyll contents were determined according to the section 3.1.6.4

3.5.5.4. Leaf gas exchange characteristics

Gas-exchange traits like net photosynthesis, stomatal conductance, intercellular

CO2 concentration and transpiration were recorded by using a LI-6400 portable

photosynthesis system (LI-COR Inc., Lincoln, Nebraska, USA), at 7 and 14 days after

heat stress treatment (DAT). During measurements, incident photon flux density was

1500 µmol (photon) m-2 s-1, the leaf temperature 25oC and ambient CO2 concentration 400

µmol mol-1. The measurements were made on penultimate leaf, under bright sunlight

between 10:00 am and 11:00 am. Stomatal limitation (Ls) was determined by using the

formula; (Ls = 1-Ci/Ca). Carboxylation use efficiency (CUE) was determined as ratio

between photosynthesis to intercellular CO2 concentration.

3.5.5.5. Leaf chlorophyll fluorescence attributes

Chlorophyll a fluorescence parameters, the maximum quantum efficiency of PSII

(Fv/Fm), quantum yield of PSII (QY) and electron transport rate (ETR) were evaluated by

quantifying the fluorescence with a pulse modulated fluorometer (OS5p, Opti-Sciences,

Hudson, NH, USA). Minimal fluorescence (Fo), maximal fluorescence (Fm) and the Fv/Fm

were quantified in dark adapted leaves for 30 min. For QY and ETR, the plants were

under a steady state of photosynthesis (the plants were exposed to ambient sunlight for

more than 5 h), which is a prerequisite for the measurement of QY and ETR. The PAR

clip (OS5p PAR Clip, Opti-Sciences, Hudson, NH, USA) provided PAR measurements

when QY and ETR was measured. The range of PAR was 600-700 μmol m -2 s-1 when QY

and ETR was measured.

3.5.5.6. Leaf estimated oxidative stress

Cell membrane stability and MDA content was determined by using the method as

described in section 3.1.6.4.48

3.5.5.7. Total phenolics content (mg g-1 FW)

Total phenolics content was determined by using the method as described in

section 3.1.6.4.


Data on yield and related traits were noted by using procedures as described in

section 3.1.6.7.

3.6. Experiment 6: Influence of seed priming on the productivity of late sown barley


The experiment was conducted in the Agronomic Research Area, University of

Agriculture, Faisalabad, Pakistan during 2014-15 and 2015-16. The experiment was laid

out in randomized complete block design (RCBD) with split-split plot arrangement

having four replications with net plot size of 6 m × 2.7 m. Soil properties are given in

table 3.1.


Same as described in section 3.1.2.

3.6.3. Seedbed preparation

A soaking irrigation was applied a week before barley sowing to keep the

experimental land soft and moist. Seed bed was prepared by cultivating field twice

followed by planking.

3.6.4. Experimental details and crop husbandry

Seed priming treatments and barley varieties were remained same as in 1st

experiment. The crop was sown at two sowing dates viz. November 30 and December 30

during both 2014 and 2015. Soil properties are given in Table 3.1. Fertilizer dose (NPK

@ 50-35-25 kg ha-1) was applied using urea (46% N), DAP (46% P2O5 and 18% N), SOP

(50% K2O) as fertilizer sources. Whole of the NPK was applied as basal dose. Sowing

was done through hand drill and seed rate was 75 kg ha -1, Weeds were controlled

manually throughout the growing season in both years. Crop was harvested on April 01,

2015 and March 25, 2016 for November 31 sowing date, and April 22, 2015 and April 20,

2016 for December 31 sown crop at maturity and was threshed manually to record yield

traits.

3.6.5. Irrigation

49

Irrigation was applied at tillering, booting, anthesis and grain formation stages. In

all 4 irrigations were applied besides soaking irringation.


Procedures for recording the data on various traits during the period of experiment

are given as follows;


Stand establishment was recorded following the procedures as described in section

3.1.6.1.

3.6.6.2. Allometric, phenological and morphological traits

i) Plant height (cm)

The plant height was recorded by randomly selecting and tagging five plants from

each replication. Plant height was measured from soil surface upto tip by using a meter

rod and averaged.

ii) Leaf area index

The leaf area index was computed according to Watson (1952);

iii) Total dry matter (g m-2)

Total dry matter was determined by weighing the oven dried plants take from m -2.

The TDM production was expressed in g m-2.

iv) Crop growth rate (g m-2 d-1)

Crop growth rate was calculated according to Hunt (1978).

Where, W1 and W2 are TDMs at times t1 and t2, respectively

v) Grain filling rate (g spike-1 d-1)

For determination of garain filling rate, five spikes were selected randomly from

each plot with an interval of seven days. The samples were dried in an oven at 70 oC till

constant weigth, grains were manually threshed, weighed with an electric balance and the

grain filling rate was computed by using following formula;

Where, W1 and W2 are dried weights of selected spikes at times t1 and t2, respectively

50

vi) Grain filling duration (days)

Grain filling duration was recorded as time from anthesis to maturity.


The yield and related traits were recorded as follows;

i) Number of productive tillers m-2

Number of productive tillers was counted from the area of one m2 at final harvest.

ii) Spike length (cm)

The spike length of five selected spikes from each plot was measured from the

base of rachis to tip of spike excluding awns and averaged.

iii) Number of spikelet’s per spike

From each replication, five spikes were taken randomly and number of spikelet’s

in each spike was counted and averaged.

iv) Number of grains per spike

At maturity, five spikes were randomly selected from each replication. Number of

grains per spike was counted after threshing spikes manually and averaged.

v) 1000-grain weight (g)

The 1000-grain weigth was determined by counting and weighing the 1000 grains

on an electric balance from each replication and average was calculated.

vi) Grain yield (t ha-1)

Plants were threshed manually. Grain weight from each replication was recorded

by an electric balance in kg and later converted into t ha-1.

vii) Biological yield (t ha-1)

Plants were harvested and total biomass of was recorded from each replication

using an electric balance in kg and later converted into t ha-1.

viii) Harvest index (%)

Harvest index was calculated as follows;


i) Chlorophyll contents (mg g -1 FW)

Chlorophyll a and b contents were determined according to section 3.1.6.4.

3.6.6.5. Grain proximate analysis

i) Grain protein content (%)

For grain crude protein, grains were analyzed using near infrared (NIR)

51

technology (Omega Analyzer G™, Bruins Instruments, Germany). The analysis by this

method is non-destructive, and don’t require reagents or sample preparation (Moroi et al.,

2011). For protein, the barley grain samples (500 g per sample) were collected from each

replication. The weighed samples were inserted into an NIR Omega G Analyzer and

reflectance values obtained from samples were noted.

ii) Grain starch content (%)

Starch was analyzed by using the same method for grain protein content.

3.7. Economic Analysis

Economic analysis was carried out by following procedure of CIMMYT (1988).

The fixed cost of production of barley was computed for the factors which were kept

fixed viz. seed bed preparation, sowing, fertilization, irrigation, weed management etc.

The variable cost incurring on different treatments of seed priming was calculated

separately. The gross income for each treatment was computed based on grain yield

barley on per hectare basis according to prevailing market value. For calculation of net

field benefits total variable cost was subtracted from total benefits of each treatment. The

costs for inputs and output, gross income and benefits were converted into Rs. ha-1. The

BCR was computed according to CIMMYT (1988);

For calculation of net field benefits the variable cost was subtracted from gross

income. Marginal rate of return was computed according to CIMMYT (1988);

3.8. Meteorological data

Meteorological data during study periods are presented in table 3.3.

3.9. Statistical analysis

Data collected were analyzed statistically by employing the Fisher’s analysis of

variance (ANOVA) technique (Steel et al., 1997) with Statistix 8.1 (Analytical software,

Statistix; Tallahassee, FL, USA, 1985-2003) and the least significance difference (LSD)

test was used to compre the treatments’ means at 5% probability level.

52

Table 3.1: Properties of experimental soil (Experiments 1, 2 and 6)

Year 2014-15 2015-16

Characteristics Unit Value Value

Texture Sandy loam

pH - 8.0 7.9

EC dS m-1 1.07 1.11

Exchangeable Na mmolc L-1 9.7 9.4

Total soluble salts (TSS) mmolc L-1 18.2 18.0

Sodium absorption ratio

(SAR)(mmolc L-1)1/2 6.05

6.05

Chloride ion mmolc L-1 9.34 10.0

HCO3 mmolc L-1 6.48 6.69

Ca + Mg mmolc L-1 7.36 7.70

Available nitrogen % 0.06 0.057

Available phosphorus ppm 6.90 6.57

Available potassium ppm 176 180

Organic matter % 0.97 0.93

53

Table 3.2: Properties of experimental soil (Experiment 5)

Characteristics Unit Value

Texture clay loam -

pH - 6.8

EC dS m-1 1.00

Sodium (Na) ppm 171

Sodium Absorption Ratio (SAR) ppm 2.03

CaCO3 % 5

Calcium (Ca) ppm 3083

Magnesium (Mg) ppm 354

Available nitrogen ppm 4.2

Available phosphorus ppm 19.0

Available potassium ppm 121.0

Organic matter % 2.70

54

Table 3.3: Weather data during the growing seasons of barley at experimental site

Month Total rainfall

(mm)

Relative humidity

(%)Temperature (°C)

Sunshine (h)Monthly

maximum

Monthly

minimum

Daily mean

2014-15 2015-16 2014-15 2015-16 2014-15 2015-16 2014-15 2015-16 2014-15 2015-16 2014-15 2015-16

Nov. 10 9 62 62 26 27 12 12 19 20 8 7

Dec. 0 0 75 63 18 22 6 7 12 15 5 7

Jan. 12 13 75 74 17 18 7 8 12 13 5 1

Feb. 21 8 66 58 22 23 11 9 16 16 6 9

Mar. 68 67 64 60 24 27 14 16 19 21 5 7

Apr. 33 6 33 34 21 34 27 20 27 27 9 8

Source: Agro-meteorology Cell, UAF

55

CHAPTER 4

RESULTS AND DISCUSSION

4.1. Influence of seed priming in improving the resistance against drought in barley

4.1.1. Stand establishment

4.1.1.1. Final emergence percentage

Seed priming significantly affected final emergence percentage; the barley

varieties did not differ significantly for final emergence percentage, during both growing

seasons. The interactive effect of varieties and seed priming was non-significant, during

both years (Table 4.1). Seed priming improved final emergence percentage and maximum

improvement was caused by osmopriming followed by biopriming, as compared to

unprimed control (Table 4.2).

4.1.1.2. Time taken to 50% emergence

Time taken to 50% emergence was significantly affected by seed priming; while,

barley varieties did not differ significantly for time taken to 50% emergence, during both

growing seasons. The interaction between varieties and seed priming was non-significant

for time taken to 50% emergence, during both years (Table 4.1). Time taken to 50%

emergence was decreased as compared to unprimed control, during both years. Minimum

time taken to 50% emergence was elapsed by osmopriming followed by biopriming

(Table 4.3).

4.1.1.3. Mean emergence time

Seed priming significantly affected mean emergence time, during both years. The

barley varieties did not differ significantly for mean emergence time, during both growing

seasons. The interaction between varieties and seed priming was non-significant for mean

emergence time, during both seasons (Table 4.4). The mean emergence time was reduced

by seed priming treatments and least mean emergence time was recorded by osmopriming

(Table 4.5).

4.1.1.4. Emergence index

Seed priming significantly affected emergence index, during both growing

seasons. The barley varieties did not differ significantly for emergence index. Similarly,

interaction between varieties and seed priming was non-significant for emergence index,

during both years (Table 4.4). The emergence index was improved by seed priming

56

treatments, as compared to unprimed control. Maximum improvement was caused by

osmopriming

Table 4.1: Analysis of variance for the influence of seed priming on final emergence percentage and time taken to 50% emergence of barley SOV df Mean sum of square

Final emergence percentage Time taken to 50% emergence

2014-15 2015-16 2014-15 2015-16Varieties (V) 1 46.315ns 29.637ns 0.022ns 0.010ns

Priming (T) 3 140.062** 325.904** 0.458* 0.636*

V×T 3 16.656ns 9.879ns 0.121ns 0.018ns

Error 16 25.919 35.184 0.101 0.146Total 23

SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, * = Significant at p≤0.05, ns = Non-significant

Table 4.2: Influence of seed priming on final emergence (%) of barleyTreatments 2014-15 2015-16

H-93 F-87 Mean H-93 F-87 MeanControl 86.67 82.22 84.45 B 82.22 77.78 80.00 BHP 95.56 88.89 92.22 A 88.89 88.89 88.89 AOP 95.55 95.55 95.55 A 97.78 93.33 95.56 ABP 93.33 93.33 93.33 A 95.56 95.55 95.56 AMean 92.78 90.00 91.11 88.89

Seed priming LSD≤0.05 = 6.2310 (2014-15) and 7.2599 (2015-16)

Table 4.3: Influence of seed priming on time taken to 50% emergence (days) of barleyTreatments 2014-15 2015-16

H-93 F-87 Mean H-93 F-87 MeanControl 4.25 4.22 4.24 A 4.97 4.95 4.96 AHP 3.75 3.98 3.87 AB 4.38 4.29 4.34 BOP 3.63 3.64 3.64 B 4.31 4.15 4.23 BBP 3.89 3.44 3.67 B 4.37 4.47 4.42 BMean 3.88 3.82 4.51 4.47

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Seed priming LSD≤0.05 = 0.3889 (2014-15) and 0.4674 (2015-16)

Table 4.4: Analysis of variance for the influence of seed priming on mean emergence time and emergence index of barley SOV df Mean sum of square

Mean emergence time Emergence index2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 0.003ns 0.040ns 0.111ns 0.020ns

Priming (T) 3 0.274** 0.197* 0.591** 0.690**

V×T 3 0.019ns 0.007ns 0.052ns 0.023ns

Error 16 0.049 0.051 0.080 0.058Total 23


57

Table 4.5: Influence of seed priming on mean emergence time (days) of barleyTreatments 2014-15 2015-16

H-93 F-87 Mean H-93 F-87 MeanControl 4.69 4.70 4.70 A 5.17 5.11 5.14 AHP 4.45 4.58 4.52 AB 4.88 4.85 4.87 ABOP 4.14 4.23 4.19 C 4.74 4.69 4.72 BBP 4.46 4.33 4.40 BC 5.10 4.92 5.01 AMean 4.44 4.46 4.97 4.89


Table 4.6: Influence of seed priming on emergence index of barleyTreatments 2014-15 2015-16

H-93 F-87 Mean H-93 F-87 MeanControl 3.01 2.78 2.90 B 2.66 2.50 2.58 CHP 3.49 3.15 3.32 A 3.00 3.04 3.02 BOP 3.67 3.62 3.65 A 3.45 3.29 3.37 ABP 3.38 3.46 3.42 A 3.17 3.23 3.20 ABMean 3.39 3.25 3.07 3.02


58

followed by biopriming (Table 4.6).

4.1.2. Discussion

Seed priming improved the emergence of barley by enhancing the emergence

percentage and decreasing the time for emergence. This may be due to improved

carbohydrates metabolism in germinating seeds by seed priming due to which activity of

hydrolytic enzymes is enhanced and food reserve becomes available for embryo (Farooq

et al. 2009b). It has been observed that seed priming invokes de novo synthesis of α-

amylase enzyme (Lee and Kim, 2000). Moreover, seed priming enhances activities of the

α-amylase, β-amylase, root system dehydrogenase and catalase enzymes under normal

and stressed conditions which leads to improved germination (He et al., 2002). In present

study, osmopriming was most effective in improving emergence which may be due to

Ca2+ used in osmopriming that is involved in regulating the cell wall structure, and cell

membrane integrity and permeability (Hepler, 2005). The improved cell membrane

stability by osmopriming results in decreased leakage and well maintained cell membrane

resulting in better and early germination (Posmyk et al., 2001). Ruan et al. (2002a, b)

reported improved energy of germination and seedling vigour index with concomitant

decrease in mean germination time by osmopriming with CaCl2 in rice. In present study,

improved emergence by biopriming may be due to endophytic bacteria which improves

water absorption in germinating seeds, and produces extracellular enzymes such as

amylase and protease that promote the degradation of proteins, sucrose and lipids leading

to enhanced and earlier germination (Zhu et al., 2017).

4.1.3. Agronomic attributes

4.1.3.1. Plant height

Drought stress and seed priming treatments significantly affected plant height;

barley varieties also differed significantly for plant height, during both growing seasons.

The interaction between varieties and drought stress was significant, during both years

while the interaction between varieties and seed priming was non-significant during

2014-15 but significant during 2015-16. The interaction between drought stress and seed

priming, and three way interaction among varieties, drought stress and seed priming were

significant, during both years (Table 4.7). Plant height was decreased with increase in

severity of drought stress. Taller plants were produced by Frontier-87 than Haider-93.

Seed priming enhanced the plant height of both barley varieties at all levels of drought

stress, as compared to unprimed control. Under moderate drought, during 2014-15

osmopriming of Frontier-87 and during 2015-16 biopriming of Frontier-87 caused 59

maximum increase in plant height. However, under severe drought the greatest increase in

plant height was recorded by biopriming of Frontier-87 during 2014-15 and osmopriming

of Frontier-87 during 2015-16 (Tables 4.8, 4.9).

4.1.3.2. Leaf area

Leaf area was significantly affected by drought stress and seed priming, during

both years. Selected barley varieties also differed significantly for leaf area, during both

growing seasons. The interaction between varieties and seed priming was non-significant,

during both years. The interactions between varieties and drought stress, and drought

stress and seed priming, and three way interaction among varieties, drought stress and

seed priming was significant, during both growing seasons (Table 4.7). There was a

decrease in leaf area with increase in severity of drought stress. Higher leaf area was

exhibited by Frontier-87 than Haider-93. Seed priming ameliorated the deleterious effects

of drought stress by improving the leaf area of both barley varieties at each level of

drought stress, as compared to unprimed control. Under moderate drought, maximum

increase in leaf area was caused by biopriming of Haider-93 during 2014-15 and

osmopriming of Frontier-87 during 2015-16. Under severe drought, the greatest increase

in leaf area was caused by biopriming of Frontier-87 (Tables 4.10, 4.11).

4.1.3.3. Total number of tillers per pot

There was a significant effect of drought stress and seed priming on total number

of tillers per pot, during both years; the tested varieties did not differ significantly for total

number of tillers per pot during 2014-15 while differed significantly growing 2015-16.

The interactions between varieties and drought stress, varieties and seed priming, drought

stress and seed priming were non-significant during 2014-15 while significant during

2015-16. However, the three way interaction among varieties, drought stress and seed

priming was significant, during both years (Table 4.12). The total number of tillers per

pot was decreased with increase in severity of drought stress. Haider-93 produced higher

number of tillers per pot than Frontier-87. Seed priming treatments improved the total

number of tillers per pot of both tested varieties at each level of drought stress, as

compared to unprimed control. Under moderate drought, maximum number of tillers per

pot was produced by biopriming of Haider-93 during 2014-15 and osmopriming of

Haider-93 during 2015-16. However, under severe drought, highest number of tillers was

produced by biopriming of Frontier-87 and Haider-93 during 2014-15 and 2015-16,

respectively (Tables 4.13, 4.14).

60

4.1.3.4. Number of productive tillers per pot

The number of productive tillers per pot was significantly affected by drought

stress and seed priming; the varieties also significantly differed, during both growing

seasons. Likewise, the interactions between varieties and drought stress, varieties and

seed priming, and drought stress and seed priming were non-significant during 2014-15

and significant during 2015-16. The three way interaction among varieties, drought and

seed priming was significant, during both years (Table 4.12). Number of productive tillers

was decreased with increase in drought severity. Haider-93 produced higher number of

productive tillers than Frontier-87. Moreover, seed priming improved the production of

number of productive tillers of both varieties at each level of drought, as compared to

unprimed control. Under moderate drought, maximum number of productive tillers was

produced by biopriming of Haider-93 during 2014-15 and osmopriming of Haider-93

during 2015-16. However, under severe drought, highest number of productive tillers was

produced by biopriming of Frontier-87 and Haider-93 during 2014-15 and 2015-16,


4.1.3.5. Spike length

Drought stress and seed priming significantly affected the spike length; tested

varieties also differed for spike length, during both years. The interaction between

varieties and drought stress was significant during 2014-15 while non-significant during

2015-16. The interaction between varieties and seed priming was non-significant during

2014-15 and significant during 2015-16. Interaction between drought stress and seed

priming as well as three way interaction among varieties, drought stress and seed priming

were significant, during both years (Table 4.17). There was a decrease in spike length

with increase in severity of drought stress. Longer spikes were produced by Haider-93

than Frontier-87. However, spike length of both tested varieties was enhanced by seed

priming treatments under all levels of drought stress, as compared to unprimed control.

Highest spike length was produced by osmopriming and biopriming of Haider-93 under

moderate and severe drought stress, respectively, during both years (Tables 4.18, 4.19).

4.1.3.6. Number of spikelets per spike

Drought stress and seed priming significantly affected the number of spikelets per

spike. The varieties also differed significantly for number of spikelets per spike, during

both years. The interaction between drought stress and seed priming was significant,

during both years. The interaction between varieties and drought stress was significant 61

during 2014-15 but non-significant 2015-16. However, the interaction between varieties

and seed priming, as well as three way interaction among varieties, drought and seed

priming were

62

Table 4.7: Analysis of variance for the influence of seed priming on plant growth of barley under drought stressSOV df Mean sum of square

Plant height Leaf area2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 435.63** 1227.66** 38845.3** 3782.3**

Drought (D) 2 1857.27** 931.17** 375779.1** 316092.0**

Priming (T) 3 348.14** 378.85** 13359.9** 27028.7**

V×D 2 100.52** 144.87** 26840.0** 1637.5**

V×T 3 32.45ns 62.03** 1093.1ns 989.7ns

D×T 6 49.25** 86.41** 1430.8** 6364.5**

V×D×T 6 51.01** 78.17** 4258.6** 2118.3**

Error 72 12.19 15.74 543.5 448.6Total 95

SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, ns = Non-significant

Table 4.8: Influence of seed priming on plant height (cm) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 62.88 d-h 64.66 def 59.24 ghi 63.89 d-g 51.14 l 52.49 klHP 64.17 def 71.58 bc 58.88 hi 62.75 e-h 53.32 jkl 52.70 klOP 67.72 cd 86.43 a 65.26 de 71.16 bc 57.36 ijk 55.84 i-lBP 71.73 bc 73.70 b 60.29 f-i 65.32 de 57.82 ij 60.44 e-i

Varieties × Drought stress × Seed priming LSD≤0.05 = 4.9205

Table 4.9: Influence of seed priming on plant height (cm) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 61.31 fg 67.90 cd 58.10 f-i 67.67 cde 53.00 i 58.51 f-iHP 68.07 cd 68.76 cd 63.38 def 71.02 bc 55.39 hi 56.26 ghiOP 71.78 bc 72.47 bc 61.00 fg 74.86 b 63.65 def 71.26 bcBP 68.25 cd 87.74 a 60.05 fgh 75.14 b 62.08 ef 60.29 fgh


Table 4.10: Influence of seed priming on leaf area (cm2) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 507.14 cd 592.56 b 449.06 fgh 435.26 gh 298.86 m 318.93 lmHP 523.10 cd 597.05 b 419.81 hi 452.00 fgh 330.95 lm 345.94 klOP 516.12 cd 643.39 a 471.96 ef 462.05 efg 394.13 ij 368.92 jkBP 529.91 c 656.27 a 490.56 de 439.35 fgh 336.87 kl 439.53 fgh

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Drought stress × Seed priming LSD≤0.05 = 32.8620

63

Table 4.11: Influence of seed priming on leaf area (cm2) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 506.34 ef 529.58 def 419.71 j 435.20 ij 332.09 m 321.97 mHP 548.50 cd 535.59 cde 459.66 hi 448.68 hij 327.63 m 348.02 lmOP 561.10 c 542.85 cd 501.79 fg 522.27 def 337.48 m 371.41 klBP 595.99 b 647.84 a 476.13 gh 447.53 hij 386.74 kl 452.87 hi


Table 4.12: Analysis of variance for the influence of seed priming on number of total and productive tillers of barley under drought stress SOV df Mean sum of square

Total No. of tillers per pot No. of productive tillers per pot2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 2.042ns 6.253** 2.470** 4.092**

Drought (D) 2 104.073** 162.003** 110.165** 134.984**

Priming (T) 3 37.458** 33.246** 17.634** 18.292**

V×D 2 0.948ns 4.346** 0.276ns 2.016**

V×T 3 0.792ns 1.433** 0.068ns 0.716**

D×T 6 0.531ns 2.850** 0.162ns 1.380**

V×D×T 6 3.323** 3.444** 1.674** 2.189**

Error 72 0.667 0.319 0.255 0.138Total 95

SOV = Source of variation, df = Degree of freedom, ** = significant at p≤0.01, ns = Non-significant

Table 4.13: Influence of seed priming on total number of tillers per pot of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 13.75 def 13.75 def 12.50 gh 11.75 hi 10.25 j 9.75 jHP 15.25 bc 14.00 de 12.75 fgh 13.00 efg 12.00 gh 10.75 ijOP 17.25 a 15.75 b 13.75 def 15.75 b 12.75 fgh 12.25 ghBP 15.75 b 16.00 b 15.50 b 14.25 cd 12.00 gh 13.00 efg


Table 4.14: Influence of seed priming on total number of tillers per pot of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 14.25 ef 13.75 efg 12.75 hi 11.50 jk 9.50 l 9.00 lHP 15.25 cd 15.25 cd 14.50 de 12.50 hi 11.00 k 12.75 hiOP 16.25 b 17.25 a 15.50 bc 13.63 fg 11.00 k 11.50 jkBP 18.00 a 15.75 bc 13.75 efg 13.75 efg 13.00 gh 12.00 ij


64

Table 4.15: Influence of seed priming on number of productive tillers per pot of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 10.73 e 10.54 ef 8.92 hij 8.51 ij 6.98 k 6.84 kHP 11.82 bc 10.99 de 9.14 hi 9.37 gh 8.21 j 7.39 kOP 13.08 a 11.87 bc 9.97 fg 10.76 de 8.81 hij 8.48 ijBP 12.25 b 12.35 b 11.45 cd 9.87 fg 8.35 j 8.88 hij


Table 4.16: Influence of seed priming on number of productive tillers per pot of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 10.79 d 10.29 e 9.05 f 8.03 g 6.65 i 6.47 iHP 11.54 c 11.54 c 10.32 e 8.78 f 7.48 h 8.69 fOP 12.30 b 13.05 a 11.44 c 10.05 e 7.69 gh 7.88 ghBP 13.55 a 11.80 bc 9.82 e 10.04 e 9.05 f 8.11 g


Table 4.17: Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under drought stress SOV df Mean sum of square

Spike length No. of spikelets per spike2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 7.432** 2.895** 21.028** 4.133*

Drought (D) 2 15.130** 17.597** 67.970** 62.527**

Priming (T) 3 2.540** 3.721** 14.858** 7.406**

V×D 2 1.201** 0.127ns 3.042* 0.182ns

V×T 3 0.154ns 0.345* 2.116ns 0.640ns

D×T 6 0.928** 0.456** 3.894** 1.710*

V×D×T 6 0.529** 0.431** 1.576ns 0.820ns

Error 72 0.143 0.092 0.970 0.596Total 95


Table 4.18: Influence of seed priming on spike length (cm) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 7.36 c-g 7.41 c-f 7.10 efg 6.97 fg 6.21 i 5.15 jHP 7.86 bc 7.09 efg 7.13 d-g 6.34 hi 6.37 hi 6.15 iOP 8.60 a 8.24 ab 7.41 c-f 6.88 gh 7.25 d-g 5.87 iBP 7.86 bc 7.52 cde 6.98 fg 7.19 d-g 7.65 cd 6.30 i


65

Table 4.19: Influence of seed priming on spike length (cm) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 7.47 def 6.90 g-j 6.55 jkl 6.47 kl 5.83 no 5.51 oHP 8.05 ab 7.45 def 6.62 i-l 6.57 jkl 5.99 mn 5.95 mnOP 8.37 a 7.56 cde 7.83 bcd 6.56 jkl 6.28 lm 6.29 lmBP 7.92 bc 7.97 abc 7.02 ghi 7.10 fgh 7.30 efg 6.73 h-k


Table 4.20a: Influence of seed priming on number of spikelets per spike of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 14.17 a 13.35 b 11.54 c 13.02 AF-87 13.84 ab 11.79 c 10.63 d 12.09 BMean 14.00 A 12.57 B 11.09 C

Varieties LSD≤0.05 = 0.4008, Drought stress LSD≤0.05 = 0.4909, Varieties × Drought stress LSD≤0.05 = 0.6942

Table 4.20b: Influence of seed priming on number of spikelets per spike of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 12.95 bcd 12.18 def 10.42 g 11.85 CHP 13.17 bc 12.65 cde 10.41 g 12.08 BOP 16.05 a 13.17 bc 11.61 f 13.61 ABP 13.84 b 12.29 c-f 11.92 ef 12.68 BMean 14.00 A 12.57 B 11.09 C

Drought stress LSD≤0.05 = 0.4909, Seed priming LSD≤0.05 = 0.5668, Drought stress × Seed priming LSD≤0.05 = 0.9818

Table 4.21a: Influence of seed priming on number of spikelets per spike of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 14.01 12.73 11.07 12.60 AF-87 13.43 12.34 10.79 12.19 BMean 13.72 A 12.54 B 10.93 C

Varieties LSD≤0.05 = 0.3140, Drought stress LSD≤0.05 = 0.3846

Table 4.21b: Influence of seed priming on number of spikelets per spike of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 12.90 bcd 12.18 de 10.30 f 11.79 BHP 13.43 bc 12.06 e 10.73 f 12.07 BOP 13.60 b 12.83 cd 11.73 e 12.72 ABP 14.93 a 13.07 bc 10.96 f 12.99 AMean 13.72 A 12.54 B 10.93 C

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Drought stress LSD≤0.05 = 0.3846, Seed priming LSD≤0.05 = 0.4441, Drought stress × Seed priming LSD≤0.05 = 0.7692

66

non-significant, during both years (Table 4.17). The drought stress decreased the number

of spikelets with minimum spikelets produced at severe drought, during both years.

Haider-93 produced higher number of spikelets as compared to Frontier-87. Seed priming

improved the number of spikelets per spike as compared to unprimed control and

maximum increase was caused by osmopriming during 2014-15 and biopriming during

2015-16 (Tables 4.20a-4.21b). Under moderate drought, maximum improvement in

number of spikelets was caused by osmopriming during 2014-15 and biopriming during

2015-16. However, under severe drought, biopriming during 2014-15 and osmopriming

during 2015-16 caused maximum increase in number of spikelets per spike (Tables 4.20b,

4.21b).

4.1.3.7. Number of grains per spike

Drought stress and seed priming significantly affected the grains per spike of

barley during; tested barley varieties also differed for grains per spike, during both years.

Likewise, the interaction between varieties and drought strss, varieties and seed priming,

drought stress and seed priming, and three way interaction among varieties, drought stress

and seed priming was significant for grains per spike, during both growing seasons (Table

4.22). Number of grains per spike was decreased with increase in severity of drought

stress. More number of grains per spike were recorded in variety Haider-93 than the

variety Frontier-87. Seed priming treatments ameliorated the effect of drought stress by

improving the number of grains per spike in both varieties, as compared to unprimed

control. Under moderate drought, biopriming of Haider-93 caused maximum increase in

number of grains per spike, during both growing seasons. However, under severe drought,

maximum increase in number of grains per spike was noted in osmopriming of variety

Haider-93, during both seasons (Tables 4.23, 4.24).

4.1.3.8. 100-grain weight

Drought stress and seed priming significantly affected the 100-grain weight of

barley during; tested barley varieties also differed for 100-grain weight, during both

growing seasons. The interactions between varieties and drought stress, and varieties and

seed priming was non-significant during 2014-15 and significant during 2015-16.

However, the interaction between drought stress and seed priming and three way

interaction among varieties, drought stress and seed priming was significant, during both

years (Table 4.22). Grain weight was decreased with increase in severity of drought

stress. Grain weight in variety Haider-93 was higher than the variety Frontier-87. Seed

priming treatments improved the 100-grain weight of both barley varieties at all levels of 67

drought stress, as compared to unprimed control. Under mild drought, biopriming of

Haider-93 had maximum increase in 100-grain weight, during both years. Under severe

drought, the greatest improvement in 100-grain weight was recorded by osmopriming and

biopriming of Haider-93 during 2014-15 and 2015-16, respectively. However, the effect

of osmopriming of Haider-93 was at par with biopriming of Haider-93 under severe

drouhgt during 2015-16 (Tables 4.25, 4.26).

4.1.3.9. Grain yield per pot

There was a significant effect of drought stress and seed priming on grain yield;

likewise, the tested varieties differed significantly for grain yield, during both years. The

interaction between varieties and drought stress was non-significant during 2014-15 while

significant during 2015-16. However, the interactions between varieties and seed priming,

drought stress and seed priming as well as three way interaction among varieties, drought

stress and seed priming was significant, during both growing seasons (Table 4.27). Grain

yield was decreased with increase in severity of drought stress. Haider-93 produced

higher grain yield than Frontier-87. Seed priming treatments improved the grain yield of

both tested varieties at each level of drought stress, as compared to unprimed control.

Under moderate drought, maximum increase in grain yield was occurred by biopriming of

Haider-93, during both years. Under severe drought, osmopriming and biopriming of

Haider-93 caused the greatest improvement in grain yield during 2014-15 and 2015-16,


4.1.3.10. Biological yield

A significant effect of drought stress and seed priming was noticed for biological

yield, during both years; however, the barley varieties differed significantly during 2014-

15 but did not differ significantly during 2015-16. The interactions between varieties and

drought stress, and drought stress and seed priming were significant, during both years.

Whereas, interaction between varieties and seed priming, and three way interaction

among varieties, drought stress and seed priming was non-significant during 2014-15 but

significant during 2015-16 (Table 4.27). Drought stress decreased the biological yield of

both varieties. Haider-93 produced higher biological yield than Frontier-87. Seed priming

improved the biological yield of both varieties, as compared to unprimed control. Under

mild as well as severe drought, greatest improvement in biological yield was noticed by

biopriming of Haider-93 (Tables 4.30a, 4.31).

4.1.3.11. Harvest index

68

Drought stress and seed priming significantly affected the harvest index of barley,

during both seasons; tested barley varieties also differed for harvest index. The interaction

between varieties and drought stress was significant, during both years. However, the

interactions between varieties and seed priming, drought stress and seed priming, and

three way interaction among varieties, drought stress and seed priming was significant

during 2014-15 but non-significant during 2015-16 (Table 4.27). Drought stress

decreased the harvest index of barley with increase in its severity. Haider-93 recorded

higher harvest index than Frontier-87. However, harvest index of both tested barley

varieties was improved by seed priming treatments under all levels of drought stress, as

compared to unprimed control. During 2014-15, the highest harvest index was recorded

by biopriming of Haider-93 and osmopriming of Frontier-87 under moderate and severe

drought, respectively. However, during 2015-16, drought stress caused a linear reduction

in harvest index with increasing stress severity. Variety Haider-93 produced higher

harvest index than Frintiers-87. Across drought stress and varieties, the osmopriming

caused maximum increase in harvest index (Tables 4.32-4.33b).

4.1.4. Discussion

Drought stress decreased growth and development of barley varieties. Drought

stress reduces plant growth by imposing its deleterious effects on mitotic activities and

cell elongation (Anjum et al., 2017b). Similar decrease in growth and development of

chick pea by drought at reproductive growth stage has been reported by Mafakheri et al.

(2010). However, in present study, seed priming treatments improved the growth of

barley plants under each level of drought stress. The improved plant growth by seed

priming under stressed conditions is attributed to early head start by greater early seedling

vigour (Afzal et al., 2006) and by improving the stress tolerance achieved through

improved water relations, osmolytes accumulation and antioxidants defense (Chen and

Arora, 2013; Tabassum et al., 2017). In present study, the improved plant growth by

osmopriming is attributed to improved cell wall structure, cell membrane integrity and

functioning, mitotic activity, and cell turgor and elongation by ca2+ which was used in

osmopriming (Hepler, 2005). Moreover, improved growth by biopriming might be due to

endophytic bacteria which improve the plant growth under normal and stressed conditions

by enhancing the uptake of water and nutrients, and enhanced production of auxin,

gibberellic acid and cytokinins while decreasing the levels of ethylene through production

of ACC deaminase (Santoyo et al., 2016).

69

The grain yield and harvest index of barley varieties was decreased by drought

stress with increase in its severity. However, the variety Haider-93 produced higher grain

yield and harvest index under severe drought which is attributed to higher number of

70

Table 4.22: Analysis of variance for the influence of seed priming on number of grains per spike and 100-grain weight of barley under drought stress SOV df Mean sum of square

No. of grains per spike 100-grain weight2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 66.600** 42.294** 0.190** 0.844**

Drought (D) 2 1479.248** 2018.698** 4.774** 6.549**

Priming (T) 3 100.164** 48.944** 0.947** 0.599**

V×D 2 12.967** 6.206** 0.025ns 0.051**

V×T 3 8.743** 4.698* 0.016ns 0.094**

D×T 6 8.419** 5.378** 0.075* 0.033*

V×D×T 6 6.459** 4.626** 0.077** 0.039**

Error 72 1.129 0.909 0.014 0.010Total 95


Table 4.23: Influence of seed priming on number of grains per spike of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 33.92 de 32.28 fg 28.01 jk 26.73 kl 22.01 n 19.65 pHP 36.27 c 33.58 ef 28.61 ij 28.28 ij 24.07 m 20.37 opOP 35.10 cd 38.24 b 30.89 gh 30.81 gh 25.34 lm 22.42 nBP 40.22 a 39.57 ab 34.19 de 29.72 hi 24.79 m 21.78 no


Table 4.24: Influence of seed priming on number of grains per spike of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 33.63 c 32.37 c 27.84 f 26.45 g 19.85 jk 17.65 lHP 36.28 ab 37.51 a 28.68 ef 27.85 f 20.73 ij 18.80 klOP 37.38 a 37.26 a 29.56 de 30.48 d 22.52 h 19.50 jkBP 36.99 a 35.55 b 32.89 c 28.43 ef 21.34 hi 19.90 jk


Table 4.25: Influence of seed priming on 100-grain weight (g) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 3.22 e 3.30 de 2.90 hi 2.80 ij 2.55 kl 2.50 lHP 3.61 bc 3.18 efg 3.02 fgh 3.17 ef 2.84 ij 2.69 jkOP 3.84 a 3.83 a 3.24 e 3.22 e 3.01 gh 2.68 jkBP 3.63 b 3.58 bc 3.45 cd 3.30 de 2.88 hi 2.85 hij


71

Table 4.26: Influence of seed priming on 100-grain weight (g) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 3.29 ef 3.17 fg 2.93 ij 2.73 k 2.45 lm 2.26 nHP 3.32 e 3.59 bc 3.06 ghi 2.87 jk 2.54 lm 2.40 mOP 3.79 a 3.47 cd 3.17 fg 3.02 hi 2.85 jk 2.56 lBP 3.61 b 3.37 de 3.36 de 3.09 gh 2.86 jk 2.45 lm


Table 4.27: Analysis of variance for the influence of seed priming on grain yield, biological yield and harvest index of barley under drought stressSOV df Mean sum of square

Grain yield Biological yield Harvest index2014-15 2015-16 2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 8.598** 1.503** 28.703** 0.751ns 33.583** 22.234**

Drought (D) 2 280.125** 370.567** 1124.787** 2103.445** 1098.881** 891.370**

Priming (T) 3 20.548** 15.545** 91.122** 64.256** 60.466** 60.160**

V×D 2 0.291ns 1.257** 11.155** 10.276** 14.747** 13.666**

V×T 3 0.604* 1.234** 0.706ns 11.026** 3.944* 1.183ns

D×T 6 1.400** 2.114** 4.516** 10.260** 1.794ns 2.157ns

V×D×T 6 0.544** 0.624** 1.575ns 2.424* 4.251** 1.943ns

Error 72 0.100 0.063 1.006 0.996 0.880 1.906Total 95


Table 4.28: Influence of seed priming on grain yield (g per pot) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 8.17 ef 8.08 ef 5.68 i 5.18 j 3.20 m 2.94 mHP 9.77 c 8.49 de 6.03 i 5.87 i 3.70 l 3.13 mOP 10.41 b 10.22 b 7.97 f 7.28 g 4.35 k 3.92 klBP 11.06 a 10.21 bc 8.62 d 6.82 h 4.11 kl 3.74 l


Table 4.29: Influence of seed priming on grain yield (g per pot) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 7.96 f 7.95 f 5.67 k 5.15 l 2.56 qr 2.25 rHP 9.09 e 10.81 b 6.61 i 6.11 j 2.86 opq 2.67 pqOP 11.17 a 10.81 b 7.29 g 6.97 gh 3.28 mn 3.05 noBP 10.19 c 9.58 d 7.79 f 6.74 hi 3.55 m 2.93 nop


72

Table 4.30a: Influence of seed priming on biological yield (g per pot) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 28.02 a 24.23 b 17.39 d 23.21 AF-87 28.24 a 22.78 c 15.34 e 22.12 BMean 28.13 A 23.50 B 16.36 C


Table 4.30b: Influence of seed priming on biological yield (g per pot) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 25.54 d 20.70 f 15.03 h 20.43 CHP 27.45 c 22.03 e 15.45 h 21.65 BOP 29.24 b 25.46 d 17.82 g 24.17 ABP 30.28 a 25.82 d 17.14 g 24.42 AMean 28.13 A 23.50 B 16.36 C

Drought stress LSD≤0.05 = 0.5001, Seed priming LSD≤0.05 = 0.5775, Drought stress × Seed priming LSD≤0.05 = 1.0002

Table 4.31: Influence of seed priming on biological yield (g per pot) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 23.58 de 24.16 d 20.23 f 19.57 f 10.84 i 9.29 jHP 26.00 c 30.18 a 22.53 e 23.39 de 11.68 hi 10.75 iOP 28.86 ab 29.74 a 22.60 e 23.38 de 12.29 gh 11.54 hiBP 27.88 b 25.97 c 25.65 c 24.15 d 13.22 g 11.12 hi


Table 4.32: Influence of seed priming on harvest index (%) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought

H-93 F-87 H-93 F-87 H-93 F-87Control 31.96 d 31.66 d 26.63 gh 25.79 h 20.15 l 20.70 klHP 35.56 ab 30.96 d 26.84 gh 27.16 fg 22.28 j 21.94 jkOP 36.02 a 34.58 bc 31.07 d 28.88 e 22.80 ij 23.67 iBP 36.71 a 33.56 c 31.38 d 28.20 ef 22.83 ij 22.93 ij


73

Table 4.33a: Influence of seed priming on harvest index (%) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 36.07 a 30.00 b 25.43 d 30.50 AF-87 35.54 a 27.57 c 25.50 d 29.54 BMean 35.80 A 28.79 B 25.46 C


Table 4.33b: Influence of seed priming on harvest index (%) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 33.48 27.23 23.81 28.17 DHP 35.42 27.73 24.80 29.32 COP 37.57 31.04 26.56 31.72 ABP 36.75 29.16 26.68 30.86 BMean 35.80 A 28.79 B 25.46 C

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Drought stress LSD≤0.05 = 0.6880, Seed priming LSD≤0.05 = 0.7944

74

productive tillers, spike length, number of spikelets, number of grain and grain weight

than Frontier-87. Drought stress affects the pollen viability due to decrease in pollen

moisture ultimately causing decrease in grain setting and spikelet fertility (Saragih et al.,

2013). Moreover, the drought stress decreases the photosynthesis and assimilate

translocation thus significantly decreasing the grain weight (Farooq et al., 2009a; Dong et

al., 2017). In present study, the seed priming improved grain yield and harvest index of

both varieties under drought stress. It was observed that seed priming enhanced the spike

length and number of spikelets which produced greater number of grains. Moreover, the

grain weight was improved by seed priming treatments which contributed to improved

grain yield and harvest index. The improved osmolytes accumulation, tissue water status

and better protection of cellular membranes from lipid peroxidation by seed priming

resulted in improved number of grains and grain weight under normal and stressed

conditions (Tabassum et al., 2017).

Improvement in grain yield of barley by osmopriming might be attributed to better

cell membrane stability by Ca2+ which led to improved pollen viability and number of

grains. Moreover, Ca2+ improves the photosynthesis, decreases ROS activity and lipid

peroxidation by enhanced osmolytes and antioxidants activity ultimately improving the

number of grains, grain weight and grain yield under stressed conditions (Dolatabadian et

al., 2013). Likewise, improved grain and biological yield, and harvest index by

biopriming is attributed to improved growth, osmolytes accumulation, and water and

nutrient relations by endophytic bacteria. Endophytic bacteria enhances production of

auxin while decreasing the ethylene accumulation which results in improved chlorophyll,

greater accumulation of osmolytes, and improved water and nutrient relations which is

translated into improved yield and harvest index (Santoyo et al., 2016). Similarly, Naveed

et al. (2014c) reported that endophytic bacterial Burkholderia phytofrmans strain PsJN

improved the photosynthesis, nutrients uptake, water relations, and yield and related traits

of wheat under drought stress.

4.1.5. Chlorophyll contents

4.1.5.1. Chlorophyll a content

The chlorophyll a content was significantly affected by drought stress and seed

priming; barley varieties significantly differed for the chlorophyll a, during both growing

seasons. The interaction between varieties and drought stress was significant, during both

years. However, the interactions between varieties and seed priming, and drought stress

and seed priming were significant during 2014-15 while non-significant during 2015-16. 75

The three way interaction among varieties, drought stress and seed priming was

significant, during both years (Table 4.34). There was a decrease in chlorophyll a with

increase in severity of drought stress. Haider-93 exhibited higher chlorophyll a than

Frontier-87 under well-watered and mild drought conditions while inverse was observed

under severe drought. However, seed priming ameliorated the deleterious effects of

drought stress by improving the chlorophyll a of both varieties at each level of drought

stress, as compared to unprimed control. During 2014-15 biopriming of Haider-93

resulted in greatest improvement in chlorophyll a content under both moderate and severe

drought. However, during 2015-16 maximum increase in chlorophyll a was observed by

osmopriming of Frontier-87 and Haider-93 under moderate and severe drought,

respectively (Figures 4.1a,b).

4.1.5.2. Chlorophyll b content

A significant effect of drought stress and seed priming was observed for

chlorophyll b content; the tested barley varieties also differed significantly for chlorophyll

b, during both growing seasons. The interaction between varieties and drought stress was

significant during 2014-15 but non-significant during 2015-16. Whereas, the interactions

between varieties and seed priming, and drought stress and seed priming as well as three

way interaction among varieties, drought and seed priming was significant, during both

years (Table 4.34). Chlorophyll b was decreased with increasing level of drought stress.

Haider-93 produced higher chlorophyll b content than Frontier-87. However, seed

priming ameliorated the deleterious effects of drought stress by improving the chlorophyll

b of both varieties at each level of drought stress, as compared to unprimed control.

Under moderate drought, highest chlorophyll b content was recorded by biopriming and

osmopriming of Haider-93 during 2014-15 and 2015-16, respectively. However, under

severe drought osmopriming and biopriming of Haider-93 caused the maximum increase

in chlorophyll b during 2014-15 and 2015-16, respectively (Figures 4.1c,d).

4.1.6. Osmolytes accumulation

4.1.6.1. Total soluble phenolics

The total soluble phenolics content was significantly affected by drought stress

and seed priming, during both years. The varieties did not differ significantly during

2014-15 while significantly differed during 2015-16. The interaction between varieties

and drought stress was non-significant during 2014-15 but significant during 2015-16.

However, the interactions between varieties and seed priming, drought stress and seed

priming as well as three way interaction among varieties, drought and seed priming was 76

significant, during both growing seasons (Table 4.35). Total soluble phenolics were

increased with an increase in the severity of drought stress. Haider-93 biosynthesized

more total soluble phenolics than Frontier-87 under control and mild drought while

opposite was observed under severe stress. However, total soluble phenolics contents of

both varieties were further increased by seed priming treatments under all levels of

drought stress, as compared to unprimed control. Under moderate drought, highest

phenolics content was produced by biopriming and osmopriming of Haider-93 during

2014-15 and 2015-16, respectively. However, under severe drought osmopriming and

biopriming of Haider-93 caused the maximum increase in phenolics content during 2014-

15 and 2015-16, respectively (Figures 4.2a,b).

4.1.6.2. Total soluble proteins

Drought stress and seed priming significantly affected the total soluble proteins;

however, the barley varieties did not differ significantly, during both growing seasons.

Similarly, the interaction between varieties and drought stress was non-significant, during

both years. However, the interactions between varieties and seed priming, drought stress

and seed priming, and three way interaction among varieties, drought stress and seed

priming was significant, during both years (Table 4.35). Total soluble proteins were

increased proportionally under drought stress relative to its severity. Haider-93 produced

greater total soluble proteins than Frontier-87. Furthermore, seed priming treatments

further increased the contents of total soluble proteins of both tested varieties under

drought stress, as compared to unprimed control. Under moderate stress, the highest total

soluble proteins content was recorded by osmopriming of Haider-93 and biopriming of

Frontier-87 during 2014-15 and biopriming of Haider-93 during 2015-16. Under severe

drought, hydropriming and osmopriming of Haider-93 exhibited highest total soluble

proteins during 2014-15 and 2015-16, respectively (Figures 4.2c,d).

4.1.6.3. Free proline content

There was a significant effect of drought stress and seed priming on free leaf

proline content, during both years; the barley varieties also differed significantly for free

proline content. The interactions between varieties and drought stress, varieties and seed

priming, drought stress and seed priming, and three way interaction among varieties,

drought stress and seed priming was significant, during both years (Table 4.36). Proline

content was increased with increase in severity of drought stress. Haider-93

biosynthesized more free proline than Frontier-87. Seed priming treatments further

increased the proline contents of both varieties under drought stress, as compared to 77

unprimed control. The greatest increase in free leaf proline content was recorded by

osmopriming of Haider-93 under both moderate

78

Table 4.34: Analysis of variance for the influence of seed priming on chlorophyll contents of barley under drought stress SOV df Mean sum of square

Chlorophyll a Chlorophyll b2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 0.0084** 0.0054** 0.0048** 0.0023*

Drought (D) 2 0.1409** 0.1152** 0.0210** 0.0484**

Priming (T) 3 0.0075** 0.0059** 0.0064** 0.0033**

V×D 2 0.0011* 0.0013* 0.0008** 0.0001ns

V×T 3 0.0024** 0.0002ns 0.0003* 0.0004**

D×T 6 0.0029** 0.0003ns 0.0009** 0.0002**

V×D×T 6 0.0011** 0.0010** 0.0008** 0.0005**

Error 72 0.0002 0.0002 0.0001 0.0001Total 95

Table 4.35: Analysis of variance for the influence of seed priming on total soluble proteins and total soluble phenolics contents of barley under drought stress SOV df Mean sum of square

Total soluble phenolics Total soluble proteins2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 238.7ns 1053.1** 0.0003ns 0.0023ns

Drought (D) 2 52503.9** 60190.5** 0.9519** 0.9148**

Priming (T) 3 23811.9** 11385.4** 0.0089** 0.0176**

V×D 2 119.9ns 680.6* 0.0002ns 0.0015ns

V×T 3 1421.8* 815.3** 0.0032** 0.0064*

D×T 6 3176.1** 4090.7** 0.0051** 0.0049**

V×D×T 6 2690.6** 2879.5** 0.0079** 0.0073**

Error 72 66.6 83.5 0.0005 0.0007Total 95


79

Chl

orop

hyll

a co

nten

t (m

g g-1

FW

)C

hlor

ophy

ll b

cont

ent (

mg

g-1 F

W)

80

Tot

al so

lubl

e ph

enol

ics (

µg g

-1 F

W)

Tot

al so

lubl

e pr

otei

ns (m

g g-1

FW)

81

and severe drought, during both years (Figures 4.3a,b).

4.1.6.4. Glycine betaine content

The drought stress and seed priming significantly affected the leaf glycine betaine

content during bth years; however, the tested barley varieties differed significantly during

2014-15 but did not differ significantly during 2015-16. The interaction between drought

stress and seed priming was non-significant during 2014-15 but significant during 2015-

16. Whereas, the interactions between varieties and drought stress, varieties and seed

priming, and three way interaction among varieties, drought stress and seed priming was

significant, during both years (Table 4.36). An increase in glycine betaine content was

noticed with increase in drought stress levels. Moreover, Haider-93 exhibited higher

glycine betaine content than Frontier-87. However, glycine betaine of both varieties was

further increased by seed priming treatments under all levels of drought stress, as

compared to unprimed control. During 2014-15, maximum increase in glycine betaine

was consequenced by biopriming of Haider-93 under both moderate and severe drought.

Whereas, during 2015-16, highest glycine betaine content was noticed by osmopriming of

Frontier-87 under both moderate and severe drought stress (Figures 4.3c,d).

4.1.7. Lipid peroxidation

4.1.7.1. Malondialdehyde content

Malondialdehyde content was significantly affected by drought stress and seed

priming, during both growing seasons; the tested barley varieties also significantly

differed for MDA content. The interaction between varieties and drought stress was

significant, during both years. However, the interactions between varieties and seed

priming, and drought stress and seed priming were significant during 2014-15 but non-

significant during 2015-16. The three way interaction among varieties, drought and seed

priming was significant, during both years (Table 4.37). Malondialdehyde accumulation

was increased with increase in severity of drought stress. Haider-93 accumulated less

MDA than Frontier-87. However, seed priming treatments caused a reduction in the

MDA accumulation in both tested varieties under all level of drought stress, as compared

to unprimed control. Minimum MDA content occurred by osmopriming and biopriming

of Frontriers-87 under moderate and severe drought, respectively, during 2014-15, while,

during 2015-16 biopriming and osmopriming of Haider-93 caused maximum decrease in

MDA under moderate and severe drought, respectively (Figures 4.4a,b).

82

4.1.7.2. Cell membrane stability

Cell membrane stability was significantly affected by drought stress and seed

priming; while barley varieties also differed significantly for cell membrane stability,

during both growing seasons. The interaction between varieties and seed priming was

non-significant during 2014-15 but significant during 2015-16. However, the interactions

between varieties and drought stress, drought stress and seed priming as well as three way


growing seasons (Table 4.37). Cell membrane stability was decreased with increase in

severity of drought stress. Haider-93 exhibited better cell membrane stability than

Frontier-87. However, seed priming ameliorated the deleterious effects of drought stress

by improving the cell membrane stability of both barley varieties at each level of drought

stress, as compared to unprimed control. Under moderate drought, greatest improvement

in cell membrane stability was noticed by biopriming of Haider-93, during both years.

Under severe drought, osmopriming of Haider-93 exhibited greatest improvement in cell

membrane stability, during both years. However, hydropriming of Frontier-87 produced

similar results for cell membrane stability during 2015-16 (Figures 4.4c,d).

4.1.8. Discussion

Drought stress impaired the chlorophyll synthesis and cell membrane stability

while increased the accumulation of osmolytes and MDA contents in both barley varieties

with increase in its severity. Drought stress hampers the growth and development of

plants by imposing deleterious effects on normal functioning of the photosynthetic

machinery, enzyme activities and oxidative burst by aggravated ROS activity (Xu and

Zhou, 2006). Nonetheless, plants turn on physiological and metabolic mechanisms which

assist in the maintenance of tissue water status and prevent injuries of oxidative stress

(Ahmadi et al., 2010). Under stressed conditions, plants tend to increase the biosynthesis

and accumulation of osmolytes that help in maintaining the tissue water status, and

protect cellular organelles and organic molecules from ROS activity by acting as physical

barriers (Kumar et al., 2012). Plants accumulate various osmolytes viz. free proline,

glycine betaine, soluble proteins and sugars, sugar alcohols, free amino acids, phenolics

etc. in large amounts under drought stress (Farooq et al., 2009a). In present study,

accumulation of osmolytes was increased in barley varieties which assisted in

maintaining the tissue water status.

In present study, better maintenance of chlorophyll and cell membrane stability by

greater accumulation of osmolytes and decreased lipid peroxidation in Haider-93 under 83

severe drought was associated with its greater stress tolerance ability. Kerepesi and

Galiba

84

Table 4.36: Analysis of variance for the influence of seed priming on free proline and glycine betaine contents of barley under drought stress SOV df Mean sum of square

Free proline content Glycine betaine content2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 0.0611** 0.0852** 0.0150** 0.0001ns

Drought (D) 2 0.2737** 0.1335** 0.3492** 0.3279**

Priming (T) 3 0.0364** 0.0187** 0.0531** 0.0224**

V×D 2 0.0127** 0.0060** 0.0027* 0.0072**

V×T 3 0.0026* 0.0032* 0.0149** 0.0083**

D×T 6 0.0037** 0.0043** 0.0016ns 0.0053*

V×D×T 6 0.0042** 0.0051** 0.0051** 0.0028*

Error 72 0.0008 0.0006 0.0008 0.0003Total 95

Table 4.37: Analysis of variance for the influence of seed priming on malondialdehyde and cell membrane stability of barley under drought stressSOV df Mean sum of square

Malondialdehyde Cell membrane stability2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 38.44** 403.39** 563.40** 482.99**

Drought (D) 2 2681.88** 4674.29** 6270.79** 4312.61**

Priming (T) 3 184.76** 72.42** 951.41** 359.60**

V×D 2 103.97** 87.01** 156.39** 249.68**

V×T 3 118.72** 4.38ns 5.84ns 35.62*

D×T 6 26.97* 12.46ns 57.16** 46.12**

V×D×T 6 43.23** 57.19** 72.42** 42.77**

Error 72 4.75 5.82 6.29 8.01Total 95


85

Free

pro

line

cont

ent (

µmol

g-1

FW

)G

lyci

ne b

etai

ne c

onte

nt (µ

mol

g-1

FW

)

86

Mal

ondi

alde

hyde

con

tent

(µm

ol g

-1 F

W)

Cel

l mem

bran

e st

abili

ty (%

)

87

(2000) reported that wheat seedlings exposed to drought stress showed more sucrose in

tolerant varieties as compared to sensitive ones. Similarly, Anjum et al. (2017c) reported

that tolerant varieties of maize accumulated more total soluble phenolics, proteins,

carbohydrates, free proline and glycine betaine, and exhibited decreased ROS activity and

lipid peroxidation than sensitive varieties.

Seed priming improved the leaf chlorophyll contents, cell membrane stability and

osmolytes accumulation while decreased the MDA accumulation in both barley varieties.

The higher chlorophyll contents in response to seed priming is attributed to better

protection of cellular membranes as indicated by well-maintained cell membrane stability

in response to seed priming (Song et al., 2017). The improved cell membrane stability in

turn is attributed to enhanced accumulation of osmolytes and decreased lipid peroxidation

(Tabassum et al., 2017). It is considered that seed priming induces stress itself because of

loss in desiccation tolerance followed by given desiccation and osmotic stress in case of

osmopriming that triggers the gene expression for osmolytes and heat shock proteins by

accumulation of transcription factors (Kibinza et al., 2011; Chen et al., 2012). The early

stress caused by seed priming induces cross tolerance in plants to subsequent stresses

through rapid expression of genes for osmolytes (Chen and Arora, 2013). Moreover, in

present study, greater accumulation of osmolytes by osmopriming might be due to the

role of Ca2+ as secondary messenger that enhanced the gene expression for osmolytes

(White and Broadley, 2003).

In current study, biopriming with endophytic bacteria ameliorated the damaging

effects of drought by substantially improving the accumulation of osmolytes and

decreasing the lipid peroxidation in both barley varieties under severe drought stress. This

might be due to endophytic bacteria which produces osmolytes in response to abiotic

stresses that act synergistically with plant produced osmolytes to induce stress tolerance

(Dimkpa et al., 2009). Moreover, endophytic plant growth promoting bacteria place the

metabolism of plants in primed state that enable greater and rapid accumulation of

transcription factors and metabolites for osmolytes and stress related gene expression

(Theocharis et al., 2012; Miotto-Vilanova et al., 2016). The enhanced accumulation of

osmolytes by endophytic bacteria results in decreased lipid peroxidation and improved

cell membrane stability (Theocharis et al., 2012).

88

4.1.9. Water relations

4.1.9.1. Leaf relative water content

Drought stress and seed priming significantly affected the leaf relative water

content; barley varieties also differed significantly, during both growing seasons.

Whereas, the interactions between varieties and seed priming as well as varieties and

drought stress were significant during 2014-15 but non-significant during 2015-16.

However, interaction between drought stress and seed priming, and three way interaction

among varieties, drought stress and seed priming was significant, during both years

(Table 4.38). Drought stress decreased leaf relative water content of barley with increase

in its severity. Haider-93 showed higher leaf relative water content than Frontier-87. Seed

priming treatments improved the leaf relative water content of both varieties under each

level of drought stress, as compared to unprimed control. Highest leaf relative water

content was observed by osmopriming and biopriming of Frontier-87 under moderate

drought during 2014-15 and 2015-16 respectively. However, under severe drought,

osmopriming of Haider-93 resulted in highest leaf relative water content, during both

growing seasons (Figures 4.5a,b).

4.1.9.2. Leaf water potential

Leaf water potential was significantly affected by drought and seed priming; the

varieties also differed significantly, during both years. The interaction between varieties

and seed priming was non-significant, during both growing seasons. However, the

interactions between varieties and drought stress, and drought stress and seed priming as

well as three way interaction among varieties, drought stress and seed priming was

significant, during both growing seasons (Table 4.38). Leaf water potential of barley was

decreased with increase in severity of drought stress. Haider-93 maintained higher leaf

water potential than Frontier-87. However, seed priming treatments improved the stress

tolerance by improving the leaf water potential of both varieties under each level of

drought stress, as compared to unprimed control. Under moderate drought, maximum

increase in leaf water potential was noticed by osmopriming of Haider-93, during both

years. Under severe drought, osmopriming and biopriming of Haider-93 led to maximum

improvement in leaf water potential during 2014-15 and 2015-16, respectively (Figures

4.5c,d).

4.1.9.3. Leaf osmotic potential

Drought stress and seed priming significantly affected leaf osmotic potential of

barley; the varieties also significantly differed, during both years. Moreover, the 89

interactions between varieties and drought stress, varieties and seed priming, drought

stress and seed priming as well as three way interaction among varieties, drought stress

and seed priming was significant, during both growing seasons (Table 4.39). Drought

stress decreased the leaf osmotic potential of barley with increase in its severity. Haider-

93 recorded higher leaf osmotic potential than Frontier-87. However, seed priming

treatments improved the stress tolerance by improving the leaf osmotic potential of both

tested varieties under each level of drought stress, as compared to unprimed control. The

greatest improvement in leaf osmotic potential was caused by biopriming and

osmopriming of Haider-93 under moderate and severe drought, respectively, during both

years (Figures 4.6a,b).

4.1.9.4. Leaf pressure potential

The leaf pressure potential was significantly affected by drought stress and seed

priming, during both growing seasons; the barley varieties also differed significantly. The

interactions between varieties and drought stress, and drought stress and seed priming

was non-significant during 2014-15 but significant during 2015-16; while, the interaction

between varieties and seed priming was non-significant, during both years. However, the


growing seasons (Table 4.39). Drought stress decreased leaf pressure potential

proportionally with increase in its severity. Haider-93 maintained higher leaf pressure

potential than Frontier-87. However, leaf pressure potential of both barley varieties was

improved by seed priming treatments under all levels of drought stress, as compared to

unprimed control. The maximum improvement in leaf pressure potential was caused by

biopriming and osmopriming of Haider-93 under moderate and severe drought,

respectively, during both years (Figures 4.6c,d).

4.1.10. Discussion

Drought stress disturbed the water relations of barley varieties and the effect of

drought was increased with increase in its severity. However, Haider-93 better maintained

the water relations under severe drought stress and this is attributed to greater

accumulation of osmolytes. Plants tend to increase the osmolytes accumulation in

response to drought stress to maintain tissue water status through osmotic adjustment

(Farooq et al., 2009a). In present study, seed priming improved the water relations in both

varieties. Improved water relations by seed priming are attributed to osmotic adjustment

through enhanced accumulation of osmolytes and improved root growth. Drought tolerant

plants increase the dry matter partitioning to roots under drought stress to increase the 90

root growth and improve the water uptake from soil (Kavar et al., 2007; Farooq et al.,

2009a). In this study, in osmoprimed plants, aside from osmolytes accumulation the Ca2+

also serves as osmoticum

91

Table 4.38: Analysis of variance for the influence of seed priming on leaf relative water content and leaf water potential of barley under drought stressSOV df Mean sum of square

Leaf relative water content Leaf water potential2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 30.30* 114.23** 11.579** 0.635*

Drought (D) 2 9908.02** 11805.58** 63.066** 89.181**

Priming (T) 3 484.14** 130.67** 1.650** 1.819**

V×D 2 37.82** 12.10ns 1.221** 3.045**

V×T 3 44.53** 17.62ns 0.147ns 0.179ns

D×T 6 51.95** 32.11** 0.304* 0.237*

V×D×T 6 31.22* 40.48** 0.910** 1.018**

Error 72 7.24 7.66 0.130 0.093Total 95

Table 4.39: Analysis of variance for the influence of seed priming on leaf osmotic potential and leaf pressure potential of barley under drought stressSOV df Mean sum of square

Leaf osmotic potential Leaf pressure potential2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 18.842** 14.338** 0.866* 8.912**

Drought (D) 2 158.830** 117.908** 23.528** 3.589**

Priming (T) 3 8.349** 5.652** 2.825** 1.088**

V×D 2 1.752** 1.089** 0.268ns 0.720**

V×T 3 0.497* 0.455* 0.258ns 0.069ns

D×T 6 0.786** 0.799** 0.217ns 0.237**

V×D×T 6 0.917** 0.753** 0.990** 0.645**

Error 72 0.142 0.034 0.182 0.063Total 95


92

Lea

f rel

ativ

e w

ater

con

tent

(%)

Lea

f wat

er p

oten

tial (

-MPa

)

93

Lea

f osm

otic

pot

entia

l (-M

Pa)

Lea

f pre

ssur

e po

tent

ial (

MPa

)

94

that might also have added its beneficial role in osmotic adjustment (White and Broadley,

2003). In current study, the bioprimed pants improved the water relation traits. The

endophytic bacteria in biopriming, improves the root growth of plants by enhanced

production of auxin while decreasing the ethylene production which results in water

uptake from deeper layers of soil (Santoyo et al., 2016). The inoculation of auxin

producing bacteria improves the root growth and helps to better maintain the water

relations under drought stress by enhanced uptake of water from soil (Vurukonda et al.,

2016). German et al. (2000) reported that inoculation with Azospirillum brasilense Cd

enhanced the specific root length and area, and root projection area as compared to

control in common bean (Phaseolus vulgaris L.) under drought conditions.

4.1.11. Grain nutrient contents

4.1.11.1. Grain zinc content

The grain Zn content was significantly affected by drought stress and seed

priming treatments; barley varieties also differed significantly, during both growing

seasons. The interaction between varieties and drought stress was significant during 2014-

15 but non-significant during 2015-16. Moreover, the interactions between varieties and

seed priming, drought stress and seed priming as well as three way interaction between

varieties, drought stress and seed priming was non-significant, during both years (Table

4.40). The drought stress caused reduction in grain Zn content and with greatest decrease

occurring at severe drought, as compared to control, during both years. Under mild as

well as severe drought the variety Haider-93 exhibited higher grain Zn content than

Frontier-87, during both growing seasons (Tables 4.41a, 4.42a). Across drought and

varieties the biopriming improved the grain Zn content, as compared to unprimed control,

during both years (Tables 4.41b, 4.42b).

4.1.11.2. Grain manganese content

Drought stress and seed priming significantly affected grain Mn content, during

both years. The varieties also significantly differed for grain Mn content. Grain Mn

content was significantly affected by interactive effect of varieties and drought stress,

during both years. However, the interactions between varieties and seed priming, drought

stress and seed priming, and three way interaction between varieties, drought stress and

seed priming was non-significant, during both growing seasons (Table 4.40). The drought

stress caused decrease in grain Mn content and least grain Mn content was recorded at

severe drought, as compared to control, during both years. Under mild as well as severe

drought higher grain Mn content was recorded by variety Haider-93 than Frontier-87 95

(Tables 4.43a, 4.44a). Across drought and varieties the biopriming improved the grain Mn

contents, as compared to unprimed control, during both years (Tables 4.43b, 4.44b).

4.1.11.3. Grain boron content

Grain B content was significantly affected by drought stress and seed priming

treatments; the tested varieties also differed significantly, during both growing seasons.

The interaction between varieties and drought stress was significant, during both growing

seasons. However, the interactions between varieties and seed priming, drought stress and

seed priming as well as three way interaction between varieties, drought stress and seed

priming was non-significant, during both years (Table 4.40). Grain B content was

decreased by drought stress as compared to control with maximum decrease occurring at

severe drought. Under mild drought, higher grain B content was recorded by variety

Haider-93, during both growing seasons. Under severe drought higher grain B content

was exhibited by Haider-93 during 2014-15 and by Frontier-87 during 2015-16 (Tables

4.45a, 4.46a). Across drought and varieties the biopriming improved the grain B contents,

as compared to unprimed control, during both growing seasons (Tables 4.45b, 4.46b).

4.1.12. Discussion

The grain nutrient contents were significantly decreased by drought stress in both

varieties. However, the Haider-93 exhibited more grain Zn, Mn and B contents under

drought stress which is attributed to better water relations and enhanced stress tolerance.

Decreased soil moisture causes a reduction in nutrient uptake due to decreased mobility

of nutrients which results in decreased tissue nutrient concentrations (Fahad et al., 2017).

Drought stress negatively affects the nutrient uptake and accumulation because of

decreased translocation by disturbed water relations and decreased assimilation of

nutrients due to decreased enzyme activity (Farooq et al., 2009a). However, in present

study the biopriming significantly improved the grain Zn, Mn and B contents of barley.

The plant growth promoting endophytic bacteria improves the nutrient uptake in plants by

solubilizing the nutrients in soil by production of organic acids, extra cellular enzymes

and siderophores, and by improving the root growth through increased production of

auxins, cytokinins and gibberellic acid while decreased synthesis of ethylene (Miliute et

al., 2015; Vurukonda et al., 2016). Moreover, increased translocation of nutrients is

essential for accumulation in grains. Thus improved water relations of barley in present

study seems the reason of improved grain Zn, Mn and B contents. Rana et al. (2012)

reported a significant increase in Zn, Mn, Cu and Fe uptake and accumulation in grains of

wheat by inoculation with Bacillus sp., Providencia sp. and Brevundimonas sp.96

Table 4.40: Analysis of variance for the influence of seed priming on grain mineral contents of barley under drought stressSOV df Mean sum of square

Seed zinc content Seed manganese content

Seed boron content

2014-15 2015-16 2014-15 2015-16 2014-15 2015-16Varieties (V) 1 161.02** 57.12** 921.38** 908.97** 0.285** 0.096**

Drought (D) 2 513.65** 761.17** 6252.31** 8299.25** 2.018** 2.440**

Priming (T) 3 66.98** 37.37** 611.42** 764.31** 0.238** 0.156**

V×D 2 24.57** 0.67ns 121.96* 186.66** 0.055** 0.113**

V×T 3 3.30ns 2.40ns 23.96ns 32.74ns 0.002ns 0.005ns

D×T 6 7.09ns 4.54ns 48.78ns 33.90ns 0.008ns 0.009ns

V×D×T 6 3.56ns 1.21ns 57.01ns 36.02ns 0.006ns 0.007ns

Error 72 3.61 3.83 29.78 23.35 0.006 0.005Total 95


Table 4.41a: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 41.28 a 37.31 bc 33.97 d 37.52 AF-87 38.34 b 36.62 c 29.83 e 34.93 BMean 39.81 A 36.96 B 31.90 C


Table 4.41b: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 39.31 35.65 30.76 35.24 CHP 39.88 37.86 32.77 36.84 BOP 36.97 35.64 31.03 34.55 CBP 43.08 38.70 33.05 38.28 AMean 39.81 A 36.96 B 31.90 C

Drought stress LSD≤0.05 = 0.9465, Seed priming LSD≤0.05 = 1.0930

Table 4.42a: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 42.63 a 38.22 c 32.65 e 37.83 AF-87 40.76 b 36.83 d 31.29 e 36.29 BMean 41.70 A 37.52 B 31.97 C

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties LSD≤0.05 = 0.7961, Drought stress LSD≤0.05 = 0.9751, Varieties × Drought stress LSD≤0.05 = 1.3790

97

Table 4.42b: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 40.57 36.30 30.96 35.94 BHP 41.72 37.85 30.99 36.86 BOP 40.63 36.52 32.69 36.61 BBP 43.86 39.41 33.26 38.84 AMean 41.70 A 37.52 B 31.97 C


Table 4.43a: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 122.44 a 117.86 b 95.27 d 111.85 AF-87 118.52 b 107.15 c 91.30 e 105.66 BMean 120.48 A 112.50 B 93.29 C


Table 4.43b: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 117.69 108.94 90.11 105.58 CHP 119.43 113.31 96.26 109.67 BOP 113.98 109.13 89.73 104.28 CBP 130.81 118.64 97.05 115.50 AMean 120.48 A 112.50 B 93.29 C


Table 4.44a: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 123.41 a 115.19 b 94.98 c 111.19 AF-87 116.31 b 114.27 b 84.54 d 105.04 BMean 119.86 A 114.73 B 89.76 C


Table 4.44b: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 116.63 110.65 86.68 104.65 CHP 121.30 117.03 91.32 109.88 BOP 111.66 110.30 86.07 102.68 CBP 129.84 120.94 94.95 115.25 AMean 119.86 A 114.73 B 89.76 C


98

Table 4.45a: Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanH-93 1.86 a 1.81 b 1.37 d 1.68 AF-87 1.79 b 1.60 c 1.32 e 1.57 BMean 1.83 A 1.70 B 1.34 C


Table 4.45b: Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2014-15)Treatments Well-watered Moderate drought Severe drought MeanControl 1.79 1.65 1.31 1.58 CHP 1.82 1.77 1.40 1.66 BOP 1.72 1.59 1.23 1.51 DBP 1.99 1.80 1.44 1.74 AMean 1.83 A 1.70 B 1.34 C


Table 4.46a: Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanH-93 1.87 a 1.75 b 1.30 d 1.64 AF-87 1.85 a 1.56 c 1.33 d 1.58 BMean 1.86 A 1.65 B 1.31 C


Table 4.46b: Influence of seed priming on grain boron content (µg g-1 DW) of barley under drought stress (2015-16)Treatments Well-watered Moderate drought Severe drought MeanControl 1.81 1.59 1.27 1.56 CHP 1.85 1.65 1.37 1.62 BOP 1.77 1.62 1.22 1.54 CBP 2.00 1.76 1.39 1.72 AMean 1.86 A 1.65 B 1.31 C


99

4.2. Influence of seed priming in improving the salt resistance in barley4.2.1. Stand establishment

4.2.1.1. Final emergence percentage

Final emergence percentage was significantly affected by seed priming

treatments; however, tested barley varieties did not differ significantly for final

emergence percentage, during both growing seasons. Likewise, the interactive effect of

variety and seed priming was non-significant, during both years (Table 4.47). Final

emergence percentage was improved by seed priming as compared to unprimed control

with highest emergence percentage caused by osmopriming and it was followed by

biopriming, during both years (Table 4.48).


Seed priming significantly affected the time taken to 50% emergence, during both

growing seasons. However, barley varieties did not differ significantly for time taken to

50% emergence, during both years. The interactive effect of varieties and seed priming

was also non-significant for time taken to 50% emergence, during both years (Table

4.47). Seed priming decreased the time taken to 50% emergence as compared to

unprimed control and the order of decrease was osmopriming < biopriming <

hydropriming < control (Table 4.49).


Seed priming treatments significantly affected the mean emergence time; the

barley varieties did not differ significantly for mean emergence time, during both growing

seasons. The interactive effect of varieties and seed priming was also non-significant for

mean emergence time, during both growing seasons (Table 4.50). The mean emergence

time was reduced by seed priming treatments as compared to unprimed control. The order

of decrease in mean emergence time was osmopriming < biopriming < hydropriming <

control during 2014-15, while osmopriming < hydropriming < biopriming < control

during 2015-16 (Table 4.51).


Emergence index was significantly affected by seed priming treatments, during

both growing seasons. However, tested barley varieties did not differ significantly for

emergence index, during both years. Likewise, the interaction between variety and seed

priming was non-significant for emergence index, during both years (Table 4.50). The

emergence index was enhanced by seed priming as compared to unprimed control.

100

Maximum improvement was caused by osmopriming followed by biopriming, during

both

101

Table 4.47: Analysis of variance for the influence of seed priming on final emergence percentage and time taken to 50% emergence of barley SOV df Mean sum of square

Final emergence percentage Time taken to 50% emergence


Priming (T) 3 85.493* 174.627** 1.227** 0.482*

V×T 3 21.046ns 6.784ns 0.028ns 0.170ns

Error 16 25.918 31.477 0.112 0.139Total 23


Table 4.48: Influence of seed priming on final emergence (%) of barleyTreatments 2014-15 2015-16

H-93 F-87 Mean H-93 F-87 MeanControl 88.89 86.67 87.78 B 82.22 84.45 83.33 BHP 93.33 86.78 90.05 B 86.67 91.11 88.89 ABOP 95.55 97.78 96.67 A 95.55 95.55 95.55 ABP 91.11 91.11 91.11 AB 93.33 93.33 93.33 AMean 92.22 90.58 89.44 91.11


Table 4.49: Influence of seed priming on time taken to 50% emergence (days) of barleyTreatments 2014-15 2015-16

H-93 F-87 Mean H-93 F-87 MeanControl 4.33 4.59 4.46 A 4.64 5.20 4.92 AHP 3.89 3.85 3.87 B 4.52 4.39 4.45 BOP 3.40 3.44 3.42 C 4.27 4.26 4.26 BBP 3.63 3.61 3.62 BC 4.50 4.33 4.42 BMean 3.81 3.87 4.48 4.55


Table 4.50: Analysis of variance for the influence of seed priming on mean emergence time and emergence index of barley SOV df Mean sum of square

Mean emergence time Emergence index2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 0.038ns 0.025ns 0.048ns 0.021ns

Priming (T) 3 0.559** 0.384* 0.624** 0.672**

V×T 3 0.013ns 0.081ns 0.046ns 0.016ns

Error 16 0.077 0.085 0.070 0.034Total 23


102

Table 4.51: Influence of seed priming on mean emergence time (days) of barleyTreatments 2014-15 2015-16

H-93 F-87 Mean H-93 F-87 MeanControl 4.72 4.87 4.80 A 5.10 5.34 5.22 AHP 4.36 4.47 4.42 B 4.67 4.90 4.79 BOP 4.02 4.13 4.08 B 4.60 4.63 4.62 BBP 4.29 4.23 4.26 B 5.00 4.75 4.88 ABMean 4.35 4.43 4.84 4.91


Table 4.52: Influence of seed priming on emergence index of barleyTreatments 2014-15 2015-16

H-93 F-87 Mean H-93 F-87 MeanControl 3.03 2.90 2.97 C 2.69 2.65 2.67 CHP 3.44 3.13 3.29 BC 3.04 3.15 3.09 BOP 3.70 3.78 3.74 A 3.48 3.46 3.47 ABP 3.42 3.43 3.42 AB 3.13 3.31 3.22 BMean 3.40 3.31 3.08 3.14


103

years (Table 4.52).

4.2.2. Discussion

Emergence traits of barley varieties were improved by seed priming traits as

compared to unprimed control. Final emergence percentage and seed index was improved

while mean emergence time and time for 50% emergence was decreased by seed priming.

This may be due to time reduced for metabolism by controlled hydration of seed. Seed

priming allows the germination metabolism to occur without actual germination through

controlled hydration (Farooq et al., 2006a). Seed priming enhances activity of hydrolytic

enzymes and improves the carbohydrate metabolism in seeds which makes the food

reserves available for developing embryo (Farooq et al., 2009b). Moreover, improved

germination by seed priming is associated with exalted activity of α-amylase, β-amylase,

and dehydrogenase in root system and catalase in germinating seeds (He et al., 2002).

Moreover, seed priming enhances de novo synthesis of α-amylase (Lee and Kim, 2000).

In present study improved emergence by osmopriming might be due to the Ca2+ which is

structural part of cell wall structure, cell membrane integrity and permeability, and

regulates cell division and elongation (Hepler, 2005). The decreased cell membrane

leakage and improved cell membrane stability by Ca2+ leads to better germination with

increased germination time and seedling vigour index (Posmyk et al., 2001; Ruan et al.,

2002a, b). In current study better emergence by biopriming may be due to endophytic

bacteria which enhances seed germination by exalting water absorption, producing

cellular enzymes viz. amylase and protease and promotes the degradation of sucrose,

proteins and lipids resulting in better and earlier germination (Zhu et al., 2017).



Plant height was significantly affected by salinity and seed priming; barley

varieties also differed significantly for plant height, during both growing seasons. The

interaction between varieties and seed priming was significant during 2014-15 and non-

significant during 2015-16. The interactions between varieties and salinity, salinity and

seed priming as well as three way interaction among varieties, salinity and seed priming

was significant, during both years (Table 4.53). Salinity decreased the plant height and it

was proportional to its severity. Taller plants were produced by Frontier-87 than Haider-

93. Seed priming increased the plant height of tested barley varieties at each level of salt

stress, as compared to unprimed control. Under moderate salinity, biopriming of Frontier-

87 and osmopriming of Haider-93 produced the tallest plants during 2014-15 and 2015-104

16, respectively. However, under severe salinity, the tallest plants were produced by

osmopriming and biopriming of Haider-93 during 2014-15 and 2015-16, respectively

(Tables 4.54, 4.55).

4.2.3.2. Leaf area

Salinity and seed priming significantly affected the leaf area; barley varieties also

differed significantly for leaf area, during both growing seasons. The interaction between

varieties and seed priming was non-significant, during both years. However, the

interactions between varieties and salinity, salinity and seed priming, and three way

interaction among varieties, salinity and seed priming was significant, during both

growing seasons (Table 4.53). There was a progressive decrease in leaf area with increase

in severity of salt stress. Higher leaf area was produced by Frontier-87 than Haider-93.

Seed priming enhanced the leaf area of both varieties at all levels of salt stress, as

compared to unprimed control. Under moderate salinity, biopriming of Haider-93 and

osmopriming of Fronteirs-87 produced maximum leaf area during 2014-15 and 2015-16,

respectively. However, under severe salinity, the greatest increase in leaf area was caused

by biopriming of Frontier-87 during years (Tables 4.56, 4.57).

4.2.3.3. Total number of tillers per pot

There was a significant effect of salinity and seed priming on total number of

tillers; however, selected barley varieties did not differ significantly for total number of

tillers, during both years. The interactions between varieties and salinity, and varieties

and seed priming was non-significant during 2014-15 but significant during 2015-16.

However, the interaction between salinity and seed priming as well as three way

interaction among varieties, salinity and seed priming was significant, during both

growing seasons (Table 4.58). Total number of tillers was decreased with increase in

severity of salt stress. Haider-93 recorded higher number of tillers than Frontier-87. Seed

priming improved the total number of tillers of both barley varieties at all levels of

salinity, as compared to unprimed control. Under moderate salinity, maximum number of

tillers per pot were recorded by osmopriming of Frontier-87, during both years. Under

severe salinity, highest number of tillers was produced by osmopriming of Haider-93,

during both years (Tables 4.59, 4.60).

4.2.3.4. Number of productive tillers per pot

The number of productive tillers was significantly affected by salinity and seed

priming; however, the varieties did not differ significantly, during both years. The

interactions between varieties and salinity, and varieties and seed priming were non-105

significant during 2014-15 and significant during 2015-16. However, the interaction

between salinity and seed priming as well as three way interaction among varieties,

salinity

106

Table 4.53: Analysis of variance for the influence of seed priming on plant growth of barley under salinitySOV df Mean sum of square

Plant height Leaf area2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 573.01** 561.25** 38036.5** 3466.0**

Salinity (S) 2 2553.82** 3035.78** 361062.0** 303931.7**

Priming (T) 3 186.92** 69.28** 13956.3** 27489.2**

V×S 2 41.88** 153.00** 25629.0** 1570.3*

V×T 3 70.89** 9.19ns 1068.1ns 982.7ns

S×T 6 23.29** 91.61** 1372.3* 6107.7**

V×S×T 6 14.47** 60.11** 4097.1* 2109.4**

Error 72 4.61 6.05 523.5 432.2Total 95


Table 4.54: Influence of seed priming on plant height (cm) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 65.13 fg 77.80 c 58.86 j-m 62.61 ghi 52.40 n 58.55 lmHP 73.05 d 78.80 bc 61.84 hij 67.28 ef 57.64 m 59.48 j-mOP 80.95 ab 80.84 ab 61.41 i-l 64.82 fgh 63.66 ghi 61.07 i-lBP 72.83 d 82.37 a 61.57 ijk 70.05 de 58.73 klm 63.05 ghi

Varieties × Salinity × Seed priming LSD≤0.05 = 3.0253

Table 4.55: Influence of seed priming on plant height (cm) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 71.17 e 76.54 bc 69.90 e 65.16 f 44.39 i 58.35 gHP 72.64 de 79.20 ab 65.02 f 64.79 f 51.14 h 64.52 fOP 75.24 cd 82.42 a 70.29 e 69.74 e 51.12 h 56.75 gBP 70.73 e 77.85 bc 65.16 f 70.13 e 62.46 f 61.83 f


Table 4.56: Influence of seed priming on leaf area (cm2) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 496.99 cd 579.52 b 439.18 fgh 426.55 gh 291.69 m 311.91 lmHP 511.59 cd 585.11 b 412.26 hi 444.32 fgh 324.33 l 339.72 klOP 507.35 cd 633.10 a 463.93 ef 453.74 efg 387.43 ij 363.02 jkBP 520.90 c 644.46 a 481.73 de 432.33 fgh 331.14 kl 432.50 fgh

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties × Salinity × Seed priming LSD≤0.05 = 32.252

107

Table 4.57: Influence of seed priming on leaf area (cm2) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 495.20 efg 518.98 def 411.32 j 425.63 ij 324.78 m 314.24 mHP 537.53 cd 523.81 cde 451.84 hi 440.60 hij 321.74 m 341.06 lmOP 552.12 c 533.62 cd 492.76 fg 513.39 def 332.08 m 365.10 klBP 585.27 c 636.83 a 468.51 gh 439.47 hij 380.55 k 445.17 hi


Table 4.58: Analysis of variance for the influence of seed priming on number of total and productive tillers of barley under salinity SOV df Mean sum of square

Total No. of tillers per pot No. of productive tillers per pot


Salinity (S) 2 46.517** 30.607** 54.629** 42.388**

Priming (T) 3 14.296** 7.111** 7.065** 3.085**

V×S 2 0.538ns 3.234** 0.244ns 1.563**

V×T 3 0.034ns 1.315* 0.045ns 0.741*

S×T 6 1.114* 1.455* 0.756** 0.909**

V×S×T 6 1.405** 1.659** 0.828** 0.880*

Error 72 0.246 0.237 0.127 0.120Total 95


Table 4.59: Influence of seed priming on total number of tillers per pot of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 13.37 g-j 13.41 ghi 13.19 h-k 12.70 jkl 11.19 n 10.97 nHP 14.23 c-f 14.20 def 13.84 e-h 14.40 b-e 12.65 kl 11.93 mOP 13.90 efg 14.48 b-e 14.90 abc 15.49 a 13.59 fgh 12.22 lmBP 15.02 ab 14.84 a-d 15.47 a 14.61 bcd 12.05 lm 12.74 i-l


Table 4.60: Influence of seed priming on total number of tillers per pot of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 13.77 efg 13.81 efg 13.33 fgh 13.34 fgh 12.31 i 11.41 jHP 14.86 bc 14.62 bcd 13.98 def 15.13 ab 13.16 gh 12.42 iOP 12.88 hi 14.94 bc 14.45 b-e 15.64 a 13.95 def 12.82 hiBP 15.07 ab 14.38 cde 15.00 abc 14.76 bc 12.66 hi 12.74 hi


108

and seed priming was significant, during both growing seasons (Table 4.58). Number of

productive tillers was decreased with increase in severity of salt stress. Haider-93

produced higher number of productive tillers than Frontier-87. Moreover, seed priming

improved the number of productive tillers of both barley varieties at each level of salinity,

as compared to unprimed control. Under moderate salinity, maximum number of

productive tillers was produced by biopriming of Haider-93 during 2014-15 and

osmopriming of Frontier-87 during 2015-16. Under severe salinity, highest number of

productive tillers was produced by osmopriming of Haider-93, during both years (Tables

4.61, 4.62).


Spike length was significantly affected by salinity and seed priming; while, the

tested varieties also differed for spike length, during both years. The interaction between

varieties and seed priming was significant during 2014-15 while non-significant during

2015-16. The spike length was not affected significantly by interaction between varieties

and salinity, during both years. Interaction between salinity and seed priming, and three

way interaction among varieties, salinity and seed priming were significant, during both

years (Table 4.63). There was a progressive decrease in spike length with increase in

severity of salinity. Longer spikes were produced by Haider-93 than Frontier-87.

However, spike length of both varieties was enhanced by seed priming treatments under

all levels of salt stress, as compared to unprimed control. Under moderate stress,

osmopriming and biopriming of Frontier-87 caused maximum increase spike length

during 2014-15 and 2015-16, respectively. Under severe salinity, biopriming of Haider-

93 produced the longest spikes, during both years (Tables 4.64, 4.65).


The number of spikelets per spike was significantly affected by salinity and seed

priming, during both years. The varieties did not differ significantly during 2014-15 while

significantly differed during 2015-16. The interaction between varieties and salinity was

non-significant during 2014-15 but significant during 2015-16. The interactive effect of

varieties and seed priming, salinity and seed priming, as well as three way interaction

among varieties, salinity and seed priming was significant, during both growing seasons

(Table 4.63). Salinity decreased the number of spikelets per spike and it was proportional

to its severity. More number of spikelets per spike was produced by Haider-93 than

Frontier-87. The number of spikelets per spike of tested barley varieties were improved

by seed priming treatments under all levels of salt stress, as compared to unprimed 109

control. Under moderate salinity, osmopriming of Frontier-87 and Haider-93 caused

maximum increase in number of spikelets per spike during 2014-15 and 2015-16,

respectively. However, under severe salinity, biopriming of Haider-93 produced

maximum number of spikelets per spike, during both growing seasons (Tables 4.66,

4.67).


Salinity and seed priming significantly affected the grains per spike of barley;

tested barley varieties also differed for grains per spike, during both growing seasons.

Interaction between variety and salinity was significant, during both years. However, the

interactions between variety and seed priming, and salinity and seed priming were

significant during 2014-15 but non-significant during 2015-16. The three way interaction

among variety, salinity and seed priming was significant for grains per spike, during both

years (Table 4.68). Salinity decreased the number of grains per spike and it was

proportional to its severity. Higher number of grains per spike was produced by Haider-

93 than Frontier-87. Seed priming enhanced the production of number of grains per spike

of both barley varieties at all levels of salinity, as compared to unprimed control. Under

moderate salinity, biopriming of Fronteirs-87 and Haider-93 produced maximum number

of grains per spike during 2014-15 and 2015-16, respectively. Under severe salinity,

biopriming of Haider-93 caused maximum increase in number of grains per spike during

both year. However, during 2015-16 osmopriming of Haider-93 produced similar number

of grains per spike (Tables 4.69, 4.70).


The 100-grain weight was significantly affected by salinity and seed priming

during years. The tested barley varieties also differed for 100-grain weight, during both

years. The interaction between varieties and salinity was non-significant during 2014-15

but significant during 2015-16. Interaction between varieties and seed priming was

significant during 2014-15 and non-significant during 2015-16. The interaction between

salinity and seed priming, and three way interaction among varieties, salinity and seed

priming were significant, during both years (Table 4.68). The 100-grain weight was

decreased with increase in severity of salt stress. Haider-93 produced higher 100-grain

weight than Frontier-87. Furthermore, seed priming improved the 100-grain weight of

both varieties at each level of salinity, as compared to unprimed control. Under mild

salinity, biopriming and osmopriming of Haider-93 had maximum increase in 100-grain

weight during 2014-15 and 2015-16, respectively. However, under severe salinity, the 110

greatest improvement in 100-grain weight was recorded by osmopriming of Haider-93,

during both years (Tables 4.71, 4.72).

Table 4.61: Influence of seed priming on number of productive tillers per pot of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 10.29 de 10.31 de 9.42 fg 9.07 gh 7.67 kl 7.52 lHP 10.78 cd 10.75 cd 9.88 ef 10.29 de 8.61 hij 8.12 jkOP 10.45 cd 10.89 bc 10.53 cd 10.95 bc 9.25 g 8.31 ijBP 11.47 a 11.33 ab 11.46 a 10.51 cd 8.25 ij 8.73 hi


Table 4.62: Influence of seed priming on number of productive tillers per pot of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 10.59 cd 10.62 cd 9.52 fg 9.53 fg 8.43 i 7.81 jHP 11.26 ab 11.08 abc 9.98 ef 10.80 bc 8.95 h 8.45 iOP 9.69 fg 11.23 ab 10.22 de 11.06 abc 9.49 g 8.72 hiBP 11.51 a 10.98 bc 10.79 bc 10.62 cd 8.67 hi 8.73 hi


Table 4.63: Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under salinity SOV df Mean sum of square

Spike length No. of spikelets per spike2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 2.548** 6.652** 0.158ns 5.202**

Salinity (S) 2 18.301** 18.712** 67.060** 87.847**

Priming (T) 3 2.506** 3.338* 15.185** 10.521**

V×S 2 0.035ns 0.145ns 0.236ns 1.742**

V×T 3 2.626** 0.244ns 3.970** 0.640*

S×T 6 1.110** 1.115** 0.987* 1.000**

V×S×T 6 0.365* 0.885** 1.301** 1.234**

Error 72 0.077 0.157 0.205 0.197Total 95


Table 4.64: Influence of seed priming on spike length (cm) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 7.64 cde 7.14 fg 7.48 ef 6.39 ij 6.26 ij 6.03 jHP 7.93 bcd 7.94 bc 7.55 de 8.14 b 6.17 ij 6.31 ijOP 7.89 bcd 7.69 cde 7.74 cde 8.21 b 6.52 hi 6.80 ghBP 8.95 a 8.24 b 7.97 bc 6.49 hi 7.37 ef 6.17 ij

111


112

Table 4.65: Influence of seed priming on spike length (cm) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 8.09 bc 7.63 c-f 7.73 b-f 6.41 hi 5.62 j 5.72 jHP 8.07 bcd 7.52 def 7.91 b-e 6.91 gh 7.30 fg 6.62 hOP 8.13 abc 8.13 abc 8.08 bcd 7.31 fg 6.87 gh 6.02 ijBP 8.25 ab 7.77 b-f 8.08 bcd 8.69 a 7.37 efg 6.47 hi


Table 4.66: Influence of seed priming on number of spikelets per spike of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 13.37 c 13.03 cd 11.73 fg 11.33 gh 10.38 i 9.81 iHP 13.37 c 13.20 cd 12.60 de 13.27 c 11.08 h 11.08 hOP 13.54 bc 15.34 a 13.54 bc 13.54 bc 11.08 h 12.03 efBP 15.94 a 14.14 b 13.20 cd 13.37 c 12.37 ef 11.08 h


Table 4.67: Influence of seed priming on number of spikelets per spike of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 13.50 cd 13.16 def 11.88 g 11.54 gh 9.70 jk 9.37 kHP 13.76 bcd 13.33 cde 12.60 f 11.64 gh 10.14 j 10.80 iOP 15.66 a 13.42 cd 13.82 bc 13.20 c-f 10.80 i 10.80 iBP 14.37 b 13.42 cd 12.75 ef 13.37 cde 11.73 g 11.05 hi


Table 4.68: Analysis of variance for the influence of seed priming on number of grains per spike and 100-grain weight of barley under salinity SOV df Mean sum of square

No. of grains per spike 100-grain weight2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 26.660** 82.381** 1.044** 0.158**

Salinity (S) 2 691.712** 850.569** 5.445** 14.597**

Priming (T) 3 54.320** 57.804** 0.946** 0.779**

V×S 2 4.145* 11.312** 0.012ns 0.381**

V×T 3 3.558* 1.390ns 0.080** 0.026ns

S×T 6 2.835* 0.861ns 0.065** 0.084**

V×S×T 6 6.047** 6.179** 0.085** 0.079**

Error 72 1.040 1.213 0.008 0.015Total 95


113

Table 4.69: Influence of seed priming on number of grains per spike of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 34.49 c 32.88 d 30.33 fg 27.45 ij 24.63 lm 23.85 mHP 35.79 bc 32.88 d 30.77 ef 30.98 ef 27.21 ij 26.08 jkOP 37.70 a 35.89 bc 32.09 de 31.44 ef 25.36 kl 27.96 hiBP 38.10 a 36.92 ab 31.87 de 32.15 de 28.98 gh 26.19 jk


Table 4.70: Influence of seed priming on number of grains per spike of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 32.84 d 30.97 ef 28.57 gh 27.02 h 21.53 l 21.42 lHP 33.63 cd 32.30 de 31.00 ef 25.78 ij 22.56 kl 23.26 kOP 35.52 b 34.58 bc 30.97 ef 28.55 gh 25.47 ij 22.94 klBP 37.35 a 33.00 d 32.18 de 29.84 fg 25.48 ij 25.22 j


Table 4.71: Influence of seed priming on 100-grain weight (g) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 3.21 cd 3.06 ef 2.82 h 2.67 i 2.38 j 2.19 kHP 3.42 b 3.02 efg 2.97 fg 2.68 i 2.83 h 2.44 jOP 3.49 b 3.69 a 3.12 de 3.08 ef 2.90 gh 2.49 jBP 3.81 a 3.45 b 3.28 c 2.96 fg 2.67 i 2.65 i


Table 4.72: Influence of seed priming on 100-grain weight (g) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 3.46 c 3.50 c 2.92 fg 3.01 ef 2.47 ijk 2.33 klHP 3.60 c 3.88 b 2.77 gh 3.18 d 2.45 jk 2.23 lOP 3.80 b 4.35 a 3.26 d 3.18 d 2.72 h 2.55 ijBP 3.92 b 4.19 a 3.15 de 3.16 de 2.63 hi 2.55 ij


114

4.2.3.9. Grain yield per pot

A significant effect of salinity and seed priming on grain yield was noticed, during

both years; the barley varieties also differed significantly for grain yield, during both

growing seasons. The interaction between varieties and salinity was non-significant

during 2014-15 while significant during 2015-16. However, the interactions between

varieties and seed priming, salinity and seed priming, and three way interaction among

varieties, salinity and seed priming was significant, during both years (Table 4.73). The

grain yield was decreased with increase in severity of salt stress. Higher grain yield was

produced by Haider-93 than Frontier-87. Grain yield of both varieties was improved by

seed priming treatments under all levels of salinity, as compared to unprimed control.

Under moderate salinity, biopriming of Haider-93 exhibited greatest improvement in

grain yield, during both years. Under severe salinity, osmopriming of Haider-93 caused

maximum improvement in grain yield, during both years (Tables 4.74, 4.75).

4.2.3.10. Biological yield per pot

Biological yield was significantly affected by salinity and seed priming, during

both growing seasons; however, the barley varieties significantly differed during 2014-15

but did not differ significantly during 2015-16. The interactions between varieties and

salinity, and salinity and seed priming were significant during 2014-15 but non-

significant during 2015-16. The interaction between varieties and salinity, and three way

interaction among varieties, salinity and seed priming were significant, during both years

(Table 4.73). Salinity decreased the biological yield and it was proportional to its severity.

Under control and moderate salinity higher biological yield was exhibited by Frontier-87

while under severe salinity Haider-93 gave higher biological yield. Seed priming

enhanced the biological yield of both tested barley varieties at all levels of salt stress, as

compared to unprimed control. Under moderate salinity, the greatest increase in

biological yield was recorded by osmopriming of Frontier-87 and biopriming of Haider-

93 during 2014-15 and 2015-16, respectively. However, under severe salinity, biopriming

of Frontier-87 and osmopriming of Haider-93 exhibited highest biological yield, during

2014-15 and 2015-16, respectively (Tables 4.76, 4.77).


There was a significant effect of salinity and seed priming on harvest index; the

selected barley varieties also differed for harvest index, during both years. The interaction

between varieties and salinity was non-significant during 2014-15 and significant during

2015-16. The interactions between varieties and seed priming as well as salinity and seed 115

priming were significant during 2014-15 but non-significant during 2015-16. The three

way interaction among varieties, salinity and seed priming was significant, during both

growing seasons (Table 4.73). Harvest index was decreased with increase in severity of

salt stress. Haider-93 recorded higher harvest index than Frontier-87. Seed priming

improved the harvest index of both barley varieties at all levels of salinity, as compared to

unprimed control. Under moderate salinity, highest harvest index was noticed by

osmopriming of Haider-93, during both years; while, under severe salinity, osmopriming

and biopriming of Haider-93 greatest increase in harvest index of barley during 2014-15

and 2015-16, respectively (Tables 4.78, 4.79).

4.2.4. Discussion

Salinity caused a reduction in growth and development of both barley varieties;

nonetheless, seed priming improved the plant height and leaf area. Deccarese in growth

and development by salt stress is attributed to osmotic stress (Farooq et al., 2015), ion

toxicity and oxidative stress induced by salinity (Munns and Tester, 2008). In present

study, improved growth by seed priming might be due to early head start and improved

stress tolerance by enhanced osmolytes accumulation and activity of antioxidants under

stressed conditions (Chen and Arora, 2013). Moreover, osmopriming enhances gene

expression and transcription factors for osmolytes, antioxidants, carbohydrate

metabolism, nitrogen metabolism, cell development and response to oxidative stress

under stress conditions (Hussain et al., 2016). Moreover, Ca2+ used in osmopriming in

present study, is the structural component of cell wall, regulates cell membrane integrity

and cell division by acting as the secondary messenger in signaling pathway that regulates

calmodulin like proteins and modulates growth processes (White and Broadley, 2003;

Hepler, 2005; Sarwat et al., 2013). In biopriming, endophytic bacteria improved the plant

growth by enhancing water and nutrient uptake which may be due to better root growth

and enhanced synthesis of growth promoting hormones i.e. auxin, gibberellic acid and

cytokinins while decreasing the ethylene production by producing ACC deaminase

(Santoyo et al., 2016).

Yield and related traits of both barley varieties were decreased by salt stress while

Haider-93 performed better in this regard. However, seed priming improved the grain

yield and harvest index by improving the spike length, number of spikelets per spike, and

number of grains and grain weight of both varieties. Salinity adversely affects the pollen

viability which decreases the number of seeds per plant and plant yield (Gul and Ahmad,

2006). Moreover, decreased photosynthesis and assimilate partitioning by salinity 116

decreases grain weight and grain yield (Cruz et al., 2017). However, in this study,

improved spike length

117

Table 4.73: Analysis of variance for the influence of seed priming on grain yield, biological yield and harvest index of barley under salinitySOV df Mean sum of square

Grain yield Biological yield Harvest index2014-15 2015-16 2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 7.031** 1.197** 3.648* 1.149ns 185.148** 53.000**

Salinity (S) 2 148.015** 209.824** 599.284** 817.033** 449.178** 714.016**

Priming (T) 3 14.941** 7.976** 41.198** 16.538** 58.858** 48.122**

V×S 2 0.177ns 0.978** 12.792** 13.176** 4.102ns 14.911*

V×T 3 1.398** 0.793** 5.154** 2.766ns 14.445** 1.926ns

S×T 6 0.993** 0.883** 2.641** 2.695ns 5.080* 2.939ns

V×S×T 6 0.997** 0.611** 7.600** 6.585** 9.831** 12.383**

Error 72 0.118 0.088 0.721 1.228 1.906 1.465Total 95


Table 4.74: Influence of seed priming on grain yield (g per pot) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 8.53 e 8.65 e 7.05 g 6.83 g 5.13 jk 4.28 lHP 9.62 c 8.68 e 8.05 f 7.18 g 5.88 hi 5.01 kOP 9.72 c 10.46 b 8.82 de 8.93 de 6.09 h 5.33 jkBP 11.73 a 9.75 c 9.28 cd 8.63 e 5.88 hi 5.55 ij


Table 4.75: Influence of seed priming on grain yield (g per pot) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 8.34 e 8.00 ef 6.47 ij 6.19 j 4.09 m 3.63 nHP 8.85 d 9.33 c 6.75 hi 6.74 hi 4.27 lm 3.97 mnOP 9.28 c 10.62 a 7.36 g 6.88 hi 4.85 k 4.23 mBP 10.62 a 9.85 b 7.91 f 7.09 gh 4.67 kl 4.24 m


Table 4.76: Influence of seed priming on biological yield (g per pot) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 24.62 gh 26.66 cd 23.28 i 23.60 hi 18.38 kl 16.56 mHP 25.03 efg 28.67 ab 24.78 fgh 26.64 cd 20.11 j 17.99 lOP 25.98 de 27.77 bc 25.95 def 28.39 b 20.12 j 19.16 jklBP 29.65 a 27.51 bc 27.81 bc 26.73 cd 19.50 jk 20.22 j


118

Table 4.77: Influence of seed priming on biological yield (g per pot) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 23.77 def 24.95 bcd 21.43 gh 21.45 gh 15.61 jkl 14.28 lHP 24.84 bcd 25.47 b 20.49 h 24.80 bcd 16.96 ij 14.93 klOP 25.41 bc 27.62 a 21.40 g 22.48 efg 17.18 i 15.49 jklBP 27.43 a 27.24 a 23.90 cde 22.34 fg 16.26 ijk 16.25 ijk


Table 4.78: Influence of seed priming on harvest index (%) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 34.68 cd 32.47 ef 30.27 gh 28.92 hi 27.91 ij 25.82 kHP 38.43 ab 30.29 gh 32.50 ef 26.97 jk 29.21 hi 27.88 ijOP 37.42 b 37.68 ab 33.98 cde 31.47 fg 30.24 gh 27.82 ijBP 39.59 a 35.44 c 33.47 de 32.35 ef 30.18 gh 27.43 ijk


Table 4.79: Influence of seed priming on harvest index (%) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity

H-93 F-87 H-93 F-87 H-93 F-87Control 35.07 bc 32.17 ef 30.21 ghi 28.89 hij 26.22 kl 25.42 lHP 35.67 bc 36.63 b 32.98 de 27.22 jk 25.18 l 26.63 klOP 36.55 b 38.46 a 34.37 cd 30.59 fgh 28.34 j 27.34 jkBP 38.75 a 36.19 b 33.12 de 31.73 efg 28.76 ij 26.10 kl


119

by seed priming resulted in improved number of spikelets and grains ultimately

improving the grain yield. Moreover, the grain weight was improved by seed priming

treatments which contributed to improved grain yield and harvest index. The improved

osmolytes accumulation, tissue water status and better protection of cellular membranes

from lipid peroxidation by seed priming is attributed to improved number of grains and

grain weight under salinity (Tabassum et al., 2017).

In present study, the yield improvement by osmopriming, is attributed to

improved osmolytes accumulation, tissue water status, cell membrane stability and

decreased lipid peroxidation. The Ca2+, used in osmopriming, is involved in cell

membrane stability which might have improved the pollen viability and number of grains.

Moreover, Ca2+ improves the photosynthesis, decreases ROS activity and lipid

peroxidation by enhancing osmolytes accumulation and activity of antioxidants ultimately

improving the number of grains, grain weight and grain yield under stressed conditions

(Dolatabadian et al., 2013). In present study, the biopriming improved the grain yield of

barley which was associated with improved plant growth that led to enhanced spike

length, number of spikelets and grains and grain weight. Moreover, the enhanced

osmolytes accumulation, better water relations and well maintained cell membrane

stability due to decreased lipid peroxidation was translated in improved grain yield and

harvest index. Endophytic bacteria, used in biopriming, enhances growth and

development by production of auxin while decreasing the ethylene accumulation that

results in improved chlorophyll, greater accumulation of osmolytes, and improved water

and nutrient relations which is translated into improved yield and harvest index (Miliute

et al., 2015; Santoyo et al., 2016; Montalbán et al., 2017). Similar, Naveed et al. (2014c)

reported that endophytic bacteria Burkholderia phytofrmans strain PsJN improved the

photosynthesis, nutrients uptake, water relations, and yield and related traits of wheat

under drought stress.



Salinity and seed priming induced a significant effect on chlorophyll a content;

tested barley varieties also significantly differed for chlorophyll a content, during both

growing seasons. The interactions between varieties and salinity, varieties and seed

priming, salinity and seed priming, and three way interaction among varieties, salinity

and seed priming was significant, during both years (Table 4.80). The chlorophyll a

content was decreased with increase in severity of salt stress. Higher chlorophyll a 120

content was exhibited by Frontier-87 during 2014-15 while during 2015-16 Haider-93

produced more chlorophyll a content. Seed priming ameliorated the deleterious effects of

salinity by improving the chlorophyll a content of tested barley varieties at each level of

salt stress, as compared to unprimed control. Under moderate salinity, the biosynthesis of

chlorophyll a was exaggerated by biopriming of Frntiers-87 and hydropriming of Haider-

93 during 2014-15 and 2015-16, respectively. However, under severe salinity, maximum

increase in chlorophyll a content was recorded by osmopriming of Haider-93 and

biopriming of Frontier-87 during 2014-15 and 2015-16 (Figures 4.7a,b).

4.2.5.2. Chlorophyll b content

Chlorophyll b content was significantly affected by salinity and seed priming,

during both years. Similarly, barley varieties also differed significantly for chlorophyll b,

during both growing seasons. The interaction between varieties and salinity was non-

significant during 2014-15 but significant during 2015-16. The interaction between

varieties and seed priming, salinity and seed priming as well as three way interaction

among varieties, salinity and seed priming was significant, during both years (Table

4.80). Salinity decreased the chlorophyll b and it was proportional to its severity. More

chlorophyll b content was produced by Haider-93 than Frontier-87. However, seed

priming ameliorated the deleterious effects of salinity by improving the chlorophyll b of

both varieties at all levels of salinity, as compared to unprimed control. Chlorophyll b

content was exalted by biopriming of Haider-93 under both moderate and severe salinity,

during both years (Figures 4.7c,d).


4.2.6.1. Total soluble phenolics

Salinity and seed priming significantly affected total soluble phenolics contents,

during both growing seasons; the varieties also differed significantly for total soluble

phenolics contents. The interactions between varieties and salinity, varieties and seed

priming, salinity and seed priming, and three way interaction among varieties, salinity

and seed priming was significant, during both years (Table 4.81). The total soluble

phenolics content was increased with increase in severity of salt stress. Frontier-87

produced higher total soluble phenolics than Haider-93. Moreover, seed priming further

improved the production of total soluble phenolics of both barley varieties at each level of

salinity, as compared unprimed control. During 2014-15, greatest increase in total soluble

phenolics content was caused by osmopriming of Haider-93 under both moderate and

severe salinity. However, during 2015-16, highest total soluble phenolics content was 121

noticed by biopriming and osmopriming of Haider-93 under moderate and severe salt

stress,

122

Table 4.80: Analysis of variance for the influence of seed priming on chlorophyll contents of barley under salinity SOV df Mean sum of square


Varieties (V) 1 0.0018** 0.0050** 0.0053** 0.0107**

Salinity (S) 2 0.2494** 0.3547** 0.0914** 0.1363**

Priming (T) 3 0.0238** 0.0048** 0.0064** 0.0053**

V×S 2 0.0019* 0.0006** 0.0001ns 0.0019**

V×T 3 0.0049** 0.0007** 0.0004** 0.0003*

S×T 6 0.0023** 0.0016** 0.0010** 0.0009**

V×S×T 6 0.0021** 0.0010** 0.0004** 0.0016**

Error 72 0.0001 0.0001 0.0001 0.0001Total 95

Table 4.81: Analysis of variance for the influence of seed priming on total soluble proteins and total soluble phenolics contents of barley under salinity SOV df Mean sum of square

Total soluble phenolics Total soluble proteins2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 2800.4** 1882.1* 0.0408** 0.0044**

Salinity (S) 2 131106.8** 251795.2** 0.5409** 0.8596**

Priming (T) 3 11235.6** 4813.8** 0.0109** 0.0033**

V×S 2 3707.5** 8575.6** 0.0094** 0.0028**

V×T 3 3306.7* 1936.9** 0.0018* 0.0008ns

S×T 6 2789.9** 1563.6** 0.0017** 0.0017**

V×S×T 6 356.5** 2240.5** 0.0040** 0.0024**

Error 72 104.9 207.7 0.0002 0.0004Total 95


123

Chl

orop

hyll

a co

nten

t (m

g g-1

FW

)C

hlor

ophy

ll b

cont

ent (

mg

g-1 F

W)

124

Tot

al so

lubl

e ph

enol

ics (

µg g

-1 F

W)

Tot

al so

lubl

e pr

otei

ns (m

g g-1

FW)

125

respectively (Figures 4.8a,b).

4.2.6.2. Total soluble proteins

Total soluble proteins were significantly affected by salinity and seed priming; the

barley varieties significantly differed, during both growing seasons. The interaction

between varieties and seed priming was significant during 2014-15 while non-significant

during 2015-16. However, the interactions between varieties and salinity, salinity and


was significant, during both years (Table 4.81). Total soluble proteins were increased

with increase in severity of salt stress. Higher total soluble proteins were produced by

Haider-93 than Frontier-87. Seed priming ameliorated the deleterious effects of salinity

by further enhancing the accumulation of total soluble proteins of both varieties at each

level of salt stress, as compared unprimed control. Under moderate stress, greatest

increase in total soluble proteins was caused by osmopriming of Haider-93 and

biopriming of Frontier-87 during 2014-15 and 2015-16, respectively. Under severe

salinity, biopriming and hydropriming of Haider-93 exhibited highest total soluble

proteins during 2014-15 and 2015-16, respectively (Figures 4.8c,d).

4.2.6.3. Free proline content

There was a significant effect of salinity and seed priming on free leaf proline

content; the tested barley varieties also differed significantly, during both years. The

interaction between varieties and seed priming, varieties and salinity, salinity and seed

priming, and three way interaction among varieties, salinity and seed priming was

significant, during both growing seasons (Table 4.82). Free proline content was increased

by salt stress relative to its severity. Higher free proline content was exhibited by Haider-

93 than Frontier-87. Seed priming enhanced the accumulation of free proline in both

barley varieties at all levels of salinity, as compared unprimed control. Under moderate

salinity, greatest increase in free leaf proline content was recorded by biopriming of

Frontier-87 and hydropriming of Haider-93 during 2014-15 and 2015-16, respectively.

However, under severe salinity, osmopriming and biopriming of Haider-93 caused

maximum increase in proline content during 20114-15 and 2015-16, respectively (Figures

4.9a,b).4.2.6.4. Glycine betaine content

Leaf glycine betaine content was significantly affected by salt stress and seed

priming; tested barley varieties also differed significantly, during both years. The

interactions between varieties and salinity, and varieties and seed priming were non-

significant during 2014-15 but significant during 2015-16. However, interaction between 126


priming were significant, during both years (Table 4.82). The glycine betaine content was

increased with increase in severity of salt stress. Haider-93 accumulated more glycine

betaine than Frontier-87. Glycine betaine content was further increased by seed priming

in both varieties at all levels of salt stress, as compared to unprimed control. Under

moderate stress, highest glycine betaine content was noticed by osmopriming of Haider-

93, during both years. However, under severe salt stress, biopriming and osmopriming of

Haider-93 caused maximum increase in glycine betaine content during 2014-15 and

2015-16, respectively (Figures 4.9c,d).

4.2.7. Lipid peroxidation

4.2.7.1. Malondialdehyde content

There was a significant effect of salinity and seed priming on MDA content,

during both years; the tested barley varieties also differed significantly for MDA content.

The interaction between varieties and seed priming was significant during 2014-15 but

non-significant during 2015-16. However, interactions between varieties and salinity,


priming was significant, during both seasons (Table 4.83). The MDA content was

increased with increase in severity of salt stress. Higher MDA content was accumulated

in Frontier-87 than Haider-93. Seed priming ameliorated the deleterious effects of salinity

by lowering down MDA accumulation in tested barley varieties at all levels of salinity, as

compared to unprimed control. Minimum MDA accumulation occurred in response to

osmopriming of Haider-93 under both moderate and severe salinity, during 2014-15.

However, during 2015-16 biopriming of Haider-93 caused maximum decrease in MDA

under both moderate and severe salinity (Figures 4.10a,b).

4.2.7.2. Cell membrane stability

A significant effect of salinity and seed priming was observed for cell membrane

stability; tested barley varieties also differed significantly for cell membrane stability,

during both growing seasons. The interaction between salinity and seed priming was non-

significant during 2014-15 but significant during 2015-16. However, interactions between

varieties and salinity, and varieties and seed priming, and three way interaction among

varieties, salinity and seed priming was significant, during both years (Table 4.83).

Salinity decreased the cell membrane stability and it was proportional to its severity.

Haider-93 recorded higher cell membrane stability than Frontier-87. Seed priming

improved the cell membrane stability of both varieties at all levels of salinity, as 127

compared to unprimed control. Under moderate salt stress, greatest improvement in cell

membrane stability was noticed by osmopriming and biopriming of Haider-93 during

2014-15 and 2015-16, respectively. Under severe salinity, osmopriming and

hydropriming of Haider-93 was superior in improving cell membrane stability during

2014-15 and 2015-16, respectively (Figures 4.10c,d).

4.2.8. Mineral analysis

4.2.8.1. Na content

The Na content was significantly affected by salinity and seed priming, while,

varieties also differed significantly for Na content, during both years. Moreover, the

interactions between varieties and salinity, varieties and seed priming, salinity and seed

priming as well as three way interaction among varieties, salinity and seed priming was

significant for Na content, during both years (Table 4.84). The Na content was increased

with increase in severity of salt stress. Haider-93 accumulated less Na than Frontier-87.

Moreover, seed priming decreased the accumulation of Na in both barley varieties at each

level of salt stress, as compared to unprimed control. Under moderate salts stress,

minimum Na accumulation occurred by biopriming of Frontier-87 and osmopriming of

Haider-93 during 2014-15 and 2015-16, respectively. However, under severe salinity,

minimum Na accumulation was recorded by osmopriming of Haider-93, during both

years (Figures 4.11a,b).

4.2.8.2. K content

Leaf K content was significantly affected by salinity and seed priming, during

both growing seasons; varieties also differed significantly for K content. The interaction

between varieties and seed priming was non-significant during 2014-15 but significant

during 2015-16. However, the interactions between varieties and salinity, salinity and


was significant, during both growing seasons (Table 4.84). The K content was

proportionally decreased by salt stress relative to its severity. Higher K content was

exhibited by Haider-93 than Frontier-87. Seed priming enhanced the K content in both

varieties at each level of salinity, as compared to unprimed control. Under moderate

salinity, the greatest increase in K content was recorded by hydropriming and

osmopriming of Haider-93 during 2014-15 and 2015-16. Whereas, under severe salts

stress, maximum K content was noticed by osmopriming and hydropriming of Haider-93

during 2014-15 and 2015-16, respectively (Figures 4.11c,d).

128

Table 4.82: Analysis of variance for the influence of seed priming on free proline and glycine betaine contents of barley under salinity SOV df Mean sum of square

Free proline content Glycine betaine content2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 0.1321** 0.0389** 0.0324** 0.0193**

Salinity (S) 2 1.7916** 1.3544** 0.4837** 0.6131**

Priming (T) 3 0.1871** 0.0254** 0.0266** 0.0338**

V×S 2 0.0344** 0.0094** 0.0011ns 0.0236**

V×T 3 0.0187** 0.0013* 0.0009ns 0.0025*

S×T 6 0.0518** 0.0069** 0.0180** 0.0077**

V×S×T 6 0.0199** 0.0035** 0.0059** 0.0035**

Error 72 0.0021 0.0005 0.0006 0.0006Total 95

Table 4.83: Analysis of variance for the influence of seed priming on malondialdehyde and cell membrane stability of barley under salinitySOV df Mean sum of square

Malondialdehyde Cell membrane stability2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 171.42** 340.34** 53.03** 54.76**

Salinity (S) 2 889.52** 1395.97** 5318.72** 4981.59**

Priming (T) 3 171.89** 84.63** 547.86** 249.60**

V×S 2 36.58** 32.94** 30.69** 131.14**

V×T 3 12.41** 1.96ns 21.77* 42.13**

S×T 6 37.72** 11.61** 7.17ns 22.89**

V×S×T 6 17.38** 11.37** 27.47** 26.17**

Error 72 2.37 1.78 5.87 2.08Total 95

Table 4.84: Analysis of variance for the influence of seed priming on leaf mineral contents of barley under salinitySOV df Mean sum of square

Na content K content 2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 99982** 111203** 45581** 8963**

Salinity (S) 2 15498035** 18125546** 148125** 297312**

Priming (T) 3 224227** 37860** 10695** 2892**

V×S 2 95082** 138417** 2617** 2888**

V×T 3 42443* 14439* 833ns 2966**

S×T 6 104532** 23474** 2396** 793*

V×S×T 6 29189** 10670** 1611** 1626**

Error 72 1476 509 314 194Total 95


129

Free

pro

line

cont

ent (

µmol

g-1 F

W)

Gly

cine

bet

aine

con

tent

(µm

ol g

-1 F

W)

130

Mal

ondi

alde

hyde

con

tent

(µm

ol g

-1 F

W)

Cel

l mem

bran

e st

abili

ty (%

)

131

Na

cont

ent (

mg

g-1 D

W)

K c

onte

nt (m

g g-1

DW

)

132

4.2.9. Discussion

Salt stress decreased the chlorophyll contents, cell membrane stability and K

content while increased osmolytes accumulation, Na and MDA contents in both barley

varieties with increase in its severity and more deleterious effects on Frontier-87. Salinity

decreases plant growth and dry matter accumulation by decreasing the net assimilation

rate (NAR), relative water content, leaf water potential, soluble sugars, K+, Ca2+ and

Mg2+ contents, chlorophyll and carotenoids contents, and number and size of stomata

while increasing the Na+, Cl− and lipid peroxidation (Karimi et al., 2005; Farooq et al.,

2015). However, plants respond to salt stress by increased osmolytes accumulation,

antioxidants activity and selective uptake of Na+ and K+ which results in improved water

relations and decreased lipid peroxidation by ROS (Munns and Tester, 2008).

In present study, seed priming improved the chlorophyll contents and cell

membrane stability by enhanced accumulation of phenolics, total soluble proteins, proline

and glycine betaine while decreased lipid peroxidation in both barley varieties. Improved

chlorophyll contents by seed priming is attributed to well-maintained cell membrane

stability due to better protection of cellular membranes from lipid peroxidation (Song et

al., 2017). Under stressed conditions, the osmopriming enhances stress tolerance by

triggering the gene expression for osmolytes, antioxidants and stress proteins (Chen et al.,

2012; Kubala et al., 2015; Souza et al., 2016) and improving the tissue water status,

chloroplast structure and functioning of chlorophyll (Kubala et al., 2015; Tabassum et al.,

2017; Dai et al., 2017), while lowering the lipid peroxidation damage to cellular

membranes (Zhang et al., 2015). Furthermore, in present study the Ca2+ used in

osmopriming, triggers the gene expression for osmolytes, and improves plant growth and

stress tolerance by regulating the calmodulin like proteins in signaling pathways (White

and Broadley, 2003; Sarwat et al., 2013).

Biopriming improved the plant growth and stress tolerance by improving the

chlorophyll contents, osmolytes accumulation and decreased lipid peroxidation in both

barley varieties under severe salt stress. Plant growth promoting bacteria improves the

stress tolerance through enhanced osmolytes accumulation, antioxidants defense, nutrient

uptake and carbohydrates metabolism (Dimkpa et al., 2009; Chakraborty et al. 2011)

which results in decreased lipid peroxidation and better cell membrane stability

(Theocharis et al., 2012). Endophytic bacteria in biopriming, place the metabolism of

plants in primed state that enable greater and rapid accumulation of transcription factors

133

and metabolites for osmolytes and stress related gene expression (Theocharis et al., 2012;

Miotto-Vilanova et al., 2016).

Seed priming enhanced K accumulation while decreased Na accumulation in both

barley varieties under severe salinity. Osmopriming triggers the gene expression for high

affinity potassium transporter protein 1 (HAK1) and the salt overly sensitive 1 (SOS 1)

antiporter which causes increase in K and decrease in Na uptake and accumulation under

stressed conditions (Souza et al., 2016). Moreover, extracellular Ca2+ causes a decrease in

efflux of K and influx of Na via non-selective cation channels due to decreased

membrane depolarization by NaCl in the presence of high Ca2+ concentration (Shabala et

al., 2006). In biopriming, endophytic bacteria enhances uptake of N, P and K thereby

increasing the K:Na ratio in plants under salinity (Dodd and Pérez-Alfocea, 2012). They

excrete exopolysaccharides which bind Na and decrease its uptake under salinity (Ashraf

et al., 2004). Moreover, it has been suggested that a greater proportion of root zone of

endophytic bacteria treated plants was covered with soil sheath that decrease the

apoplastic flow of Na+ into stele (Dodd and Pérez-Alfocea, 2012).

4.2.10. Water relations

4.2.10.1. Leaf relative water content

There was a significant effect of salinity and seed priming on leaf relative water

content; barley varieties also differed significantly, during both growing seasons.

Interaction between varieties and salinity was significant during 2014-15 but non-

significant during 2015-16. Whereas, the interactions between varieties and seed priming,

salinity and seed priming as well as three way interaction among varieties, salinity and

seed priming was significant, during both years (Table 4.85). Leaf relative water content

was proportionally decreased by salt stress relative to its severity. Haider-93 recorded

higher leaf relative water content than Frontier-87. Moreover, seed priming improved the

leaf relative water content in tested barley varieties at each level of salt stress, as

compared to unprimed control. Highest leaf relative water content was observed by

biopriming of Frontier-87 and Haider-93 under moderate salinity during 2014-15 and

2015-16 respectively. However, under severe salinity osmopriming of Haider-93 resulted

in highest leaf relative water content, during both growing seasons (Figures 4.12a,b).

4.2.10.2. Leaf water potential

Salt stress and seed priming significantly affected leaf water potential; the selected

varieties also differed significantly, during both growing seasons. However, the

134

interaction between varieties and seed priming was significant during 2014-15 but non-

significant during 2015-16. Whereas, the interactions between varieties and salinity,


priming was significant, during both years (Table 4.85). Leaf water potential was

decreased with increase in severity of salt stress. Haider-93 maintained higher leaf water

potential than Frontier-87. Leaf water potential of both varieties was improved by seed

priming treatments under all levels of salinity, as compared to unprimed control. Under

moderate salinity, maximum increase in leaf water potential was noticed by hydropriming

and osmopriming of Haider-93 during 2014-15 and 2015-16. Under severe salinity,

osmopriming and biopriming of Haider-93 led to maximum improvement in leaf water

potential during 2014-15 and 2015-16, respectively (Figures 4.12c,d).

4.2.10.3. Leaf osmotic potential

Salinity and seed priming significantly affected the leaf osmotic potential of

barley, during both growing seasons; while, the varieties significantly differed during

2014-15 but did not differ significantly during 2015-16. The interactions between

varieties and salinity, varieties and seed priming, salinity and seed priming, and three way

interaction among varieties, salinity and seed priming was significant, during both years

(Table 4.86). Salinity decreased the leaf osmotic potential and it was proportional to its

severity. Higher osmotic potential was exhibited by Haider-93 than Frontier-87. The

osmotic potential of both barley varieties were improved by seed priming treatments

under each level of salinity, as compared to unprimed control. Under moderate stress, the

greatest improvement in leaf osmotic potential was caused by osmopriming of Haider-93,

during both years. Under severe salinity, maximum leaf osmotic potential was observed

by biopriming of Haider-93, during both years. However, osmopriming of Haider-93

produced similar results for leaf osmotic potential under sever salt stress during 2014-15

(Figures 4.13a,b).

4.2.10.4. Leaf pressure potential

The leaf pressure potential was significantly affected by salinity, during both

growing seasons. However, there was a non-significant effect of seed priming on water

potential, during both years. Whereas, the varieties did not differ significant during 2014-

15 but differed significantly during 2015-16. The interaction between varieties and

salinity was significant, during both growing seasons. However, the interaction between

varieties and seed priming was non-significant during 2014-15 but significant during

2015-16; while, interaction between salinity and seed priming was non-significant, during 135

both growing seasons. Three way interaction among varieties, salinity and seed priming

was significant during 2014-15 but non-significant during 2015-16 (Table 4.86). Leaf

pressure

136

Table 4.85: Analysis of variance for the influence of seed priming on leaf relative water content and leaf water potential of barley under salinitySOV df Mean sum of square

Leaf relative water content Leaf water potential2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 225.40** 163.88** 5.694** 3.550**

Salinity (S) 2 8651.30** 10060.88** 41.225** 47.351**

Priming (T) 3 202.10** 97.11** 0.568* 5.157**

V×S 2 79.54** 0.49ns 1.154** 1.667*

V×T 3 16.85** 11.33* 0.279** 0.157ns

S×T 6 44.69** 14.93** 0.146* 0.414**

V×S×T 6 11.34* 29.99** 0.299** 0.410**

Error 72 2.59 2.44 0.063 0.077Total 95

Table 4.86: Analysis of variance for the influence of seed priming on leaf osmotic potential and leaf pressure potential of barley under salinitySOV df Mean sum of square

Leaf osmotic potential Leaf pressure potential2014-15 2015-16 2014-15 2015-16

Varieties (V) 1 7.069** 0.024ns 0.074ns 3.000**

Salinity (S) 2 82.650** 73.200** 8.005** 3.641**

Priming (T) 3 0.847** 5.896** 0.152ns 0.041ns

V×S 2 3.496* 0.137* 1.390* 0.917**

V×T 3 0.219* 0.511** 0.071ns 0.339*

S×T 6 0.092** 0.308** 0.061ns 0.109ns

V×S×T 6 0.088** 0.208* 0.544** 0.071ns

Error 72 0.014 0.018 0.068 0.074Total 95


137

Lea

f rel

ativ

e w

ater

con

tent

(%)

Lea

f wat

er p

oten

tial (

-MPa

)

138

Lea

f osm

otic

pot

entia

l (-M

Pa)

Lea

f pre

ssur

e po

tent

ial (

MPa

)

139

potential was proportionally decreased by salt stress relative to its severity. Haider-93

maintained higher pressure potential than Frontier-87. Moreover, seed priming improved

the leaf pressure potential of tested barley varieties at each level of salt stress, as

compared to unprimed control. The maximum improvement in leaf pressure potential was

caused by osmopriming of Haider-93 and hydropriming of Frontier-87 under moderate.

Whereas, under severe salinity, hydropriming of Haider-93 and biopriming of Frontier-87

caused greatest increase in leaf pressure potential during 2014-15 and 2015-16,

respectively (Figures 4.13c,d).

4.2.11. Discussion

Water relations were perturbed by salinity with increase in its severity; however,

seed priming improved the leaf relative water content, water potential, osmotic potential

and pressure potential in both varieties. However, Haider-93 better maintained tissue

water status which is attributed to greater accumulation of osmolytes. Salinity disturbs the

water relations of by osmotic stress; however, to cope with this situation plants produce

and accumulate osmolytes in greater amount for osmotic adjustment (Munns and Tester,

2008). In present study, improved water relations by seed priming might be due to better

root growth that enhanced water uptake from deeper layers of soil and osmotic

adjustment through enhanced accumulation of osmolytes due to increased gene

expression resulting from accumulation of transcription factors during priming induced

stress in the form of desiccation and osmotic stress (Chen and Arora, 2013). Moreover, in

osmopriming Ca2+ also serves as osmoticum that might also have added its beneficial role

in osmotic adjustment (White and Broadley, 2003). In biopriming, the endophytic

bacteria produce auxin which results in enhanced root growth of plants making the plants

capable for water uptake from deeper layers of soil (Santoyo et al., 2016). It has been

observed that treatment with auxin producing bacteria enhances root growth and water

uptake which aids to maintain better tissue water status under stressed conditions

(German et al., 2000; Vurukonda et al., 2016). Moreover, endophytic bacteria enhances

production and accumulation of osmolytes that maintain better water relations through

osmotic adjustment as observed in present study (Dimkpa et al., 2009).

4.2.12. Grain nutrient contents

4.2.12.1. Grain zinc content

The grain Zn content was significantly affected by salinity and seed priming;

varieties also differed for grain Zn content significantly, during both growing seasons.

The interaction between varieties and salinity was significant, during both years. 140

However, the interactions between varieties and seed priming, salinity and seed priming

and three way interaction among varieties, salinity and seed priming was non-significant,

during both years (Table 4.87). A reduction in grain Zn content was caused by salt stress

with greatest decrease occurring at severe salinity, as compared to control. Under both

moderate as well as severe salinity the variety Haider-93 exhibited higher grain Zn

content than Frontier-87, during both growing seasons (Tables 4.88a, 4.89a). Across

salinity and varieties the biopriming improved the grain Zn contents, as compared to

unprimed control (Tables 4.88b, 4.89b).

4.2.12.2. Grain manganese content

Grain Mn content was significantly affected by salinity and seed priming. Selected

barley varieties also significantly differed for grain Mn content, during both years. The

interaction between varieties and salinity was significant, during both years. However, the

interactions between varieties and seed priming, salinity and seed priming and three way

interaction among varieties, salinity and seed priming was non-significant, during both

growing seasons (Table 4.87). Grain Mn content was decreased by salt stress and least

Mn content was recorded at severe salinity, as compared to control (Table 2). Under

moderate stress, variety Haider-93 exhibited higher Mn content, during both years.

However, under severe salinity higher grain Mn content was observed in variety Haider-

93 during 2014-15 and in Frontier-87 during 2015-16 (Tables 4.90a, 4.91a). Across

salinity and varieties the grain Mn content was improved by biopriming, during both

growing seasons, as compared to unprimed control (Tables 4.90b, 4.91b).

4.2.12.3. Grain boron content

Salt stress and seed priming significantly affected grain B contents; barley

varieties also differed significantly, during both years. The interaction between varieties

and salinity was significant, during both years. However, the interactions between

varieties and seed priming, salinity and seed priming and three way interaction between

varieties, salinity and seed priming were non-significant, during both seasons (Table

4.87). Salinity decreased the grain B content as compared to control with maximum

decrease occurring at severe salinity (Table 2). Under moderate salinity, higher grain B

contents were recorded by Frontier-87 during 2014-15 while during 2015-16 higher B

contents were noticed in Haider-93. However, under severe salt stress higher grain B

content was exhibited by Haider-93, during both years (Tables 4.92a, 4.93a). Across

salinity and varieties the biopriming improved the grain B contents, as compared to

unprimed control, during both years (Tables 4.92b, 4.93b).141

4.2.13. Discussion

Salt stress caused a reduction in grain mineral nutrients contents in both varieties

relative to its increasing severity; however, Haider-93 accumulated more Zn, Mn and B in

its grains. Better grain nutrient contents in Haider-93 is attributed to well-maintained

tissue water status and cell membrane stability. Salt stress causes osmotic stress which

results in decreased water uptake with concomitant decrease in nutrient uptake by plants

(Marcelis and Hooijdonk, 1999). In present study, seed priming treatments improved the

grain nutrient contents under salt stress. There was significant increase in grain mineral

nutrients contents by biopriming which might be due to solubilization of nutrients in soil

by producing extra cellular enzymes and siderophores, and through improved root growth

due to production of growth promoting phytohormones and decrease in ethylene synthesis

(Miliute et al., 2015; Vurukonda et al., 2016). In present study, biopriming improved

water relations in both varieties which might have caused enhanced translocation and

accumulation of nutrients in grains. Similar results were reported by Rana et al. (2012)

that inoculation of wheat with Bacillus sp., Providencia sp. and Brevundimonas sp.

increased Zn, Mn, Cu and Fe uptake and accumulation in wheat grains.

142

Table 4.87: Analysis of variance for the influence of seed priming on grain mineral contents of barley under salinitySOV df Mean sum of square

Seed zinc content Seed manganese content

Seed boron content

2014-15 2015-16 2014-15 2015-16 2014-15 2015-16Varieties (V) 1 72.77** 75.63** 1522.11** 441.27** 0.288** 0.232**

Salinity (S) 2 553.44** 807.85** 6622.35** 10426.41** 1.180** 1.448**

Priming (T) 3 49.58** 50.50** 608.86** 529.01** 0.113** 0.093**

V×S 2 14.86* 18.08** 152.67* 240.11** 0.114** 0.040*

V×T 3 1.67ns 1.39ns 28.71ns 20.27ns 0.006ns 0.002ns

S×T 6 6.92ns 6.73ns 101.14ns 26.54ns 0.012ns 0.017ns

V×S×T 6 4.00ns 2.02ns 20.07ns 24.76ns 0.004ns 0.001ns

Error 72 3.32 3.13 46.50 20.64 0.006 0.009Total 95


Table 44.88a: Influence of seed priming on grain zinc content (µg g -1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanH-93 40.29 a 36.32 bc 31.00 d 35.87 AF-87 36.98 b 35.47 c 29.93 d 34.13 BMean 38.64 A 35.89 B 30.47 C

Varieties LSD≤0.05 = 0.7409, Salinity LSD≤0.05 = 0.9074, Varieties × Salinity LSD≤0.05 = 1.2833

Table 4.88b: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanControl 37.76 34.47 29.19 33.80 CHP 38.25 35.64 30.82 34.90 BOP 36.64 36.00 30.08 34.24 BCBP 41.91 37.46 31.77 37.05 AMean 38.64 A 35.89 B 30.47 C

Salinity LSD≤0.05 = 0.9074, Seed priming LSD≤0.05 = 1.0478

Table 4.89a: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanH-93 41.66 a 37.04 bc 30.73 d 36.48 AF-87 38.20 b 36.47 c 29.44 e 34.70 BMean 39.93 A 36.75 B 30.08 C

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties LSD≤0.05 = 0.7202, Salinity LSD≤0.05 = 0.8821, Varieties × Salinity LSD≤0.05 = 1.2474

143

Table 4.89b: Influence of seed priming on grain zinc content (µg g-1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanControl 38.79 35.59 29.05 34.48 CHP 40.70 36.21 30.20 35.70 BOP 37.49 36.58 29.65 34.58 CBP 42.73 38.63 31.43 37.60 AMean 39.93 A 36.75 B 30.08 C


Table 4.90a: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanH-93 127.45 a 123.18 ab 97.69 d 116.11 AF-87 119.35 b 110.92 c 94.16 d 108.14 BMean 123.40 A 117.05 B 95.92 C


Table 4.90b: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanControl 121.81 111.36 91.22 108.13 CHP 121.60 120.47 96.71 112.93 BOP 115.88 113.93 95.70 108.50 CBP 134.31 122.44 100.05 118.94 AMean 123.40 A 117.05 B 95.92 C


Table 4.91a: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanH-93 124.92 a 113.96 c 86.53 e 108.47 AF-87 120.82 b 104.11 d 87.62 e 104.18 BMean 122.87 A 109.04 B 87.08 C


Table 4.91b: Influence of seed priming on grain manganese content (µg g -1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanControl 119.25 104.34 83.64 102.41 CHP 121.06 107.90 87.22 105.39 BOP 119.05 108.16 85.96 104.39 BCBP 132.12 115.75 91.49 113.12 AMean 122.87 A 109.04 B 87.08 C

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Salinity LSD≤0.05 = 2.2643, Seed priming LSD≤0.05 = 2.6146

144

Table 4.92a: Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanH-93 1.95 a 1.70 c 1.61 d 1.75 AF-87 1.82 b 1.72 c 1.39 e 1.64 BMean 1.88 A 1.71 B 1.50 C


Table 4.92b: Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2014-15)Treatments Control Moderate salinity Severe salinity MeanControl 1.85 1.64 1.43 1.64 CHP 1.86 1.73 1.49 1.69 BOP 1.81 1.68 1.51 1.67 BCBP 2.02 1.80 1.57 1.80 AMean 1.88 A 1.71 B 1.50 C


Table 4.93a: Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanH-93 1.96 a 1.69 c 1.51 d 1.72 AF-87 1.80 b 1.67 c 1.40 e 1.62 BMean 1.88 A 1.68 B 1.45 C


Table 4.93b: Influence of seed priming on grain boron content (µg g-1 DW) of barley under salinity (2015-16)Treatments Control Moderate salinity Severe salinity MeanControl 1.85 1.58 1.39 1.60 CHP 1.88 1.73 1.42 1.67 BOP 1.81 1.66 1.49 1.65 BCBP 1.99 1.75 1.53 1.75 AMean 1.88 A 1.68 B 1.45 C

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Salinity LSD≤0.05 = 0.0463, Seed priming LSD≤0.05 = 0.0534

145

4.3. Influence of seed priming in improving the resistance against osmotic and salt stresses in barley4.3.1. Seedling growth

Osmotic stress and seed priming significantly affected shoot and root length, and

fresh and dry weights of barley seedlings; the tested varieties of barley also differed

significantly for seedling growth traits except shoot length and root dry weight. The

interaction between varieties and osmotic stress was significant for shoot length, shoot

fresh weight, root fresh weight and shoot dry weight while, non-significant for root length

and root dry weight. Interaction between varieties and seed priming was significant for all

seedling growth traits except shoot fresh weight. However, the interaction between

osmotic stress and seed priming, and three way interaction among varieties, osmotic

stress and seed priming were significant for all studied seedling growth traits (Table

4.94).

Seedling growth was decreased by both osmotic stress (PEG-8000) and salt stress

(NaCl salt), as compared to control. Salt stress caused greater reduction in seedling

growth of both varieties as compared to osmotic stress. The varieties showed a

differential response to osmotic and salt stress regarding seedling growth traits. The

deleterious effects of osmotic stress on root growth were greater in Frontier-87 while for

shoot growth more reductions were observed in Haider-93. However, salt stress imposed

more negative effects on both root and shoot growth traits of Frontier-87 than Haider-93.

Seed priming improved the seedling growth of both varieties under stressed conditions, as

compared to unprimed control. Under osmotic stress, maximum increase in shoot length,

root length, shoot dry weight, and root fresh and dry weights was caused by biopriming of

Haider-93; while, shoot fresh weight was improved most by osmopriming of Frontier-87.

Under salt stress, maximum increase in shoot length, root length, shoot and root fresh and

dry weights was caused by osmopriming of Haider-93 (Figures 4.14a-c, 4.15a-c).


Chlorophyll a and b contents were significantly affected by osmotic stress and

seed priming; while, barley varieties also differed significantly for chlorophyll a and b

contents. The interaction between varieties and osmotic stress was significant for

chlorophyll a and b contents. However, interactive effects of varieties and seed priming,

and osmotic stress and seed priming were significant for chlorophyll a content while non-

significant for chlorophyll b content. The three way interaction among varieties, osmotic

stress and seed priming was significant for both chlorophyll a and b contents (Table

146

4.95). Osmotic and salt stress decreased the chlorophyll a and b contents in both varieties,

as compared to control. However, both osmotic and salt stresses were equally deleterious

for Haider-93 but salt stress was more deleterious for Frontier-87 than osmotic stress

regarding chlorophyll a and b contents. Seed priming improved the chlorophyll contents

in both varieties under osmotic as well as salt stress, as compared to unprimed control.

Under osmotic stress, maximum increase in chlorophyll a and b contents was caused by

biopriming of Haider-93. Under salts stress, chlorophyll a and b contents were increased

most by biopriming and osmopriming of Haider-93, respectively (Figures 4.16a,b).


Osmotic stress and seed priming significantly affected total soluble phenolics,

total soluble proteins, proline and glycine contents; tested barley varieties also differed

significantly for all studied osmolytes. The interaction between varieties and seed priming

was non-significant for all studied osmolytes. The interactions between varieties and

osmotic stress, osmotic stress and seed priming, and three way interaction among

varieties, osmotic stress and seed priming was significant for all studied osmolytes

(Tables 4.95, 4.96).

Osmotic and slat stresses increased the production and accumulation of osmolytes

in both barley varieties, as compared to control. However, accumulation of total soluble

phenolics, total soluble proteins, proline and glycine contents was greater under osmotic

stress in both varieties than salt stress. Moreover, the varieties differed in osmolytes

accumulation under osmotic and salt stress. Osmolytes accumulation in both varieties was

similar under osmotic stress, however, under salt stress Haider-93 accumulated more

osmolytes than Frontier-87. Seed priming further increased the accumulation of

osmolytes under stressed conditions, as compared to unprimed control. Under osmotic

stress, total soluble phenolics, total soluble proteins and glycine betaine contents were

enhanced most by biopriming of Haider-93, while, proline content was exalted by

osmopriming of Haider-93. Under salt stress, biopriming of Frontier-87 and Haider-93

caused maximum increase in accumulation of total soluble phenolics and proline,

respectively. However, maximum increase in total soluble proteins and glycine betaine

contents was caused by osmopriming of Haider-93 (Figures 4.16c, 4.17a-c).

4.3.4. Lipid peroxidation and sodium accumulation

Osmotic stress and seed priming significantly affected MDA and Na contents.

Varieties also differed significantly for MDA and Na accumulation. The interactions

between varieties and osmotic stress, and osmotic stress and seed priming were non-147

significant for MDA while significant for Na content. However, interaction between

varieties and seed priming was significant for MDA but non-significant for Na content.

The three way interaction among varieties, osmotic stress and seed priming was

significant for both MDA and Na contents (Table 4.97). Osmotic and salt stress

substantially increased the accumulation of MDA, while Na content was increased by

NaCl salt stress in both varieties, as compared to control. The MDA accumulation was

greater under salt stress than osmotic stress. Moreover, greater MDA and Na was

accumulated in Frontier-87 than Haider-93 under stressed conditions. Seed priming

caused a reduction in MDA and Na accumulation in both varieties under osmotic as well

as salt stress, as compared to unprimed control. Under osmotic stress, biopriming of

Haider-93 decreased the MDA content most. However, under salt stress, osmopriming of

Haider-93 caused maximum decrease in MDA and Na accumulation (Figures 4.18a,b).

4.3.5. Discussion

Osmotic and salt stress caused a reduction in seedling growth and biomass

production of both barley varieties. However, seed priming improved the growth and

stress tolerance of barley varieties under both PEG-8000 induced osmotic stress and NaCl

salt stress. Nonetheless, growth improvement was more pronounced under salt stress and

it was associated with better chlorophyll contents, greater accumulation of osmolytes and

decreased MDA accumulation. The improved plant growth and stress tolerance by

osmopriming might be due to up-regulation of gene expression for osmolytes (Kubala et

al., 2015), antioxidants (Souza et al., 2016), dehydrin like proteins (Chen et al., 2012),

aquaporins (Chen et al., 2013b), and improved water relations (Tabassum et al., 2017),

chloroplast ultrastructure (Dai et al., 2017) and chlorophyll photochemistry (Kubala et

al., 2015), while decreased ROS activity and lipid peroxidation (Zhang et al., 2015).

Moreover, Ca2+ used in osmopriming, acts as a secondary messenger, enhances gene

expression for osmolytes, regulates calmodulin like proteins in signaling pathways that

trigger various growth mechanisms and protect plants from stresses (White and Broadley,

2003; Sarwat et al., 2013).

In present study, biopriming improved the plant growth, chlorophyll contents and

accumulation of phenolics, total soluble proteins, proline and glycine betaine under

stressed conditions. The endophytic bacteria in bioprimed plants may have improved

plant growth and development under stressed conditions by enhancing the production of

plant growth promoting hormones viz. auxins, cytokinins and gibberellic acid while

decreasing ethylene production by producing ACC deaminase enzyme which improved 148

the chlorophyll contents and induced stay green character in plants (Mahmood et al.,

2016). Improved stress tolerance by endophytic bacteria in bioprimed plants is associated

with enhanced osmolytes accumulation, antioxidants activity, nutrient uptake and

carbohydrates metabolism (Dimkpa et al., 2009; Chakraborty et al., 2011). Moreover,

endophytic bacteria improves the osmolytes and stress related metabolites by placing the

plants in primed condition that rapidly trigger the expression for osmolytes and stress

related genes expression on exposure to stress (Miliute et al., 2015; Miotto-Vilanova et

al., 2016). In present study, enhanced accumulation and activity of osmolytes by

endophytic bacteria in bioprimed plants decreased the lipid peroxidation by ROS and

improved plant growth and development which is in accordance with Montalbán et al.

(2017).

In present study, seed priming enhanced the accumulation of phenolics, total

soluble proteins, proline and glycine betaine under both PEG-8000 and NaCl induced

osmotic stress that conferred a decrease in lipid peroxidation, and improved chlorophyll

and plant growth of barley. The phenolics accumulation is increased in plants under

stressed conditions and it is associated with improved stress tolerance (Anjum et al.,

2017c). Phenolics protect the plants from ROS (Shetty et al., 2001) and stabilizes cellular

membranes due to the presence of aromatic ring having one or more hydroxyl groups in

their structure (Bhattacharya et al., 2010; Taiz et al., 2015). The soluble proteins protect

the cellular membranes, organelles and organic molecules from oxidative damage by

ROS and enhance hydration of cell structures (Arafa et al., 2009; Wahid and Close,

2007). Moreover, the stress proteins are involved in transport and protection of cell

proteins and repair of damaged proteins (Wahid et al., 2007). The accumulation of proline

and glycine betaine in plants is exalted under stressed conditions to enhance the plant

growth and stress tolerance ability by scavenging and quenching the ROS with

concomitant decrease in MDA accumulation, well maintained cell membrane stability

(Anjum et al., 2017c), and improved tissue water status trough osmotic adjustment (Song

et al., 2017; Tabassum et al., 2017).

The Na accumulation in leaves of both barley varieties was exaggerated under

NaCl salt stress; however, seed priming caused a significant reduction in Na

accumulation, as compared to unprimed control. Although PEG-8000 and NaCl induced

stresses decreased growth of barley but there was no pronounced difference in growth

reduction either by PEG-8000 or NaCl salt stress. However, decreased Na accumulation

and more pronounced growth improvement by seed priming under salt stress indicates 149

that aside form osmotic stress the ionic stress was also responsible for growth reduction in

plants exposed to salt stress. Osmopriming causes a reduction in Na uptake and

accumulation in plants by up-regulating the genes for high affinity potassium transporter

protein 1 (HAK1) and the salt overly sensitive 1 (SOS 1) antiporter (Souza et al., 2016).

Moreover, extracellular Ca2+, used in osmopriming in this study, decreases influx of Na

and efflux of K via non-selective cation channels due to less membrane depolarization by

NaCl in the presence of high Ca2+ concentration (Shabala et al., 2006). In present study

decreased Na content by biopriming is attributed to the endophytic bacteria which reduces

Na uptake by excreting the exopolysaccharides that bind Na and prevent its uptake under

salt stress (Ashraf et al., 2004). Moreover, they enhance the uptake of N, P and K thus

increase the K:Na ratio in salt stressed plants (Dodd and Pérez-Alfocea, 2012).

150

Table 4.94: Analysis of variance for the influence of seed priming on seedling growth of barley under osmotic and salt stressSOV df Mean sum of square

Shoot length

Root length

Shoot fresh

weight

Root fresh

weight

Shoot dry

weight

Root dry

weightVarieties (V) 1 0.20ns 199.96** 61075** 7311* 635** 253ns

Osmotic stress (O) 2 1135.71** 2167.50** 4399939** 1342194** 57825* 11889**

Seed priming (T) 3 121.79** 197.10** 732617** 298075** 25183** 3081**

V×O 2 9.59** 2.74ns 30856** 42206** 890** 21ns

V×T 3 6.69** 12.17** 11988ns 22464** 851* 307*

O×T 6 23.82** 22.35** 92932** 31821** 5743** 1110**

V×O×T 6 40.07** 10.35** 28759** 10099** 1679** 612**

Error 72 1.61 1.73 4953 1123 69 88Total 95

Table 4.95: Analysis of variance for the influence of seed priming on chlorophyll and total soluble phenolics contents in barley under osmotic and salt stressSOV df Mean sum of square

Chlorophyll a content

Chlorophyll b content

Total soluble phenolics

Varieties (V) 1 0.0088** 0.0006* 2546.3**

Osmotic stress (O) 2 0.1352** 0.0297** 21157.5**

Seed priming (T) 3 0.0114** 0.0046** 10446.2**

V×O 2 0.0009* 0.0008** 208.9*

V×T 3 0.0017** 0.0001ns 40.0ns

O×T 6 0.0014** 0.0001ns 1311.2**

V×O×T 6 0.0014** 0.0005** 532.8**

Error 72 0.0003 0.0001 62.6Total 95


151

Shoo

t len

gth

(cm

)R

oot l

engt

h (c

m)

Shoo

t fre

sh w

eigh

t (m

g)

152

Roo

t fre

sh w

eigh

t (m

g)Sh

oot d

ry w

eigh

t (m

g)R

oot d

ry w

eigh

t (m

g)

153

Chl

orop

hyll

a co

nten

t (m

g g-1

FW

)C

hlor

ophy

ll b

cont

ent (

mg

g-1 F

W)

Tot

al so

lubl

e ph

enol

ics (

µg g

-1 F

W)

154

Table 4.96: Analysis of variance for the influence of seed priming on osmolytes accumulation in barley under osmotic and salt stressSOV df Mean sum of square

Total soluble proteins

Free proline content

Glycine betaine content

Varieties (V) 1 0.0065** 0.0067** 0.0028*

Osmotic stress (O) 2 0.5102** 0.0440** 0.3887**

Seed priming (T) 3 0.0381** 0.0213** 0.0287**

V×O 2 0.0029** 0.0093** 0.0028*

V×T 3 0.0006ns 0.0004ns 0.0005ns

O×T 6 0.0018** 0.0009* 0.0019**

V×O×T 6 0.0023** 0.0023** 0.0027**

Error 72 0.0005 0.0003 0.0006Total 95

Table 4.97: Analysis of variance for the influence of seed priming on malondialdehyde and Na contents in barley under osmotic and salt stressSOV df Mean sum of square

Malondialdehyde Na contentVarieties (V) 1 293.61** 7340*

Osmotic stress (O) 2 3145.24** 24376762**

Seed priming (T) 3 83.49** 26542**

V×O 2 2.45ns 7757**

V×T 3 50.92** 2749ns

O×T 6 11.16ns 23927**

V×O×T 6 46.89** 2934*

Error 72 9.29 1259Total 95


155

Tot

al so

lubl

e pr

otei

ns (m

g g-1

FW

)Fr

ee p

rolin

e (µ

mol

g-1

FW )

Gly

cine

bet

aine

(µm

ol g

-1 FW

)

156

Mal

ondi

alde

hyde

(µm

ol g

-1 FW

)N

a co

nten

t (m

g g-1

DW

)

157

4.4. Influence of seed priming in improving the resistance against cadmium stress in barley4.4.1. Seedling growth

Cadmium stress and seed priming significantly affected shoot and root length,

shoot and root fresh weight, and shoot and root dry weight. The tested barley varieties

significantly differed for root length, shoot fresh weight, and shoot dry weight; however,

did not differ significantly for root and shoot fresh weight, and root dry weight. Likewise,

the interaction between varieties and Cd stress was significant for shoot and root length,

shoot and root fresh weight, and root dry weight while non-significant for shoot dry

weight. The interactions between varieties and seed priming, and Cd stress and seed

priming was non-significant for shoot length while significant for root length, shoot and

root fresh weight, and shoot and root dry weight. However, three interaction among

varieties, Cd stress and seed priming was significant for shoot and root length, shoot and

root fresh weight as well as shoot and root dry weight (Table 4.98).

Seedling growth of barley was decreased by Cd toxicity stress, as compared to

control. The reduction in seedling growth was increased with severity of Cd stress in both

varieties. However, Frontier-87 showed more tolerance to Cd under moderate stress while

Haider-93 performed better under severe stress. Seed priming treatments improved the

seedling growth of both barley varieties under all levels of Cd stress, as compared to

control. Under moderate Cd stress, biopriming of Haider-93 caused maximum increase in

shoot length, and shoot fresh and dry weights. However, root length, root fresh and dry

weights were improved most by osmopriming of Haider-93. Under severe Cd stress,

maximum increase in shoot length occurred by biopriming of Frontier-87, while,

maximum increase in shoot fresh and dry weights was caused by osmopriming of Haider-

93. Nonetheless, biopriming of Haider-93 caused greatest improvement in root length,

and root fresh and dry weights (Figures 4.19a-c, 4.20a-c).


The chlorophyll a and b contents were significantly affected by Cd stress and seed

priming. The varieties significantly differed for chlorophyll a content while did not differ

significantly for chlorophyll b content. However, the interactions between varieties and

Cd stress, and varieties and seed priming were non-significant for both chlorophyll a and

b contents. The interaction between Cd stress and seed priming was non-significant for

chlorophyll a but significant for chlorophyll b content. The there way interaction among

varieties, Cd stress and seed priming was significant for chlorophyll a and b contents

158

(Table 4.99). A substantial reduction in chlorophyll a and b contents of barley was caused

by Cd stress, as compared to control. The decrease in chlorophyll contents was increased

with increase in Cd stress levels. However, greater reductions occurred in Fronteirs-87

under each level of Cd stress. Seed priming improved the chlorophyll a and b contents in

both varieties under Cd stress, as compared to control. Under moderate Cd stress,

biopriming of Haider-93 exhibited greatest improvement in chlorophyll a and b contents.

However, under severe Cd stress, maximum increase in chlorophyll a and b contents was

caused by osmopriming of Haider-93 (Figures 4.21a,b).


The total soluble phenolics, total soluble proteins, free proline and glycine betaine

contents were significantly affected by Cd stress and seed priming. However, varieties

significantly differed for total soluble phenolics and total soluble proteins while did not

differ significantly for free proline and glycine betaine contents. Significant interactions

between varieties and Cd stress, and varieties and seed priming occurred for total soluble

proteins while were non-significant for total soluble phenolics, proline and glycine

betaine contents. Nonetheless, interaction between Cd stress and seed priming as well as

three way interaction among varieties, Cd stress and seed priming were significant for

total soluble phenolics, total soluble proteins, free proline and glycine betaine contents

(Tables 4.99, 4.100).

Osmolytes accumulation was increased by Cd stress in both barley varieties, as

compared to control. The osmolytes accumulation was increased with increase in stress

severity. Haider-93 accumulated more osmolytes than Frontier-87. Seed priming

treatments further improved the accumulation of osmolytes in both varieties under all

levels of Cd stress, as compared to control. Under moderate Cd stress, total soluble

phenolics and glycine betaine contents were exalted most by biopriming of Haider-93,

while, maximum increase in total soluble proteins and proline contents was caused by

osmopriming of Haider-93. Under severe Cd stress, the greatest increase in total soluble

phenolics, total soluble proteins and glycine betaine contents was occurred by

osmopriming of Haider-93; however, the influence of biopriming of Haider-93 on glycine

betaine content was at par with osmopriming of Haider-93. Proline content was improved

most by osmopriming of Frontier-87 (Figures 4.21a, 4.22a-c).

4.4.4. Lipid peroxidation and cadmium content

Accumulation of MDA and Cd was significantly affected by Cd toxicity and seed

priming; the varieties also differed significantly for MDA and Cd contents. The 159

interaction between varieties and Cd stress was ssignificant for both MDA and Cd

contents. However, the interaction between varieties and seed priming was significant for

seed priming while non-significant for Cd content. Intercation between Cd stress and seed

priming was non-significant for MDA but significant for Cd content. The three way

interation among varieties, Cd stress and seed priming was significant for both MDA and

Cd contents (Table 4.101). Accumulation of MDA and Cd in barley varieties was

aggravated by Cd stress, as compared to control. The MDA and Cd accumulation was

increased with increase in Cd stress levels (severe > moderate > control). However,

Haider-93 accumulated less MDA as well as Cd than Frontier-87. Moreover, seed

priming decreased the accumulation of MDA and Cd in both varieties under Cd stress, as

compared to control. Under moderate Cd stress, least MDA and Cd accumulation

occurred by biopriming of Haider-93 while under severe stress osmopriming of Haider-93

was superior in decreasing the MDA as well as Cd accumulation (Figures 4.23a,b).

4.4.5. Discussion

Cadmium stress caused a reduction in seedling growth and biomass production in

both barley varieties and the decrease was proportional to the stress severity. Nonetheless,

seed priming improved stress tolerance by improving leaf chlorophyll contents,

accumulation of phenolics, total soluble proteins, proline and glycine betaine, while

reducing MDA and Cd contents as indicated by improved seedling growth of barley, as

compared to control. This might be attributed to enhanced accumulation of transcription

factors and metabolites that trigger the gene expression for osmolytes, heat shock proteins

and antioxidants (Kibinza et al., 2011; Chen and Arora, 2013), which reduces ROS

activity, lipid peroxidation and improves water relations ultimately improving the plant

growth and stress tolerance (Chen and Arora, 2013; Tabassum et al., 2017). In present

study, the Ca2+ used in osmopriming, acts as a secondary messenger that enhances gene

expression for osmolytes accumulation (White and Broadley, 2003). Moreover, Ca2+ acts

in the signaling pathways and regulates the calmodulin like proteins to trigger various

growth mechanisms and protect plants from damaging effects of stress (Sarwat et al.,

2013).

In present study, the biopriming was effective in improving the seedling growth

and stress tolerance of barley through enhanced chlorophyll contents and osmolytes

accumulation. This might be due to endophytic plant growth promoting bacteria used in

biopriming that improves the plant growth by modulating the production of

phytohormones i.e. increasing auxin, cytokinins and gibberellic acid while decreasing the 160

ethylene production by producing ACC deaminase enzyme (Miliute et al., 2015; Santoyo

et al., 2016). Moreover, endophytic bacteria place the metabolism of plants in primed

state that enable greater and rapid accumulation of transcription factors for osmolytes and

stress related genes expression (Theocharis et al., 2012; Miotto-Vilanova et al., 2016).

Endophytic bacteria also produce osmolytes that act synergistically with plant produced

osmolytes under stressed conditions (Dimkpa et al., 2009) which decrease the lipid

peroxidation by ROS activity and improve the plant growth and development (Theocharis

et al., 2012; Montalbán et al., 2017).

In present study, the seed priming increased soluble phenolics and proteins

accumulation which resulted in decreased MDA accumulation, and increased chlorophyll

contents and seedling growth, as compared to unprimed control, under Cd toxicity. The

soluble phenolics contain aromatic ring in their structures which might have protected and

stabilized cellular membranes under stressed conditions (Taiz et al., 2015), enhanced

ROS scavenging in cells (Shetty et al. 2001), and improved the stress tolerance and plant

growth. Likewise, soluble proteins protect the biological membranes and cellular

organelles from oxidative damage to lipids, proteins and nucleic acid (Arafa et al., 2009),

which improves stress tolerance by hydration of cellular structures (Wahid and Close,

2007). In current study, free leaf proline and glycine betaine contents were increased in

barley by seed priming under Cd toxicity stress which are associated with decrease in

MDA accumulation, improved cell membrane stability (Anjum et al., 2017c); moreover,

they improve water relations by osmotic adjustment (Tabassum et al., 2017), ultimately

improving the plant growth and development under stressed conditions (Song et al.,

2017).

Cadmium content in barley was increased with increase in Cd toxicity; however,

seed priming ameliorated the effects of Cd toxicity on plant growth by decreasing the Cd

contents. In osmoprimed plants, Ca2+ might have decreased Cd concentration in barley

due to restricted uptake and/or translocation to aerial plant parts (Abd_Allah et al., 2017).

The Ca+2 also improves the uptake of K while decreases Cd uptake resulting in decreased

Cd contents in plants under Cd toxicity (Kurtyka et al. 2008). However, decrease in Cd

content in bioprimed barley plants could be due to adsorption and immobilization of toxic

ions from solution by endophytic bacteria through production of extracellular proteins

and polysaccharides which can bind and precipitate the metals ions (Burd et al., 1998). In

this way, the endophytic bacteria may have reduced toxic effects of Cd by improving the

growth and dry biomass of host plant (Montalbán et al., 2017).161

Table 4.98: Analysis of variance for the influence of seed priming on seedling growth of barley under cadmium stressSOV df Mean sum of square

Shoot length

Root length

Shoot fresh

weight

Root fresh

weight

Shoot dry

weight

Root dry

weightVarieties (V) 1 0.04ns 65.21* 7030* 70ns 8470.7** 10.0ns

Cadmium stress (C) 2 381.96** 1200.43** 7209818** 667839** 13339.1** 1568.8**

Seed priming (T) 3 18.98** 203.38** 362979** 260575** 4098.7** 477.5**

V×C 2 76.99** 39.67* 6048* 90552** 88.2ns 192.5**

V×T 3 8.59ns 58.42** 5832* 19127** 399.2** 51.0**

C×T 6 8.74ns 182.40** 76073** 56896** 181.3** 116.9**

V×C×T 6 17.34** 28.61* 48060** 39968** 294.5** 68.5**

Error 72 4.24 10.31 1517 799 41.3 2.6Total 95

Table 4.99: Analysis of variance for the influence of seed priming on chlorophyll and total soluble phenolics contents in barley under cadmium stressSOV df Mean sum of square

Chlorophyll a content

Chlorophyll b content

Total soluble phenolics

Varieties (V) 1 0.0201** 0.0001ns 1319.8**

Cadmium stress (C) 2 0.1019** 0.0314** 17076.3**

Seed riming (T) 3 0.0083** 0.0042** 5774.1**

V×C 2 0.0002ns 0.0002ns 19.3ns

V×T 3 0.0002ns 0.0001ns 111.3ns

C×T 6 0.0002ns 0.0002* 109.7*

V×C×T 6 0.0004* 0.0003* 126.9*

Error 72 0.0002 0.0001 45.9Total 95


162

Shoo

t len

gth

(cm

)R

oot l

engt

h (c

m)

Shoo

t fre

sh w

eigh

t (m

g)

163

Roo

t fre

sh w

eigh

t (m

g)Sh

oot d

ry w

eigh

t (m

g)R

oot d

ry w

eigh

t (m

g)

164

Chl

orop

hyll

a co

nten

t (m

g g-1

FW

)C

hlor

ophy

ll b

cont

ent (

mg

g-1 F

W)

Tot

al so

lubl

e ph

enol

ics (

µg g

-1 F

W)

165

Table 4.100: Analysis of variance for the influence of seed priming on osmolytes accumulation in barley under cadmium stressSOV df Mean sum of square

Total soluble proteins

Free proline content

Glycine betaine content

Varieties (V) 1 0.0035** 0.0011ns 0.0001ns

Cadmium stress (C) 2 0.8827** 0.6065** 0.8822**

Seed priming (T) 3 0.0501** 0.0282** 0.0533**

V×C 2 0.0047** 0.0021ns 0.0008ns

V×T 3 0.0016* 0.0012ns 0.0013ns

C×T 6 0.0029** 0.0034** 0.0015*

V×C×T 6 0.0011* 0.0036** 0.0022**

Error 72 0.0004 0.0007 0.0007Total 95

Table 4.101: Analysis of variance for the influence of seed priming on malondialdehyde and cadmium contents in barley under cadmium stressSOV df Mean sum of square

Malondialdehyde Cadmium contentVarieties (V) 1 53.97** 2372.2**

Cadmium stress (C) 2 5654.79** 195715.9**

Seed priming (T) 3 61.65** 1113.1**

V×C 2 25.47* 545.3**

V×T 3 19.96* 76.3ns

C×T 6 11.35ns 325.5**

V×C×T 6 26.06** 99.8*

Error 72 5.81 41.2Total 95


166

Tot

al so

lubl

e pr

otei

ns (m

g g-1

FW

)Fr

ee p

rolin

e (µ

mol

g-1

FW )

Gly

cine

bet

aine

(µm

ol g

-1 FW

)

167

Mal

ondi

alde

hyde

(µm

ol g

-1 FW

)C

d co

nten

t (µg

g-1

DW

)

168

4.5. Influence of seed priming in improving the resistance against terminal heat stress in barley4.5.1. Stand establishment

Seed priming significantly affected final emergence percentage, time taken to

50% emergence, mean emergence time and emergence index of barley (Table 4.102).

Final emergence percentage and emergence index were increased while time taken to

50% emergence and mean emergence time of barley was decreased by seed priming, as

compared to unprimed control. Maximum improvement was caused by osmopriming and

it was followed by hydropriming (Table 4.103).


Heat stress and seed priming significantly affected plant height, number of

productive tillers, spike length, number of spikelets and grains per spike, 100-grain

weight, grain and biological yield, and harvest index of barley (Table 4.104, 4.107).

However, interaction between heat stress and seed priming was non-significant for plant

height, number of productive tillers, spike length, number of spikelets per spike and

biological yield; while, significant for number of grains per spike, 100-grain weight, grain

yield and harvest index of barley (Table 4.104, 4.107). Heat stress caused a reduction in

plant height, number of productive tillers, spike length, number of spikelets and grains per

spike, 100-grain weight, grain and biological yield, and harvest index of barley, as

compared to control. However, seed priming treatments improved all these traits, as

compared to unprimed control, and hydropriming was most effective followed by

osmopriming (Tables 4.105, 4.106, 4.108-4.110). Furthermore, the greatest improvement

in number of grains per spike, 100-grain weight and harvest index was caused by

hydropriming and osmopriming at normal temperature and under heat stress, respectively,

as compared to unprimed control (Tables 4.105, 4.106, 4.108-4.110).

4.5.3. Gas exchange attributes

Photosynthesis, stomatal conductance, transpiration, internal CO2 concentration

and stomatal limitation were significantly affected by terminal heat stress at 7 and 14

DAT. However, CUE was not significantly affected at 7 DAT but significantly affected at

14 DAT by heat stress. Seed priming significantly affected photosynthesis and CUE at 7

as well as 14 DAT, while transpiration was significantly affected at 7 DAT only.

Nonetheless, stomatal conductance, stomatal limitation and intercellular CO2

concentration were not affected significantly by seed priming. Interaction of heat stress

169

and seed priming was significant for photosynthesis, transpiration and CUE at both 7 and

14 DAT; while,

170

Table 4.102: Analysis of variance for the influence of seed priming on emergence of barley SOV df Final

emergence percentage

Mean emergence time

Time taken to 50% emergence

Emergence index

Seed priming (T) 2 324.06* 0.594* 0.819* 0.123*

Error 15 67.88 0.128 0.162 0.010Total 17

SOV = Source of variation, df = Degree of freedom, * = Significant at p≤0.05

Table 4.103: Influence of seed priming on emergence attributes of barleyTreatments Final emergence

percentage (%)Mean emergence

time (days)Time taken to 50% emergence (days)

Emergence index

Control 58.34 b 5.29 a 4.71 a 0.68 bHP 69.45 a 4.88 ab 4.14 b 0.89 aOP 72.22 a 4.68 b 4.02 b 0.95 aLSD≤ 0.05 10.139 0.4405 0.4954 0.1229

Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming

Table 4.104: Analysis of variance for the influence of seed priming on growth and yield related traits of barley under terminal heat stressSOV df Plant height No. of

productive tillers

Spike length No. of spikelets per

spikeHeat (H) 1 211.27** 61.361** 1.217* 3.373*

Seed priming (T) 2 88.83* 1.083* 2.170** 11.820**

H×T 2 1.21ns 0.361ns 0.149ns 1.079ns

Error 30 20.56 0.283 0.277 0.700Total 35


Table 4.105: Influence of seed priming on plant height and number of productive tillers per pot of barley under terminal heat stressTreatments Plant height (cm) No. of productive tillers per pot

Control Heat Mean Control Heat MeanControl 49.92 45.23 47.57 B 4.67 2.17 3.42 BHP 54.94 50.63 52.78 A 5.50 2.50 4.00 AOP 54.30 48.76 51.53 A 5.00 2.67 3.83 ABMean 53.05 A 48.21 B 5.06 A 2.44 B

LSD≤ 0.05Heat stress = 3.0869, Seed priming = 3.7807

Heat stress = 0.3624, Seed priming = 0.4438


171

Table 4.106: Influence of seed priming on spike length and number of spikelets per spike of barley under terminal heat stressTreatments Spike length (cm) No. of spikelets per spike

Control Heat Mean Control Heat MeanControl 9.64 9.20 9.42 B 12.00 11.55 11.78 BHP 10.46 9.92 10.19 A 14.22 12.94 13.58 AOP 10.18 10.07 10.13 A 13.45 13.33 13.39 AMean 10.09 A 9.73 B 13.22 A 12.61 B

LSD≤ 0.05Heat stress = 0.3582, Seed priming = 0.4388



Table 4.107: Analysis of variance for the influence of seed priming on yield related traits, yield and harvest index of barley under terminal heat stressSOV df No. of

grains per spike

100-grain weight

Grain yield

Biological yield

Harvest index

Heat (H) 1 502.36** 2.127** 69.417** 178.089** 3765.5**

Seed priming (T) 2 22.25** 0.431** 2.121** 7.228** 111.5**

H×T 2 13.03* 0.113* 0.803** 0.628ns 62.8*

Error 30 2.42 0.030 0.131 1.206 16.1Total 35


Table 4.108: Influence of seed priming on number of grains per spike and 100-grain weight of barley under terminal heat stressTreatments No. of grains per spike 100-grain weight (g)

Control Heat Mean Control Heat MeanControl 18.44 b 9.78 e 14.11 B 3.71 ab 3.00 d 3.36 BHP 20.55 a 11.87 d 16.21 A 3.89 a 3.51 bc 3.70 AOP 19.20 ab 14.13 c 16.66 A 3.85 a 3.48 c 3.67 AMean 19.40 A 11.92 B 3.82 A 3.33 B

LSD≤ 0.05Heat stress = 1.0588, Seed priming = 1.2968, Interaction = 1.8339

Heat stress = 0.1176, Seed priming = 0.1441, Interaction = 0.2037

Table 4.109: Influence of seed priming on grain yield and biological yield per pot of barley under terminal heat stressTreatments Grain yield (g per pot) Biological yield (g per pot)

Control Heat Mean Control Heat MeanControl 3.17 c 0.62 e 1.90 B 7.87 3.39 5.63 BHP 4.39 a 1.02 de 2.71 A 9.59 4.70 7.15 AOP 3.71 b 1.29 d 2.50 A 8.65 4.68 6.67 AMean 3.76 A 0.98 B 8.70 A 4.26 B

LSD≤ 0.05Heat stress = 0.2467, Seed priming = 0.3022, Interaction = 0.4273



172

Table 4.110: Influence of seed priming on harvest index (%) of barley under terminal heat stressTreatments Control Heat MeanControl 40.62 b 18.74 d 29.68 BHP 46.11 a 21.97 d 34.04 AOP 43.22 ab 27.88 c 35.55 AMean 43.32 A 22.86 BLSD≤ 0.05 Heat stress = 2.7293, Seed priming = 3.3427, Interaction = 4.7273


Table 4.111a: Analysis of variance for the influence of seed priming on gas exchange attributes of barley under terminal heat stressSOV df Photosynthesis Stomatal

conductanceTranspiration

7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DATHeat (H) 1 169.56** 258.19** 0.2467** 0.0920** 77.998** 107.088**

Seed priming (T) 2 93.33** 81.90** 0.0094ns 0.0032ns 9.161** 5.211ns

H×T 2 40.93* 28.55* 0.0134* 0.0028ns 6.095* 6.468*

Error 30 12.01 8.32 0.0039 0.0023 1.687 1.896Total 35

Table 4.111b: Analysis of variance for the influence of seed priming on gas exchange attributes of barley under terminal heat stressSOV df intercellular CO2

concentrationStomatal limitation

Carboxylation use efficiency

7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DATHeat (H) 1 40401** 23053** 0.248** 0.146** 3.03E-05ns 0.0013*

Seed priming (T) 2 579ns 5329ns 0.003ns 0.033ns 2.15E-03** 0.0048**

H×T 2 2416* 3081ns 0.014* 0.019ns 9.35E-04* 0.0007*

Error 30 667 2678 0.004 0.017 2.73E-04 0.0002Total 35


173

PN ( μ

mol

CO

2 m

-2 s-1

)gs

(mm

ol H

2O m

-2 s-1

)C

i (μm

ol C

O2 m

ol-1)

174

Tr

(mm

ol H

2O m

-2 s-1

)L

s (%

)C

UE

(mol

m-2 S

-1)

175

significant for stomatal conductance, internal CO2 concentration and stomatal limitation

at 7 DAT but non-significant at 14 DAT (Tables 4.111a,b).

Gas exchange attributes were negatively affected by terminal heat stress as

compared to control; however, seed priming treatments exerted ameliorating effect by

improving the gas exchange attributes. Under no heat stress, maximum improvement in

photosynthesis and CUE was caused by hydropriming at 7 and 14 DAT, as compared to

unprimed control. The greatest improvement in stomatal conductance and transpiration

was recorded by osmopriming at 7 DAT and hydropriming at 14 DAT, as compared to

unprimed control. On the other hand, the greatest decrease in internal CO2 concentration

was caused by hydropriming at 7 DAT and osmopriming at 14 DAT; while, stomatal

limitation was increased in response to seed priming treatments from 7 to 14 DAT, as

compared to unprimed control. However, under terminal heat stress, photosynthesis,

stomatal conductance, transpiration and CUE was improved to a maximum by

hydropriming and osmopriming from 7 to 14 DAT, respectively, as compared to

unprimed control. However, maximum decrease in internal CO2 concentration was caused

by osmopriming at 7 DAT and hydropriming at 14 DAT, as compared to unprimed

control. The stomatal limitation was decreased by hydropriming at 7 DAT; however,

increased by seed priming treatments at 14 DAT, as compared to unprimed control

(Figures 4.24a-f, 4.25a-f).

4.5.4. Chlorophyll a fluorescence attributes

Heat stress significantly affected maximal fluorescence (Fm), variable

fluorescence (Fv), Fv/Fm and ETR at 14 DAT but these attributes were not significantly

affected at 7 DAT; while, minimal fluorescence (Fo) and QY were not affected

significantly by terminal heat stress either at 7 and 14 DAT. Seed priming did not affect

chlorophyll a fluorescence attributes significantly at 7 and 14 DAT. The interaction

between heat stress and seed priming was significant for Fm, Fv and Fv/Fm at 7 DAT

while non-significant for these traits at 14 DAT. Moreover, the interaction of heat stress

and seed priming was significant for ETR at 7 and 14 DAT, while, QY was not

significantly affected at 7 DAT but significantly affected at 14 DAT (Table 4.112a,b).

Terminal heat stress did not decrease the Fm, Fv and Fv/Fm at 7 DAT but at 14

DAT these traits were decreased by heat stress, as compared to control. However, at 7

DAT seed priming partially improved the Fm, Fv and Fv/Fm with maximum

improvement caused by hydropriming under normal and osmopriming under heat stressed

conditions, as compared to unprimed control. Electron transport rate was decreased by 176

heat stress at 14 DAT; while, seed priming improved the ETR at both 7 and 14 DAT, as

compared to

177

Table 4.112a: Analysis of variance for the influence of seed priming on chlorophyll a fluorescence attributes of barley under terminal heat stressSOV df Minimal

fluorescence (F0)Maximal fluorescence

(Fm)Variable

fluorescence (Fv)7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DAT

Heat (H) 1 720.0ns 1626.8ns 67ns 141501** 1225 ns 101867**

Seed priming (T) 2 90.3ns 961.8ns 6274ns 1997ns 5394ns 1965ns

H×T 2 63.7ns 588.0ns 15861* 3826ns 13977* 2910ns

Error 30 203.8 424.6 4676 4736 3477 3286Total 35

Table 4.112b: Analysis of variance for the influence of seed priming on chlorophyll a fluorescence attributes of barley under terminal heat stressSOV df Maximum

efficiency of PSII (Fv/Fm)

Quantum yield of PSII (QY)

Electron transport rate (ETR)

7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DATHeat (H) 1 0.0017ns 0.0235** 2025ns 21025** 0.0007ns 0.0336ns

Seed priming (T) 2 0.0007ns 0.0018ns 7375ns 2003ns 0.0132ns 0.0111ns

H×T 2 0.0018* 0.0015ns 9027* 5986* 0.0015ns 0.0552*

Error 30 0.0005 0.0023 2661 1662 0.0130 0.0148Total 35


178

Min

imal

fluo

resc

ence

(Fo)

Max

imal

fluo

resc

ence

(Fm

)V

aria

ble

fluor

esce

nce

(Fv)

179

Max

imum

qua

ntum

yie

ld (F

v/Fm

)Q

uant

um y

ield

of P

SII (

QY

)E

lect

ron

tran

spor

t rat

e (E

TR

)

180

unprimed control. It was noticed that hydropriming was effective in improving ETR

under control while osmopriming was superior under heat stress. Compared with control,

QY was decreased by heat stress at 14 DAT while improved by osmopriming, as

compared to unprimed control (Figures 4.26a-f, 4.27a-f).


The chlorophyll contents of barley were significantly affected by terminal heat

stress at 7 as well as 14 day after treatment (DAT). Seed priming as well as interaction of

heat stress and seed priming significantly affected chlorophyll a at 14 DAT, and

chlorophyll b and total chlorophyll contents at 7 and 14 DAT. However, chlorophyll a

content was not affected significantly by seed priming, interaction of heat stress and seed

priming at 7 DAT (Table 4.113). Heat stress decreased the biosynthesis of chlorophyll in

barley as compared to control. However, seed priming improved the chlorophyll contents

under normal as well as heat stressed conditions. Chlorophyll a, b and total chlorophyll

contents were improved by hydropriming and osmopriming under normal and under heat

stressed conditions at 7 and 14 DAT, respectively, as compared to unprimed control

(Figures 4.28a-f).

4.5.6. Biochemical attributes

Terminal heat stress significantly affected MDA and cell membrane stability at 7

as well as 14 DAT; while, total soluble phenolics were not significantly affected at 7

DAT while significantly affected at 14 DAT. Likewise, seed priming significantly

affected MFA, total soluble phenolics and cell membrane stability at both 7 and 14 DAT.

However, the interaction between heat stress and seed priming was significant for total

soluble phenolics, MDA and cell membrane stability at both 7 and 14 DAT (Table 4.114).

Heat stress increased the accumulation of phenolics and MDA while decreased cell

membrane stability as compared to control at both 7 and 14 DAT. However, seed priming

ameliorated the negative effects of heat stress by decreasing the accumulation of MDA

while increased the phenolics and cell membrane stability, as compared to unprimed

control. Under no heat stress, hydropriming caused maximum decrease in MDA and

increase in phenolics and cell membrane stability, as compared to unprimed control.

However, under terminal heat stress, osmopriming was superior in decreasing MDA, and

improving phenolics and cell membrane stability at both 7 and 14 DAT, as compared to

unprimed control (Figures 4.29a-f).

181

Table 4.113: Analysis of variance for the influence of seed priming on chlorophyll contents of barley under terminal heat stressSOV df Chlorophyll a Chlorophyll b Total chlorophyll

7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DATHeat (H) 1 0.0961** 0.0374** 0.0107* 0.0030* 0.1708** 0.0633**

Seed priming (T) 2 0.0006ns 0.0034** 0.0071* 0.0037** 0.0098* 0.0135**

H×T 2 0.0001ns 0.0030* 0.0074* 0.0030** 0.0087* 0.0103**

Error 30 0.0003 0.0006 0.0017 0.0004 0.0022 0.0018Total 35

Table 4.114: Analysis of variance for the influence of seed priming on total soluble phenolics, malondialdehyde and cell membrane stability of barley under terminal heat stressSOV df Total soluble

phenolics Malondialdehyde Cell membrane

stability7 DAT 14 DAT 7 DAT 14 DAT 7 DAT 14 DAT

Heat (H) 1 110.8ns 3026.3** 1530.50** 681.21** 33.54** 32.97*

Seed priming (T) 2 2031.6* 1893.8** 101.49** 76.30* 259.17** 634.42**

H×T 2 2125.4* 1098.7* 47.52* 114.08** 7.40* 32.26**

Error 30 538.9 270.0 12.21 19.89 1.95 4.68Total 35


182

Chl

orop

hyll

a co

nten

t (m

g g-1

FW

)C

hlor

ophy

ll b

cont

ent (

mg

g-1 F

W)

Tot

al c

hlor

ophy

ll co

nten

t (m

g g-1

FW

)

183

Tot

al so

lubl

e ph

enol

ics (

µg g

-1 F

W)

Mal

ondi

alde

hyde

(µm

ol g

-1 FW

)C

ell m

embr

ane

stab

ility

(%)

184

4.5.7. Discussion

Emergence of barley was enhanced by seed priming as compared to control. There

was an increase in emergence percentage and emergence index while decrease in

emergence time. Seed priming improves the emergence with concomitant decrease in

emergence time by allowing the germination metabolism to occur without actual

germination due to controlled hydration of seed (Farooq et al., 2006a). Better emergence

by seed priming is attributed to improved activity of hydrolytic enzymes and

carbohydrate metabolism (Farooq et al. 2009b). It has been observed that seed priming

causes de novo synthesis of the α-amylase enzyme (Lee and Kim, 2000), while, increases

activities of β-amylase, root system dehydrogenase and catalase enzymes (He et al.,

2002). In present study, the Ca2+ used in osmopriming, is involved in structural integrity

and permeability of cell membrane which results in decreased cell membrane leakage

(Posmyk et al., 2001; Hepler, 2005) resulting in improved germination and seedling

vigour (Ruan et al., 2002a, b).

Terminal heat stress decreased the performance of barley by reducing growth,

yield and photosynthesis while increasing lipid peroxidation. However, seed priming

improved the photosynthesis and ETR while decreased lipid peroxidation through

enhanced accumulation of phenolics ultimately increasing the grain yield and harvest

index. Seed priming improves the stress tolerance by exalting the accumulation of

transcription factors and metabolites which rapidly and greatly up-regulates the gene

expression for osmolytes and antioxidants on exposure to stress (Kibinza et al., 2011;

Chen and Arora, 2013), thereby improving the water relations and decreasing lipid

peroxidation (Tabassum et al., 2017). Moreover, in present study the Ca2+ used in

osmopriming, is involved in enhancing the gene expression for osmolytes, and improves

plant growth and stress tolerance by regulating the calmodulin like proteins in signaling

pathways (White and Broadley, 2003; Sarwat et al., 2013).

In present study, the decrease in photosynthesis by terminal heat stress was

associated with a reduction in stomatal conductance and intercellular CO2 concentration

which might be due to closure of stomata as an early response of plants to heat stress

(Fahad et al., 2017); nonetheless, these reductions were less in seed primed plants

compared with unprimed plants especially at earlier time following heat stress. Wang et

al. (2014) suggested that stomatal conductance is regulated more by leaf tissue water

status rather than ABA production under abiotic stress. Seed priming improves the tissue

water status through osmotic adjustment by exaggerating osmolytes accumulation which 185

enhances stomatal conductance and photosynthesis under stressed conditions (Tabassum

et al., 2017; Abid et al., 2018). In present study improved stomatal conducatance by

osmopriming may be due to Ca2+ signaling which regulates the stomatal aperture because

stomatal closure is induced by increased concentration of external Ca2 + thus affecting the

CO2 exchange rate (Hochmal et al., 2015).

Chlorophyll pigments are degraded by high temperature which causes drastic

reductions in photosynthesis due to decreased CUE of Rubisco and photochemical

efficiency of PSII (Salvucci and Brandner, 2004a,b; Feng et al., 2014). Similarly, in

present study, decrease in chlorophyll contents, CUE, photochemical efficiency of PSII

and photosynthesis occurred under terminal heat stress, as compared to control. However,

seed priming improved biosynthesis of chlorophyll, CUE, Fv/Fm, QY and ETR under

heat stress, as compared to unprimed control. In seed primed plants, cellular membranes

and organelles are better protected by enhanced accumulation of osmolytes and

antioxidants activity resulting in improved chloroplast ultrastructure, chlorophyll

contents, photosynthesis and chlorophyll photochemistry (Dai et al., 2017; Abid et al.,

2018). In present study, improved chlorophyll, photosynthesis and chlorophyll

photochemistry by osmopriming might be attributed to Ca2+ which is structural

component of PSII, and regulates the NADK2 gene that encodes for NAD+ in chloroplast

and deletion or down regulation of this gene results in decreased chlorophyll biosynthesis,

QY and ETR (Hochmal et al., 2015). Moreover, increase in extracellular Ca2+ enhances

the ETR in cyclic electron flow (Terashima et al., 2012).

In present study, heat stress caused a reduction in cell membrane stability due to

increased lipid peroxidation; however, seed priming accumulated phenolics in greater

quantities which improved cell membrane stability and decreased MDA accumulation, as

compared to unprimed control. This might be due to suppression of photosynthesis by

terminal heat stress which leads to greater production of ROS causing oxidative damage

to the cellular membranes, photosynthetic machinery, proteins, lipids and nucleic acid

(Xiong et al., 2002). However, seed priming induces osmolytes and antioxidants defense

which counteracts the ROS activity and lipid peroxidation leading to improved cell

membrane stability (Chen and Arora, 2013). In present study, phenolics were enhanced

by seed priming which contain aromatic ring in their structures with one or more

hydroxyl groups, and protect and stabilize cellular membranes and organelles under

stressed conditions (Taiz et al., 2015), by enhanced scavenging of ROS in cells ultimately

improving stress tolerance and plant growth (Shetty et al. 2001; Song et al., 2017).186

In present study, terminal heat stress imposed deleterious effects on yield and

related traits, and harvest index of barley. However, improved photosynthesis and better

protection of cellular membranes as recorded in present study, and improved water

relations by seed priming might have improved the pollen viability and assimilate

translocation leading to improved grain setting and grain weight (Mohammed and

Tarpley, 2009; Mohammed et al., 2015; Abid et al., 2018). These gains from

osmopriming were translated into higher number of productive tillers, number of grains

and grain weight, which resulted in improved grain yield and harvest index (Tabassum et

al., 2017).

187

4.6. Influence of seed priming on the productivity of late sown barley

4.6.1. Stand establishment


The mean emergence time was significantly affected by sowing time and seed

priming, during both years. However, the varieties did not differ significantly for mean

emergence time. Likewise, the interactions between sowing time and varieties, sowing

time and seed priming, varieties and seed priming, and three way interaction among

sowing time, varieties and seed priming was non-significant, during both years (Table

4.115). Mean emergence time was substantially increased by late sowing as compared to

optimum sowing, during both years. However, seed priming treatments caused a

reduction in mean emergence time with minimum time elapsed by osmopriming, during

both years (Table 4.116).


There was a significant influence of sowing time and seed priming on time taken

for 50%; while, the varieties did not differ significantly for time taken to 50% emergence,

during both years. The interaction between varieties and seed priming was significant

during 2014-15 but non-significant during 2015-16. However, the interactions between

sowing time and varieties, sowing time and seed priming, and three way interaction

among sowing time, varieties and seed priming was non-significant, during both years

(Table 4.115). Time taken to 50% emergence was increased by late sowing than optimum

sowing. However, seed priming treatments decreased time taken to 50% emergence with

maximum reduction caused by osmopriming, as compared to control, during both years.

Furthermore, varieties responded differently to seed priming treatments during 2014-15.

Minimum time taken to 50% emergence was taken by Haider-93 in response to

osmopriming while Fronteirs-87 responded better to biopriming (Tables 4.117a,b).


Sowing time and seed priming treatments significantly affected emergence index

while variety did not differ significantly for emergence index, during both years. The

interaction between varieties and seed priming was significant for emergence index

during 2014-15 while non-significant during 2015-16. Whereas, interactions between

sowing time and varieties, sowing time and seed priming, and three way interaction

among sowing time, varieties and seed priming was non-significant for emergence index,

during both years (Table 4.115). Late sowing decreased the emergence index as compared

188

to optimum sowing. However, seed priming improved the emergence index with

maximum

189

Table 4.115: Analysis of variance for the influence of seed priming on emergence of barley under optimum and late sowing time

SOV DF Mean sum of squareMean emergence

timeTime taken to 50%

emergenceEmergence index

2014-15 2015-16 2014-15 2015-16 2014-15 2015-16Replication (R) 3 0.380 0.109 0.176 0.098 94.815 91.519Sowing time (SD) 1 53.053** 53.290** 45.782** 53.144** 1747.136** 1491.118**

Error 1 3 0.003 0.000 0.078 0.059 72.290 70.339Varieties (V) 1 0.000ns 0.002ns 0.015ns 0.044ns 5.377ns 7.223ns

SD×V 1 0.007ns 0.002ns 0.000ns 0.130ns 0.468ns 0.019ns

Error 2 6 0.068 0.030 0.175 0.048 1.121 2.200Priming (T) 3 1.036** 0.720** 1.084** 0.936** 101.937** 42.338**

SD×T 3 0.003ns 0.015ns 0.081ns 0.019ns 1.144ns 0.845ns

V×T 3 0.042ns 0.034ns 0.216* 0.173ns 8.117* 2.455ns

SD×V×T 3 0.003ns 0.013ns 0.002ns 0.084ns 0.006ns 0.062ns

Error 3 36 0.019 0.032 0.042 0.092 1.537 3.944Total 63


Table 4.116: Influence of seed priming on mean emergence time (days) of barley under optimum and late sowing timeTreatments

2014-15 2015-16November

30December

30Mean November

30December

30Mean

Control 5.79 7.65 6.72 A 5.90 7.81 6.85 AHP 5.63 7.43 6.53 B 5.58 7.37 6.47 BCOP 5.24 7.05 6.15 D 5.46 7.27 6.36 CBP 5.37 7.19 6.28 C 5.61 7.40 6.51 BMean 5.51 B 7.33 A 5.64 B 7.46 A

Sowing time LSD≤0.05 = 0.0443 (2014-15) and 0.0083 (2015-16), Seed priming LSD≤0.05 = 0.0987 (2014-15) and 0.1277 (2015-16)

Table 4.117a: Influence of seed priming on time taken for 50% (days) emergence of barley under optimum and late sowing timeTreatments 2014-15 2015-16

November 30

December 30

Mean November 30

December 30

Mean

Control 4.94 6.57 5.75 A 5.08 6.95 6.02 AHP 4.60 6.12 5.36 B 4.68 6.52 5.60 BOP 4.30 6.09 5.19 C 4.53 6.39 5.46 BBP 4.29 6.12 5.21 C 4.72 6.44 5.58 BMean 4.53 B 6.22 A 4.75 B 6.58 A

Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 0.2224 (2014-15) and 0.1932 (2015-16), Seed priming LSD≤0.05 = 0.1478 (2014-15) and 0.2177 (2015-16)

190

Table 4.117b: Influence of seed priming on time taken to 50% emergence (days) of barley under optimum and late sowing time (2014-15)Treatments H-93 F-87 MeanControl 5.87 a 5.63 b 5.75 AHP 5.31 c 5.40 c 5.36 BOP 5.07d 5.31 c 5.19 CBP 5.31 c 5.10 d 5.21 CMean 5.39 5.36

Seed priming LSD≤0.05 = 0.1478, Varieties × Seed priming LSD≤0.05 = 0.2090

Table 4.118a: Influence of seed priming on emergence index of barley under optimum and late sowing time

Treatments 2014-15 2015-16November

30December 30 Mean November

30December 30 Mean

Control29.41 19.73

24.57 C 30.28 21.25

25.76 B

HP33.63 23.09

28.36 B 33.60 23.96

28.78 A

OP35.48 24.61

30.05 A 34.43 24.32

29.37 A

BP35.14 24.42

29.78 A 33.66 23.82

28.74 A

Mean 33.41 A 22.97 B 32.99 A 23.34 BSowing time LSD≤0.05 = 6.7645 (2014-15) and 7.7733 (2015-16), Seed priming LSD≤0.05 = 0.8889 (2014-15) and 1.4240 (2015-16)

Table 4.118b: Influence of seed priming on emergence index of barley under optimum and late sowing time (2014-15)Treatments H-93 F-87 MeanControl 25.76 c 23.38 d 24.57 CHP 28.67 ab 28.05 ab 28.36 BOP 30.26 a 29.83 a 30.05 ABP 29.23 a 30.33 a 29.78 AMean 28.48 27.90

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Seed priming LSD≤0.05 = 0.8889, Varieties × Seed priming LSD≤0.05 = 1.2570

191

increased caused by osmopriming, during both years. Furthermore, varieties responded

differently to seed priming treatments regarding emergence index with highest emergence

index produced by Haider-93 in response to osmopriming and Fronteirs-87 in response to

biopriming during 2014-15 (Tables 4.118a,b).

4.6.2. Discussion

Late sowing caused a reduction in emergence and seedling establishment due to

prevailing low temperature at the time of sowing. However, seed priming improved the

emergence index with a reduction in emergence time indicating that seed priming has

potential to improve emergence under late sown conditions and prevailing low

temperature. Previous reports have shown that seed priming enhances germination speed,

germination rate and uniformity under optimum and late sown chilling stressed field

conditions (Kant et al., 2006; Farooq et al., 2008a). Seed priming makes the food reserves

readily available for embryo by enhancing carbohydrate metabolism through enhanced

activities of hydrolytic enzymes (Kaur et al., 2005; Farooq et al. 2009b). He et al. (2002)

reported that seed priming improved the α-amylase, β-amylase, catalase and root system

dehydrogenase activities in rice under stressed conditions. In the present study,

osmopriming improved emergence of barley which may be due to Ca2+ that regulates the

cell wall structure, cell membrane integrity and permeability, and mitotic activities

(Hepler, 2005) resulting in well-maintained cell membrane with better and rapid

germination (Posmyk et al., 2001). In present study, improved emergence by biopriming

might be due to endophytic bacteria which might have improved water absorption in

germinating seeds, and produced extracellular hydrolytic enzymes viz. amylase and

protease resulting in enhanced degradation of carbohydrates, proteins and lipids leading

to better germination under normal and stressed conditions (Zhu et al., 2017).

4.6.3. Allometric traits

4.6.3.1. Leaf area index

The LAI was increased progressively and then declined with advancement in crop

maturity. Higher LAI was recorded by optimum sowing than late sowing. It was observed

that maximum LAI was produced at 75 DAS in optimum sowing and 60 DAS in late

sowing, during both years. Likewise, the varieties differed regarding LAI. Fronteir-87

produced greater LAI than Haider-93. However, there was prompt increase in LAI of

Frontier-87 at early growth stages (upto 75 DAS) and started decreasing rapidly

afterwards while in Haider-93 there was slow increase at early growth stages and

192

decrease at later growth stages until maturity. Moreover, seed priming improved the LAI

of both varieties

193

Lea

f are

a in

dex

194

Lea

f are

a in

dex

195

at both sowing times and growth stages as compared to control, during both years.

Haider-93 responded well to osmopriming and Frontier-87 produced highest LAI by

biopriming under both optimum and late sowing times. However, under both optimum

and late sowing conditions maximum LAI was produced by biopriming of Frontier-87

(Figures 4.30, 4.31).

4.6.3.2. Total dry matter

The temporal pattern of TDM accumulation showed an increase upto maturity.

Late sowing caused a reduction in TDM accumulation as compared to optimum sowing,

during both years. Maximum TDM accumulation took place during 45-75 DAS in both

sowing time. There was a differential accumulation of TDM in both varieties. During

2014-15, Haider-93 produced more TDM than Frontier-87 although Frontier-87

accumulated more TDM during early growth stages than Haider-93. However, during

2015-16 Frontier-87 accumulated more TDM than Haider-93 from initial stages to

maturity. Seed priming improved the TDM in both varieties at both sowing times and all

growth stages. It was observed that under optimum sowing maximum TDM accumulation

in both varieties occurred by osmopriming, during both years; however, under late

sowing, maximum increase in TDM accumulation in Haider-93 was caused by

osmopriming during 2014-15 and biopriming during 2015-16 while in Frontier-87

biopriming improved TDM most, during both years. Overall, maximum TDM was

recorded by osmopriming of Haider-93 under optimum sowing time, while, biopriming of

Haider-93 produced similar TDM during 2014-15. However, under late sowing, highest

TDM was produced by osmopriming of Haider-93 during 2014-15 and biopriming of

Frontier-87 during 2015-16. However, biopriming of Haider-93 produced similar TDM

during 2015-16 (Figures 4.32, 4.33).

4.6.3.3. Crop growth rate

Crop growth rate of barley increased with increase in time and then dropped until

maturity. Late sowing caused a reduction in CGR than optimum sowing, during both years.

In optimum sowing, maximum CGR was attained at 45 DAS and then remained stable until

60-75 DAS; while, in late sowing maximum CGR was recorded at 45-60 DAS. The

varieties performed differently regarding CGR. Haider-93 attained maximum CGR at 60-

75 DAS while Frontier-87 attained highest CGR at 45-60 DAS after which it started

declining. Haider-93 exhibited higher CGR than Frontier-87 under both sowing times. Seed

priming improved the CGR of both varieties at both sowing times and all growth stages, as

compared to control. In optimum sowing, maximum improvement in CGR of both varieties 196

was caused by osmopriming, during both years. In late sowing, the osmopriming was

superior in improving CGR of Haider-93 during 2014-15 and biopriming was effective

during 2015-16.

197

Tot

al d

ry m

atte

r (g

m-2)

198

Tot

al d

ry m

atte

r (g

m-2)

199

Cro

p gr

owth

rat

e (g

m-2 d

-1)

200

Cro

p gr

owth

rat

e (g

m-2 d

-1)

201

However, maximum improvement in CGR was recorded by biopriming of Fronter-87

under late sowing, during both years. Overall, maximum CGR was observed by

osmopriming of Haider-93 under optimum sowing time, during both years, and by

osmopriming and biopriming of Haider-93 under late sowing during 2014-15 and 2015-

16, respectively (Figures 4.34, 4.35).

4.6.3.4. Grain filling rate

Grain filling was increased with time and then declined at maturity. Late sowing

caused a drastic reduction in grain filling rate as compared to optimum sowing time.

Maximum grain filling rate occurred at 14-21 days after anthesis (DAA) in both sowing

times, during both years. Moreover, varieties differed in grain filling rate. In Haider-93

greater grain filling rate was observed in early stages of grain filling while in Frontier-87

higher grain filling rate was observed at later stages of grain filling. Seed priming

improved the grain filling rate of both varieties at both sowing times and all growth

stages, as compared to unprimed control. It was observed that at optimum sowing highest

grain filling rate occurred by osmopriming and biopriming of Haider-93 during 2014-15

and 2015-16, respectively. Whereas, in late sowing maximum increase in grain filling rate

was caused by biopriming of Haider-93, during both years (Figures 4.36, 4.37).

4.6.3.5. Grain filling duration

Grain filling duration was significantly affected by sowing time; while, tested

barley varieties also differed significantly, during both years. Seed priming did not affect

grain filling rate during 2014-15 but significantly affected during 2015-16. Likewise,

interaction between sowing time and varieties was significant for grain filling duration

during 2014-15 but non-significant during 2015-16. The interactions between sowing

time and seed priming, and varieties and seed priming were non-significant, during both

years. However, three way interaction among sowing time, varieties and seed priming

was significant, during both year (Table 4.119). Late sowing caused a substantial

decrease in grain filling duration as compared to optimum sowing. Likewise, Haider-93

took less time for grain filling than Frontier-87, during both years. Seed priming was not

influential on grain filling duration during 2014-15 but during 2015-16 biopriming caused

a slight decrease. At optimum sowing, highest grain filling duration was recorded by

osmopriming of Frontiers-87 and least was observed by osmopriming of Haider-93,

during both years. However, at late sowing, highest grain filling duration occurred by

biopriming of Frontier-87 during 2014-15 and hydropriming of Frontier-87 during 2015-

202

16. Whereas, minimum grain filling duration was recorded by biopriming of Haider-93,

during both years, while, G

rain

filli

ng r

ate

(mg

spik

e-1 d

-1)

203

Gra

in fi

lling

rat

e (m

g sp

ike-1

d-1)

204

Table 4.119: Analysis of variance for the influence of seed priming on grain filling duration of barley under optimum and late sowing time

SOV DFMean sum of squares

2014-15 2015-16Replication (R) 3 0.72 1.90Sowing time (SD) 1 1032.02** 462.25**

Error 1 3 1.89 0.42Varieties (V) 1 17.02** 33.06**

SD×V 1 8.27* 1.00ns

Error 2 6 1.22 1.11Priming (T) 3 0.52ns 2.40*

SD×T 3 0.52ns 0.25ns

V×T 3 0.18ns 0.56ns

SD×V×T 3 5.68** 2.17*

Error 3 36 0.78 0.66Total 63


Table 4.120: Influence of seed priming on grain filling duration (days) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30

H-93 F-87 H-93 F-87Control 34.25 bc 35.50 ab 28.25 ef 29.25 efHP 33.75 cd 35.50 ab 28.25 ef 28.00 fOP 32.75 d 36.25 a 29.25 ef 28.25 efBP 34.25 bc 34.75 bc 28.00 f 29.50 e

Sowing time × Varieties × Seed priming LSD≤0.05 = 1.2661

Table 4.121: Influence of seed priming on grain filling duration (days) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30

H-93 F-87 H-93 F-87Control 33.75 bc 35.75 a 28.50 fg 30.00 deHP 34.75 ab 35.75 a 29.25 def 30.25 dOP 32.75 c 35.75 a 29.00 efg 29.50 defBP 34.00 b 34.75 ab 28.00 g 29.75 de

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 1.1679

205

hydropriming of Frontier-87 gave similar results during 2014-15 (Tables 4.120, 4.121).

4.6.4. Discussion

In present study, late sowing caused a reduction in TDM and CGR which was

associated with decrease in LAI. Late sowing causes a reduction in plant growth by

exposing the plants to cold stress (Farooq et al., 2008a). Moreover, decrease in LAI in

present study may be attributed to decreased emergence and plant growth by early season

low temperature because LAI is a function of number of plants and leaves per unit area,

and leaf growth rate. However, in present study seed priming improved LAI, TDM and

CGR under both optimum and late sowing. This might be due to enhanced early seedling

vigour and enhanced plant protection from environmental stresses resulting in improved

plant growth and leaf area under normal and stressed conditions (Tabassum et al., 2017).

Furthermore, it was observed that seed priming improved the photosynthetic pigments

which may have resulted in enhanced photosynthesis leading to improved TDM

production and grain yield (Abid et al., 2018).

In current study, osmopriming enhanced LAI, TDM and CGR which might be due

to the Ca2+ which modulates the calmodulin like protiens in signaling pathways and

improves plant growth (Sarwat et al., 2013). Furthermore, Ca2+ is involved in cell wall

structure, cell membrane integrity and permeability, and cell division which regulates the

plant growth and development (Hepler, 2005). Moreover, in this study improved leaf area

and chlorophyll contents by osmopriming may have resulted in better light utilization and

photosynthesis because Ca2+ is also involved in chlorophyll synthesis and photosynthesis

(Hochmal et al., 2015; Dai et al., 2017) thus improving the dry matter production.

Improved plant growth and TDM by biopriming may be attributed to the endophytic

bacteria which improves the plant growth and development by production of plant growth

promoting hormones while decreasing ethylene production, and by improved nutrient

uptake (Miliute et al., 2015). Previous studies have shown that endophytic bacteria

Enterobacter sp. FD17, used in present study, improves the leaf area, chlorophyll

photochemistry, photosynthesis and dry matter production and ultimately crop yield

(Naveed et al., 2014a).

In present study, late sowing decreased the grain filling rate which is attributed to

decreased plant growth, leaf area and grain filling duration. The decreased leaf area

resulted in decreased dry matter accumulation and CGR due to decrease in assimilatory

surface. However, seed priming treatments improved the grain filling rate which may be

attributed to improved LAI and CGR because grain filling duration was not affected by 206

seed priming treatments. It has been observed that seed priming with CaCl2 improves the

leaf area, leaf area duration (LAD) and NAR (Mahboob et al., 2015). Moreover, in present

study improved grain filling rate by seed priming under late sowing conditions might be

attributed to its protective role form high temperature stress because late sowing exposes

the plants to high temperature during grain filling period which negatively affects the starch

synthase enzyme because it is sensitive to temperature more than 20˚C (Keeling et al.,

1994).



A significant influence of sowing time and seed priming was noticed for plant

height of barley; while barley varieties also significantly differed for plant height, during

both years. The interaction between sowing time and varieties was significant during

2014-15 but non-significant during 2015-16. Interaction between sowing time and seed

priming was non-significant, during both years. Whereas, interaction between varieties

and seed priming, and three way interaction among sowing time, varieties and seed

priming were non-significant during 2014-15 but significant during 2015-16 (Table

4.122). Late sowing decreased the plant height than optimum sowing. Taller plants were

produced by Frontier-87 than Haider-93. Seed priming increased the plant height of both

varieties at both sowing times, as compared to unprimed control. During 2014-15,

biopriming and osmopriming of Frontier-87 produced tallest plants at optimum sowing

and late sowing, respectively. However, during 2015-16, tallest plants were noticed by

biopriming of Frontier-87 and Haider-93 at optimum sowing and late sowing,

respectively (Tables 4.123a-4.124).

4.6.5.2. Number of productive tillers m-2

Number of productive tillers m-2 was affected significantly by sowing time and

seed priming; barley varieties also significantly differed for number of productive tillers,

during both years. The interaction between sowing time and varieties was significant

during 2014-15 but non-significant during 2015-16. The interactions between sowing

time and seed priming, and varieties and seed priming were non-significant, during both

years. However, three way interaction among sowing time, varieties and seed priming

was significant, during both years (Table 4.122). The production of productive tillers was

decreased by late sowing than optimum sowing. Higher number of productive tillers was

produced by Haider-93 than Frontier-87. Number of productive tillers of both varieties

was increased by seed priming at both sowing times, as compared to unprimed control. 207

Highest number of productive tillers was produced by osmopriming of Haider-93 at

optimum sowing, during both years, while at late sowing, osmopriming and biopriming of

Haider-93 caused maximum increase in number of productive tillers during 2014-15 and

2015-16,

208

Table 4.122: Analysis of variance for the influence of seed priming on plant height and number of productive tillers per m2 of barley under optimum and late sowing time


Plant height Number of productive tillers per m2

2014-15 2015-16 2014-15 2015-16Replication (R) 3 127.79 48.95 49.02 138.28Sowing time (SD) 1 11236.00** 5645.08** 40876.75** 88553.11**

Error 1 3 133.97 31.43 76.96 452.83Varieties (V) 1 192.31** 92.62* 399.10* 1115.81**

SD×V 1 15.27* 5.25ns 1685.10** 44.0ns

Error 2 6 2.42 12.75 39.58 52.08Priming (T) 3 85.58* 431.10** 13920.40** 6408.34**

SD×T 3 73.24ns 50.38ns 98.42ns 273.07ns

V×T 3 14.06ns 64.11* 8.55ns 42.01ns

SD×V×T 3 17.43ns 63.12* 283.13** 566.82*

Error 3 36 26.03 21.14 54.46 174.75Total 63


Table 4.123a: Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30 MeanH-93 109.35 b 83.83 d 96.59 BF-87 113.79 a 86.32 c 100.05 AMean 111.57 A 85.07 B

Sowing time LSD≤0.05 = 9.2088, Varieties LSD≤0.05 = 0.9508, Sowing time × Varieties LSD≤0.05 = 1.3446

Table 4.123b: Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30 MeanControl 108.76 80.95 94.86 BHP 113.45 85.61 99.53 AOP 109.46 89.18 99.32 ABP 114.61 84.54 99.58 AMean 111.57 A 85.07 B

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 9.2088, Seed priming LSD≤0.05 = 3.6584

209

Table 4.124: Influence of seed priming on plant height (cm) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30

H-93 F-87 H-93 F-87Control 88.75 b 90.50 b 67.76 f 79.35 deHP 97.75 a 101.08 a 73.01 ef 77.95 deOP 99.67 a 99.92 a 81.48 cd 84.30 bcdBP 101.50 a 103.50 a 87.99 bc 80.57 d


Table 4.125: Influence of seed priming on number of productive tillers per m2 of barley under optimum and late sowing time

Treat-ments

2014-15 2015-16November 30 December 30 November 30 December 30

H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control

354.02 ef 351.11 f 307.26 h 303.48 h 358.28 c 350.46 c 285.07 f 281.52 f

HP411.01 b 390.86 c 340.04 g

350.52 fg 388.93 b 379.70 b 314.44 de 299.74 ef

OP 425.16 a 412.50 b 371.90 d 374.78 d 421.34 a 393.40 b 319.34 d 326.85 dBP 425.06 a 399.75 c 352.81 f 364.30 de 385.73 b 390.67 b 331.21 d 315.18 de

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 10.5832 (2014-15) and 18.9575 (2015-16)

210

respectively (Table 4.125).


Sowing time and seed priming treatments significantly affected spike length,

during both years. However, tested barley varieties did not differ significantly for spike

length during both years. The interaction between varieties and seed priming was non-

significant for spike length, during both years. The interactions between sowing time and

varieties, sowing time and seed priming, and three way interaction among sowing time,

varieties and seed priming was significant for spike length, during both years (Table

4.126). Late sowing decreased the spike length as compared to optimum sowing. Longer

spikes were produced by Haider-93 than Frontier-87. Seed priming enhanced the spike

length of both barley varieties at both sowing times, as compared to unprimed control.

Maximum increase in spike length was recorded by biopriming of Haider-93 at optimum

sowing, during both years. However, at late sowing the greatest increase in spike length

was observed by osmopriming of Frontier-87 during 2014-15 and biopriming of Haider-

93 during 2015-16 (Table 4.127).


Sowing time and seed priming treatments significantly affected the number of

spikelets per spike, during both years. The varieties significantly differed during 2014-15

while did not differ significantly during 2015-16 for number of spikelets per spike.

Interactions between sowing time and varieties, and sowing time and seed priming were

significant during 2014-15 but non-significant during 2015-16. The interaction between

varieties and seed priming was non-significant for number of spikelets per spike during

2014-15 while significant during 2015-16. The three way interaction among sowing time,

varieties and seed priming was significant, during both years (Table 4.126). Late sowing

lowered the number of spikelets per spike as compared to optimum sowing. Higher

number of spikelets were produced by Haider-93 than Frontier-87. Number of spikelets

per spike of both varieties were improved by seed priming at both sowing times, as

compared to unprimed control. At optimum sowing osmopriming of Haider-93 while at

late sowing biopriming of Haider-93 caused greatest increase in number of spikelets per

spike, during both years. However osmopriming of Haider-93 at late sowing produced

similar results for number of spikelets per spike during 2015-16 (Table 4.128).


211

There was a significant effect of sowing time and seed priming on number of

grains per spike; tested barley varieties also differed significantly for number of grains

per spike,

212

Table 4.126: Analysis of variance for the influence of seed priming on spike length and number of spikelets per spike of barley under optimum and late sowing time


Spike length Number of spikelets per spike2014-15 2015-16 2014-15 2015-16

Replication (R) 3 0.162 0.052 0.799 0.675Sowing time (SD) 1 43.346** 101.884** 823.475** 530.151**

Error 1 3 0.188 0.123 2.691 0.412Varieties (V) 1 0.082ns 1.706ns 31.767** 2.481ns

SD×V 1 13.811** 1.739* 0.032ns 0.903ns

Error 2 6 0.072 0.286 0.886 0.801Priming (T) 3 17.972** 7.938** 54.501** 49.995**

SD×T 3 1.739** 1.088** 4.697* 1.094ns

V×T 3 0.733ns 0.287ns 1.111ns 2.466**

SD×V×T 3 1.055* 0.495* 3.810* 1.825*

Error 3 36 0.348 0.154 1.262 0.483Total 63


Table 4.127: Influence of seed priming on spike length (cm) of barley under optimum and late sowing time

Treatments


H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 8.83 e 8.70 e 7.29 h 7.52 gh 9.80 e 9.75 e 8.06 h 7.90 hHP 10.28 cd 8.45 ef 7.62 fgh 8.44 ef 11.90 ab 10.95 d 8.33 gh 8.88 fgOP 11.04 bc 10.24 cd 8.75 e 10.03 d 12.03 ab 11.58 bc 8.90 f 8.78 fgBP 11.96 a 11.29 ab 8.15 efg 9.83 d 12.25 a 11.08 cd 9.28 ef 9.03 f

Sowing time × Varieties × Seed priming LSD≤0.05 = 0.8465 (2014-15) and 0.5633 (2015-16)

Table 4.128: Influence of seed priming on number of spikelets per spike of barley under optimum and late sowing time

Treatments


H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 16.50 e 15.40 ef 10.84 ij 9.50 j 17.50 e 16.88 e 11.93 h 11.53 hHP 20.17

bc 18.38 d13.05

gh11.50

hi 19.00 d 21.00 bc 15.00 fg 14.50 gOP

22.50 a19.43

cd13.05

gh12.17

hi 22.00 a 21.00 bc 15.50 f 14.63 fgBP 20.67

bc21.18

ab 14.38 fg12.33

hi21.50

ab 20.50 c 15.50 f 14.75 fgValues sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 1.6110 (2014-15) and 0.9969 (2015-16)

213

during both years. The interactions between sowing time and varieties, and sowing time

and seed priming were significant for number of grains per spike, during both years while

interaction between varieties and seed priming was significant during 2014-15 and non-

significant during 2015-16. The three way interaction among sowing time, varieties and

seed priming was significant, during both years (Table 4.129). A reduction in number of

grains per spike was observed by late sowing as compared to optimum sowing. The

variety Haider-93 produced more number of grains per spike than Frontier-87. However,

seed priming exhibited increase in number of grains per spike of both varieties at both

sowing times, as compared to unprimed control. Highest number of grains per spike were

produced by osmopriming and hydropriming of Haider-93 at optimum sowing during

2014-15 and 2015-16, respectively. However, at late sowing osmopriming of Haider-93

exhibited greatest increase in number of grains per spike, during both years (Table 4.130).


The 1000-grain weight was significantly affected by sowing time and seed

priming; the varieties also differed significantly differed for 100-grains weight, during

both years. However, the interactions between sowing time and varieties, sowing time

and seed priming, varieties and seed priming, and three way interaction among sowing

time, varieties and seed priming was non-significant during 2014-15 while significant

during 2015-16 (Table 4.129). Late sowing caused a reduction in 1000-grain weight as

compared to optimum sowing. Variety Haider-93 produced higher 1000-grain weight

than Frontier-87. The seed priming caused an increase in 1000-grain weight of both

varieties at both sowing times, as compared to unprimed control. At optimum sowing,

osmopriming and biopriming of Haider-93 showed highest increase in 1000-grain weight

of barley during 2014-15 and 2015-16, respectively. Whereas, at late sowing biopriming

of Haider-93 caused the greatest increase in 1000-grain weight, during both years (Table

4.131a-4.132).

4.6.5.7. Grain yield

There was a significant effect of sowing time and seed priming treatments on

grain yield; while, varieties also significantly differed for grain yield, during both years.

Interaction between varieties and seed priming was non-significant during 2014-15 but

significant during 2015-16. However, the interactions between sowing time and varieties,

sowing time and seed priming, and three way interaction among sowing time, varieties

and seed priming was significant for grain yield, during both years (Table 4.133). There

was a substantial reduction in grain yield by late sowing than optimum sowing. The 214

variety Haider-93 produced more grain yield than Frontier-87. Grain yield was

significantly improved by seed priming of both varieties at both sowing times, as

compared to unprimed control. The grain yield was increased most by osmopriming of

Haider-93 at optimum sowing, during both years. However, at late sowing osmopriming

of Haider-93 and biopriming of Frontier-87 exhibited maximum improvement in grain

yield during 2014-15 and 2015-16, respectively (Table 4.134).

4.6.5.8. Straw yield

Sowing time and seed priming significantly affected straw yield while varieties

did not differ significantly, during both years. Interactions between sowing time and

varieties, and varieties and seed priming were non-significant while interaction between

sowing time and seed priming was significant, during both years. However, three way

interaction among sowing time, varieties and seed priming was significant during 2014-

15 but non-significant during 2015-16 (Table 4.133). Late sowing resulted in lower straw

yield as compared to optimum sowing. Variety Frontier-87 produced greater straw yield

than Haider-93. Straw yield was bettered by seed priming of both varieties at both sowing

times, as compared to unprimed control. During 2014-15, straw yield was improved most

by biopriming and osmopriming of Haider-93 at optimum sowing and late sowing,


4.6.5.9. Biological yield

A significant effect of sowing time and seed priming was observed for biological

yield of barley. Tested barley varieties differed significantly during 2014-15 while did not

differ significantly during 2015-16. The interactions between sowing time and varieties,

and varieties and seed priming were non-significant, during both years. Interaction

between sowing time and seed priming was significant for biological yield, during both

years. The three way interaction among sowing time, varieties and seed priming was

significant during 2014-15 but non-significant during 2015-16 (Table 4.137). Lower

biological yield was noticed by late sowing than optimum sowing. Higher biological yield

was recorded by variety Haider-93 during 2014-15 and by Frontier-87 during 2015-16.

Seed priming enhanced the biological yield of both varieties at both sowing times, as

compared to unprimed control. During 2014-15, biological yield was enhanced most by

biopriming and osmopriming of Haider-93, at early and late sowing, respectively (Tables

4.138, 4.139).


215

There was a significant effect of sowing time and seed priming on harvest index;

tested barley varieties also differed significantly for harvest index, during both years. The

interactions between sowing time and varieties, and varieties and seed priming were non-

significant, during both years while interaction between sowing time and seed priming

was significant during 2014-15 but non-significant during 2015-16. The three way

interaction among sowing time, varieties and seed priming was significant, during both

years (Table 4.137). Harvest index was decreased by late sowing as compared to

optimum sowing. Higher harvest index was exhibited by Haider-93. Seed priming

enhanced the harvest index of both varieties at both sowing times, as compared to

unprimed control. At optimum sowing, highest harvest index was recorded by

osmopriming and biopriming of Haider-93 during 2014-15 and 2015-16, respectively. At

late sowing, maximum harvest index was observed by biopriming of Haider-93 and

Frontier-87 during 2014-15 and 2015-16, respectively (Table 4.140).

4.6.6. Discussion

Late sowing caused a decrease in plant height, yield and harvest index of barley

varieties. This could be due to cold temperature during early vegetative stage which

results in decreased plant growth (Farooq et al., 2008a). However, in present study seed

priming improved plant height in both early and late sown conditions. Seed priming

improves the plant growth by early head start and improved stress tolerance by increased

accumulation of osmolytes and antioxidants activity, under stressed conditions (Chen and

Arora, 2013). In osmoprimed plants, higher plant height is attributed to role of Ca2+ in cell

wall structure, cell membrane integrity and mitotic activities (Hepler, 2005). Moreover,

Ca2+ regulates the calmodulin like proteins in signaling pathways and improves the plant

growth under stressed conditions (Sarwat et al., 2013). In biopriming, the endophytic

bacteria migt have promoted the growth by enhancing nutrient uptake through

solubilization and producing plant growth promoting hormones such as auxins, cytokinins

and gibberellic acid while suppressing the ethylene production by synthesis of ACC

deaminase enzyme (Miliute et al., 2015).

In present study, the late sowing caused a reduction in yield and harvest index of

both varieties; while, Haider-93 performed better in this regard. The decrease in grain yield

under late sown conditions was associated with decreased emergence and stand

establishment, number of productive tillers and grains, and grain weight; nonetheless, seed

primed plants showed less reductions than unprimed plants. Higher total and productive

tillers due to seed priming were the result of early better plant growth events such as early 216

vigorous seedling growth and development (Kaur et al., 2005; Farooq et al., 2006b).

Moreover, Ca2+ could have improved the photosynthesis, protected biological membranes

and cell organelles through enhanced osmolytes accumulation and antioxidants activity

217

Table 4.129: Analysis of variance for the influence of seed priming on number of grains per spike and 1000-grain weight of barley under optimum and late sowing time


Number of grains per spike 1000-grain weight2014-15 2015-16 2014-15 2015-16


Error 1 3 4.588 0.452 1.272 0.188Varieties (V) 1 108.134** 42.136** 11.458* 38.347**

SD×V 1 4.177* 4.521* 0.083ns 5.700*

Error 2 6 0.501 0.637 1.743 0.597Priming (T) 3 82.686** 24.476** 11.228** 20.161**

SD×T 3 3.616ns 14.434** 2.244ns 1.885**

V×T 3 1.284ns 4.352* 0.529ns 5.258**

SD×V×T 3 4.078* 4.515* 1.722ns 1.061*

Error 3 36 1.385 1.297 0.904 0.324Total 63


Table 4.130: Influence of seed priming on number of grains per spike of barley under optimum and late sowing time

Treatments


H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 39.09 ghi 37.84 ij 37.93 hij 35.38 k 40.21 bcd 39.83 cd 36.15 e 34.11 fHP 42.88 cd 40.84 ef 40.30 fg 36.47 jk 42.12 a 39.90 cd 39.20 cd 38.78 dOP 45.49 a 43.75 bc 42.88 cd 38.29 hi 41.73 ab 40.23 bcd 41.74 ab 36.94 eBP

45.36 ab 42.03 de 41.08 ef39.61 fgh 40.29 bcd 40.03 cd 40.45 bc 39.09 cd


Table 4.131a: Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2014-15)Treatments H-93 F-87 MeanControl 30.66 29.70 30.18 CHP 31.40 31.04 31.22 BOP 32.42 31.19 31.81 ABBP 32.49 31.66 32.07 AMean 31.74 A 30.90 B

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Varieties LSD≤0.05 = 0.8077, Seed priming LSD≤0.05 = 0.6818

218

Table 4.131b: Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30 MeanH-93 33.56 29.93 31.74 AF-87 32.78 29.01 30.90 BMean 33.17 A 29.47 B

Sowing time LSD≤0.05 = 0.8975, Varieties LSD≤0.05 = 0.8077

Table 4.132: Influence of seed priming on 1000-grain weight (g) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30

H-93 F-87 H-93 F-87Control 31.19 cd 29.92 efg 28.72 h 27.47 iHP 33.03 b 30.59 de 30.23 ef 29.32 ghOP 33.45 b 32.81 b 29.41 gh 29.57 fgBP 35.32 a 31.10 cd 31.60 c 29.81 efg

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time × Varieties × Seed priming LSD≤0.05 = 0.8167

Table 4.133: Analysis of variance for the influence of seed priming on grain yield and straw yield of barley under optimum and late sowing time


Grain yield Straw yield2014-15 2015-16 2014-15 2015-16


Error 1 3 0.0026 0.0026 0.1447 0.0686Varieties (V) 1 0.3615** 0.0798** 0.0298ns 0.5532ns

SD×V 1 0.0147* 0.0841** 0.2916ns 0.0329ns

Error 2 6 0.0031 0.0015 0.0710 0.1219Priming (T) 3 2.5372** 1.7752** 2.9967** 2.0697**

SD×T 3 0.0624** 0.1198** 0.2740** 0.2479*

V×T 3 0.0107* 0.0194** 0.1106ns 0.0326ns

SD×V×T 3 0.0146* 0.0093* 0.3605** 0.1424ns

Error 3 36 0.0034 0.0031 0.0528 0.0697Total 63


219

Table 4.134: Influence of seed priming on grain yield (t ha-1) of barley under optimum and late sowing time

Treatments 2014-15 2015-16November 30 December 30 November 30 December 30H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87

Control 2.75 g 2.65 h 2.13 j 1.99 k 2.67 gh 2.63 hi 1.98 k 2.00 kHP 3.29 d 3.13 e 2.51 i 2.46 i 3.01 d 2.87 e 2.33 j 2.39 jOP 3.85 a 3.64 b 2.93 f 2.70 gh 3.56 a 3.36 b 2.69 gh 2.55 iBP 3.69 b 3.42 c 2.77 g 2.71 gh 3.28 b 3.10 c 2.74 fg 2.80 ef


Table 4.135: Influence of seed priming on straw yield (t ha -1) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30

H-93 F-87 H-93 F-87Control 5.42 fg 5.48 fg 4.78 i 4.77 iHP 5.81 de 6.23 bc 5.48 fg 5.07 hiOP 6.40 abc 6.45 ab 6.07 cd 5.45 fgBP 6.63 a 6.48 ab 5.18 gh 5.51 ef


Table 4.136: Influence of seed priming on straw yield (t ha -1) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30 MeanControl 5.61 b 4.64 c 5.12 BHP 5.39 bc 4.69 c 5.04 BOP 6.13 a 5.40 bc 5.77 ABP 5.80 b 5.43 bc 5.61 AMean 5.73 A 5.04 B

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 0.2083, Seed priming LSD≤0.05 = 0.1893, Sowing time × Seed priming LSD≤0.05

= 0.2677

220

Table 4.137: Analysis of variance for the influence of seed priming on biological yield and harvest index of barley under optimum and late sowing time


Biological yield Harvest index2014-15 2015-16 2014-15 2015-16


Error 1 3 0.1311 0.0789 3.087 1.246Varieties (V) 1 0.5948* 0.2082ns 15.054* 25.756**

SD×V 1 0.1754ns 0.0129ns 5.966ns 7.209ns

Error 2 6 0.0789 0.1443 1.168 1.535Priming (T) 3 11.0172** 7.1492** 32.991** 47.100**

SD×T 3 0.3674** 0.5963** 5.433** 2.298ns

V×T 3 0.1667ns 0.0956ns 1.097ns 0.178ns

SD×V×T 3 0.4357** 0.1206ns 5.035** 4.010*

Error 3 36 0.0622 0.0810 0.851 1.054Total 63


Table 4.138: Influence of seed priming on biological yield (t ha -1) of barley under optimum and late sowing time (2014-15)

Treatments November 30 December 30H-93 F-87 H-93 F-87

Control 8.17 e 8.14 e 6.92 g 6.76 gHP 9.10 cd 9.36 c 7.98 e 7.53 fOP 10.24 ab 10.09 ab 9.00 d 8.15 eBP 10.32 a 9.89 b 7.95 e 8.21 e


Table 4.139: Influence of seed priming on biological yield (t ha -1) of barley under optimum and late sowing time (2015-16)

Treatments November 30 December 30 MeanControl 8.26 c 6.63 f 7.44 DHP 8.33 c 7.05 e 7.69 COP 9.59 a 8.02 cd 8.81 ABP 8.98 b 8.20 c 8.59 BMean 8.79 A 7.47 B

Sowing time LSD≤0.05 = 0.2235, Seed priming LSD≤0.05 = 0.2041, Sowing time × Seed priming LSD≤0.05

= 0.2886

Table 4.140: Influence of seed priming on harvest index (%) of barley under optimum and late sowing time

Treatments


H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 33.65 def 32.65 fg 30.89 h 29.42i 32.92 fg 31.30 hi 30.29 ij 29.75 jHP 36.15 b 33.48 ef 31.39 gh 32.74 f 35.95 abc 34.67 cde 33.98 def 33.05 fgOP 37.56 a 36.12 b 32.52 fg 33.12 f 36.77 ab 35.40 bcd 33.53 ef 31.88 ghBP 35.73 bc 34.52 cde 34.89 bcd 32.96 f 37.31 a 33.81 ef 33.40 ef 34.14 def


221

which was translated into greater number of grains, grain weight and yield under normal

and stressed conditions (Dolatabadian et al., 2013). Similar, results were reported by

Farooq et al. (2008a) that osmopriming with CaCl2 improved the grain yield and harvest

index of wheat under late sown field conditions by ameliorating the damaging effects of

chilling stress.

In present study, the improved grain yield and harvest index by endophytic

bacteria in biopriming under late sown conditions is attributed to improved number of

productive tillers and grains, and grain weight. The improved number of productive tillers

by biopriming is attributed to improved early seedling establishment and growth

promotion by endophytic bacteria (Santoyo et al., 2016). Moreover, biopriming improves

the water relations of plants, enhances chlorophyll synthesis, and improves

photosynthesis and chlorophyll photochemistry resulting in improved number of grains

and grain weight which ultimately leads to better grain yield (Belimov et al., 2009;

Naveed et al., 2014a; Gagné-Bourque et al., 2016). Similar, results were reported by

Naveed et al. (2014c) that endophytic bacterial Burkholderia phytofrmans strain PsJN

improved the photosynthesis, nutrients uptake, water relations, and yield and related traits

of wheat under drought stress.



Chlorophyll a content was significantly affected by sowing time and seed priming,

during both years; however, varieties did not differ significantly during 2014-15 but

significantly differed during 2015-16. Interaction between sowing time and varieties, and

varieties and seed priming was significant during 2014-15 but non-significant during

2015-16. However, interactions between sowing time and seed priming, and three way

interaction among sowing time, varieties and seed priming was significant, during both

years (Table 4.141). Chlorophyll a content was decreased by late sowing than optimum

sowing. The variety Haider-93 produced higher chlorophyll a content than Frontier-87.

Moreover, chlorophyll a content was improved by seed priming treatments in both

varieties at both sowing times, as compared to unprimed control. At optimum sowing,

biopriming and hydropriming of Haider-93 caused the great improvement in chlorophyll

a content during 2014-15 and 2015-16, respectively. However, at late sowing biopriming

of Haider-93 resulted in maximum increase in chlorophyll a content, during both years

(Table 4.142).

4.6.7.2. Chlorophyll b content222

A significant effect of sowing time was observed for chlorophyll a content, during

both years; seed priming significantly affected chlorophyll b content during 2014-15 but

did not affect during 2015-16. Tested barley varieties significantly differed, during both

years. Interactions between sowing time and varieties, and sowing time and seed priming

were non-significant, during both years. Interaction between varieties and seed priming

and three way interaction among sowing time, varieties and seed priming was significant,

during both years (Table 4.141). Late sowing partially caused a reduction in chlorophyll b

than optimum sowing. Chlorophyll b content in variety Haider-93 was higher than

Frontier-87. The seed priming treatments enhanced the chlorophyll b content in both

varieties at both sowing times, as compared to unprimed control. Chlorophyll b content

was improved most by biopriming of Haider-93 during 2014-15, while, by biopriming of

Frontier-87 during 2015-16. However, at late sowing biopriming and osmopriming of

Haider-93 was most effective in improving chlorophyll b content during 2014-15 and

2015-16, respectively (Table 4.143).

4.6.8. Discussion

Photosynthesis is extremely important for plants to keep the growth and

development in pace under stressed conditions. However, abiotic stresses cause

deleterious effects on photosynthesis by damaging the photosynthetic machinery and

inhibiting the biosynthesis of photosynthetic pigments (Prasad et al., 2011b). In present

study the late sowing caused a decrease in chlorophyll contents in both varieties of barley

which might be attributed to low temperature during early vegetative growth (Farooq et

al., 2008a). It has been observed that low temperature causes a decrease in the

biosynthesis of chlorophyll contents due to suppressed gene expression for chlorophyll

synthesis (Yang et al., 2005). Similarly, Ahmed and Fayyaz-ul-Hassan (2015) reported a

decrease in chlorophyll content in wheat under late sown conditions. However, in present

study, seed priming improved the chlorophyll contents in both barley varieties under

normal as well as late sown conditions. This might be attributed to the protective role of

seed priming through enhanced osmolytes accumulation and antioxidants activities under

stressed conditions (Chen and Arora, 2013).

In present study, osmopriming improvedd the chlorophyll contents, as compared

to unprimed control. It has been observed that osmopriming improves the protection of

cellular membranes and organelles from stress caused oxidative burst resulting in

improved chloroplast ultrastructure, chlorophyll synthesis, chlorophyll photochemistry

and photosynthesis (Dai et al., 2017; Abid et al., 2018). Moreover, Ca2+ regulates the 223

NADK2 gene which encodes for NAD+ in chloroplast and deletion or down regulation of

this gene results in decreased chlorophyll biosynthesis and photosynthesis (Hochmal et

al., 2015).

224

Table 4.141: Analysis of variance for the influence of seed priming on chlorophyll contents of barley under optimum and late sowing time



Replication (R) 3 0.00014 0.00001 0.00012 0.00025Sowing time (SD) 1 0.01960** 0.01756* 0.01210** 0.01210**

Error 1 3 0.00005 0.00107 0.00004 0.00013Varieties (V) 1 0.00010ns 0.01000** 0.00391** 0.00226*

SD×V 1 0.00490** 0.00006ns 0.00010ns 0.00090ns

Error 2 6 0.00020 0.00035 0.00022 0.00021Priming (T) 3 0.00524** 0.00257* 0.00142** 0.00021ns

SD×T 3 0.00088** 0.00289* 0.00016ns 0.00020ns

V×T 3 0.00382** 0.00064ns 0.00042* 0.00123**

SD×V×T 3 0.00208** 0.00408** 0.00029* 0.00055**

Error 3 36 0.00017 0.00074 0.00010 0.00012Total 63


Table 4.142: Influence of seed priming on leaf chlorophyll a content (mg g-1 FW) of barley under optimum and late sowing time

Treatments

2014-15 2015-16November 30 December 30 November 30 December 30H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87

Control0.27 b 0.26 bc 0.18 g 0.25 cd

0.30 abc 0.27 b-e 0.24 ef 0.21 f

HP 0.26 bc 0.27 b 0.21 f 0.24 de 0.33 a 0.27 b-e 0.25 de 0.25 deOP 0.26 bc 0.25 cd 0.26 bcd 0.22 ef 0.29 bcd 0.25 de 0.27 b-e 0.25 deBP

0.33 a 0.26 bc 0.27 bc 0.27 bc 0.27 b-e 0.31 ab0.30 abc 0.25 de


Table 4.143: Influence of seed priming on leaf chlorophyll b content (mg g-1 FW) of barley under optimum and late sowing time

Treatments 2014-15 2015-16November 30 December 30 November 30 December 30

H-93 F-87 H-93 F-87 H-93 F-87 H-93 F-87Control 0.13 de 0.14 cd 0.13 de 0.11 f 0.17 bc 0.16 c-f 0.16 c-f 0.14 gHP 0.17 ab 0.16 bc 0.14 cd 0.12 ef 0.19 ab 0.17 cd 0.15 d-g 0.14 gOP 0.17 ab 0.15 c 0.13 de 0.13 de 0.19 ab 0.18 bc 0.18 bc 0.13 hBP 0.18 a 0.15 c 0.15 c 0.12 ef 0.17 bc 0.20 a 0.15 d-g 0.15 efg


225

Similar to our results, Rehman et al. (2015) reported that seed priming with CaCl2 and

moringa leaf extract improved the leaf chlorophyll content under normal and late sown

conditions. In current study biopriming also improved the chlorophyll contents, as

compared to unprimed control, which might be due to endophytic bacteria that decreases

chlorophyll degradation by inhibiting the production of ethylene through production of

ACC deaminase enzyme rendering the plants stay green for longer periods (Dimpka et al.,

2009). Similarly, Nadeem et al. (2007) observed that seed inoculation of maize with ACC

deaminase containing Pseudomonas syringae, P. fluorescens and E. aerogenes improved

the proline, water relations and chlorophyll contents under normal and salt stressed

conditions.

4.6.9. Grain proximate analysis

4.6.9.1. Grain crude protein content

Sowing time and seed priming treatments significantly affected grain crude

protein content, during both years; barley varieties significantly differed during 2014-15

but did not differ significantly during 2015-16. Interaction between sowing time and

varieties was non-significant during 2014-15 but significant during 2015-16. Interaction

between sowing time and seed priming was non-significant, during both growing seasons.

Interaction between varieties and seed priming, and three way interaction among sowing

time, varieties and seed priming was significant during 2014-15 but non-significant

during 2015-16 (Table 4.144). Grain crude protein content was decreased by late sowing

than optimum sowing. The variety Haider-93 produced more grain protein content than

Frontier-87. The seed priming treatments improved the grain crude protein content of

both varieties at both sowing times, as compared to unprimed control. During 2014-15,

osmopriming of Haider-93 and biopriming of Frontires-87 led to maximum increase in

grain crude protein content at early and late sowing, respectively. During 2015-16, late

sowing decreased the protein content while seed priming improved the grain protein

content. Moreover, at optimum sowing Haider-93 produced more grain protein content

while at late sowing Frontier-87 produced more grain protein content (Tables 4.145,

4.146b).

4.6.9.2. Grain starch content

The grain starch content was significantly affected by sowing time and seed

priming; however, barley varieties did not differ significantly, during both years.

Similarly, the interactions between sowing time and varieties, sowing time and seed

priming, varieties and seed priming, and three way interaction among sowing time, 227

varieties and seed priming was non-significant, during both years (Table 4.144). Grain

starch content was lowered by late sowing as compared to optimum sowing, during both

years. However, seed priming treatments improved the grain starch content, as compared

to unprimed control. The greatest improvement was caused by biopriming. However,

osmopriming and hydropriming produced similar results, during both years (Table 4.147).

4.6.10. Discussion

Grain quality in terms of protein and starch contents was negatively affected by

late sowing of barley. This might be attributed to decreased photosynthesis, nutrient

uptake and plant growth by late sowing. It has been observed that early planted barley

have more grain protein contents due to healthier plants with longer root systems that

cause higher uptake of residual nitrogen and have more time for grain filling as compared

to late sowing (Ozturk et al., 2008). Similarly, Seleiman et al. (2011) reported that late

sowing reduced the grain carbohydrates, as compared to optimum sowing. Moreover, late

sowing exposes the plants to terminal heat stress that shortens the grain development

period as a result poor quality and shriveled grains are achieved (Ehdaie et al., 2006;

Kaur and Behl, 2010; Farooq et al., 2011). In late sowing, high temperature during grain

development caused an increase in the ratio of amylose to amylopectin but decreased the

ratio of glutenin to gliadin ratio that negatively affected the dough elasticity (Hurkman et

al., 2003).

In present study, seed priming improved the grain protein as well starch contents

of barley under normal and late sown conditions. The improved grain protein and starch

contents by seed priming might be attributed to better chlorophyll contents, enhanced

LAI, CGR and improved grain filling rate as observed in present study. Similar results

were reported by Mahboob et al. (2015) that seed priming with CaCl2, salicylic acid and

moringa leaf extract improved the crude protein content in maize under normal and late

sowing conditions by enhancing LAD and NAR. Seed priming might have improved the

grain starch content by decreasing the damaging effects of high temperature during grain

filling period in late sown barley because starch synthase enzyme which is involved in

starch synthesis and accumulation is highly sensitive to high temperatures and its activity

is decreased by temperature exceeding 20°C (Keeling et al., 1994). In present study, the

improved grain protein and starch contents may be attributed to endophytic bacteria

which enhances nutrient uptake and assimilation (Santoyo et al., 2016), and enhances

photosynthesis and nitrate reductase activity (Marcos et al., 2016).

4.6.11. Economic and marginal analysis228

The economic analysis revealed that late sowing caused a reduction in net benefits

and BCR in both barley varieties. However, varieties performed differently regarding

grain yield and net benefits. Haider-93 gave higher net benefits and BCR under both

normal and

229

Table 4.144: Analysis of variance for the influence of seed priming on grain crude protein and starch contents of barley under optimum and late sowing time


Grain crude protein content Grain starch content2014-15 2015-16 2014-15 2015-16

Replication (R) 3 0.064 4.054 37.154 39.880Sowing time (SD) 1 3.730** 7.798** 384.356* 405.720*

Error 1 3 0.017 0.021 29.294 27.196Varieties (V) 1 0.447* 0.656ns 2.016ns 5.108ns

SD×V 1 0.046ns 1.243* 53.071ns 34.810ns

Error 2 6 0.070 0.155 33.527 32.816Priming (T) 3 1.962** 3.236** 102.793* 120.098*

SD×T 3 0.050ns 0.283ns 23.924ns 33.001ns

V×T 3 0.621** 0.113ns 32.832ns 42.239ns

SD×V×T 3 0.254* 0.346ns 32.413ns 22.091ns

Error 3 36 0.088 0.315 33.419 33.589Total 63


Table 4.145: Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2014-15)Treatments November 30 December 30

H-93 F-87 H-93 F-87Control 10.65 de 10.69 cde 10.16 fg 10.04 gHP 11.47 a 11.17 ab 10.96 bcd 10.53 efOP 11.48 a 10.97 bcd 11.11 abc 10.46 efgBP 11.40 a 11.29 ab 10.62 de 11.37 ab


Table 4.146a: Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2015-16)Treatments November 30 December 30 MeanH-93 11.23 a 10.26 c 10.74F-87 10.75 b 10.33 c 10.54Mean 10.99 A 10.29 B

Values sharing same case letter do not differ significantly at p≤0.05; H-93 = Haider-93, F-87 = Frontier-87, HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 0.1148, Sowing time × Varieties LSD≤0.05 = 0.3410

230

Table 4.146b: Influence of seed priming on grain crude protein content (%) of barley under optimum and late sowing time (2015-16)Treatments H-93 F-87 MeanControl 10.04 10.02 10.03 CHP 10.86 10.56 10.71 BOP 11.30 10.93 11.11 ABP 10.77 10.66 10.72 ABMean 10.74 10.54

Seed priming LSD≤0.05 = 0.4023

Table 4.147: Influence of seed priming on grain starch content (%) of barley under optimum and late sowing time

Treatments 2014-15 2015-16November 30 December 30 Mean November 30 December 30 Mean

Control 57.76 54.88 56.32 B 58.11 54.80 56.45 BHP 59.06 55.89 57.47 AB 59.95 57.27 58.61 AOP 60.54 56.46 58.50 A 60.74 56.40 58.57 ABP 61.05 57.24 59.14 A 61.57 57.51 59.54 AMean 59.60 A 56.12 B 60.09 A 56.49 B

Values sharing same case letter do not differ significantly at p≤0.05; HP = hydropriming, OP = osmopriming, BP = biopriming; Sowing time LSD≤0.05 = 4.3061 (2014-15) and 4.1491 (2015-16), Seed priming LSD≤0.05 = 4.1451 (2014-15) and 0.0443 (2015-16)

231

late sowing conditions which was related to higher grain yield than Frontier-87.

Moreover, seed priming improved the net benefits and BCR of both varieties under both

sowing times by improving the grain yield despite of higher cost of production by seed

priming treatments than control and hydropriming. However, at optimum sowing time,

highest net returns and BCR was recorded by osmopriming of Haider-93 and it was

followed by osmopriming of Frontier-87. Whereas, at late sowing, osmopriming of

Haider-93 gave highest net returns and BCR, and it was followed by biopriming of

Frontier-87 (Table 4.148).

The marginal analysis revealed that MRR was decreased by late sowing in both

varieties. Haider-93 gave higher MRR than Frontier-87. Moreover, osmopriming gave the

highest MRR in early sown crop while hydropriming was superior in late sown crop.

Biopriming gave the MRR in both sowing times but it could not exceed hydropriming and

osmopriming. In optimum sowing, osmopriming of Haider-93 gave highest MRR and it

was followed by osmopriming of Frontier-87. However, in late sowing, hydropriming

Haider-93 produced highest MRR and it was followed by hydropriming of Frontier-87

(Table 4.149).

4.6.12. Discussion

In present study, late sowing of both varieties substantially decreased net returns

and BCR by significantly decreasing the grain and straw yield due to poor plant growth

and development. However, Haider-93 gave more net returns and BCR than Frontier-87

which was associated with higher grain yield due to more tolerance to adverse climatic

conditions due to late sowing. Moreover, seed priming especially osmopriming improved

the net returns under optimum and late sowing conditions, as compared to unprimed

control. Seed priming treatments produced more net returns despite of high initial cost

which was compensated by higher grain yield. Aune et al. (2011) observed increase in

economic returns by seed priming in sorghum and pearl millet owing to increased yield

and concluded that it is a low cost, low risk technique which can be adopted by poor

farmers. Similarly, Jafar et al. (2012) reported improvement in economic returns by

osmopriming with CaCl2 under normal as well as saline conditions indicating that it has

the potential to improve the grain yield as well as economic returns in a range of growing

conditions. In conclusion seed priming can be adopted to improve the crop performance

and economic returns under optimum as well as late sown conditions.

232

Table 4.148: Economic analysisTreatments Grain

yield(t ha-1)

Adjusted grain yield

(t ha-1)

Straw yield

(t ha-1)

Adjusted straw yield

(t ha-1)

Gross income

(Rs.)

Fixed cost(Rs.)

Variable cost(Rs.)

Total cost(Rs.)

Net benefits

(Rs.)

BCR

November 30 H-93 Control 2.71 2.44 5.43 4.89 128029 66902 9747 76649 51380 1.67HP 3.15 2.84 5.59 5.03 138556 66902 11590 78492 60064 1.77OP 3.70 3.33 6.26 5.64 161459 66902 16727 83629 77830 1.93BP 3.48 3.14 6.08 5.47 152757 66902 16541 83443 69314 1.83

F-87 Control 2.64 2.38 5.63 5.06 120340 66902 9502 76404 43937 1.58HP 3.00 2.70 5.82 5.24 134177 66902 11050 77951 56225 1.72OP 3.50 3.15 6.29 5.66 154300 66902 16000 82902 71399 1.86BP 3.25 2.93 6.27 5.65 145334 66902 15711 82613 62722 1.76

December 30 H-93 Control 2.05 1.85 4.67 4.20 94948 66902 7395 74297 20652 1.28HP 2.42 2.18 5.00 4.50 109541 66902 8953 75855 33687 1.44OP 2.81 2.53 5.71 5.14 126706 66902 13502 80403 46303 1.58BP 2.75 2.48 5.31 4.78 123003 66902 13909 80811 42193 1.52

F-87 Control 1.99 1.79 4.75 4.27 93128 66902 7176 74077 19051 1.26HP 2.43 2.18 4.95 4.46 109614 66902 8982 75883 33731 1.44OP 2.63 2.36 5.46 4.91 119071 66902 12852 79754 39317 1.49BP 2.75 2.48 5.46 4.91 123671 66902 13911 80813 42859 1.53

H-93: Haider-93, F-87: Frontier-87, HP: Hydropriming, OP: osmopriming, BP: Biopriming, BCR: Benefit cost ratio

233

Table 4.149: Marginal analysisTreatments Variabl

e cost (Rs.)

Marginal variable cost (Rs.)

Net field

benefits (Rs.)

Marginal net field benefits

(Rs.)

Marginal rate of return

(%)November 30 H-

93Control 9747 - 118282 - -HP 11590 1843 126966 8684 471BP 16541 4951 136216 9250 187OP 16727 186 144732 8516 4578

F-87 Control 9502 - 110838 - -HP 11050 1548 123127 12289 794BP 15711 4661 129623 6496 139OP 16000 289 138300 8677 3001

December 30 H-93

Control 7395 - 87553 - -HP 8953 1558 100588 13035 837OP 13502 4549 113205 12616 277BP 13909 407 109094 - D

F-87 Control 7176 - 85953 - -HP 8982 1806 100632 14680 813OP 12852 3871 106219 5587 144BP 13911 1059 109760 3541 334

H-93: Haider-93, F-87: Frontier-87, HP: Hydropriming, OP: osmopriming, BP: Biopriming

234

CHAPTER 5

SUMMARY

Studies on evaluating the potential of seed priming in improving the performance

of barley varieties under late sown and abiotic stress conditions was evaluated at green

house and field of University of Agriculture, Faisalabad, and glass house of Texas A&M

University, USA. In pot experiments, the potential of seed priming in improving the

tolerance of barley against drought, salinity and terminal heat stress was explored. In

hydroponics experiments effect of seed priming on performance of barley under osmotic,

salt and Cd stress was evaluated. The pot and hydroponics experiments were conducted

by using completely randomized design (CRD) with factorial arrangement and four

replications, except the experiment conducted to determine effect of seed priming on

barley under terminal heat stress, in which six replications were used. Data were collected

regarding emergence, growth, yield, photosynthesis, chlorophyll fluorescence,

chlorophyll contents, osmolytes, lipid peroxidation, ion toxicity, water relations and grain

nutrient contents. In field experiment, the influence of seed priming on the performance

of barley under optimum and late sown conditions was explored. The experiment was

conducted with randomized complete block design (RCBD) with split-split plot

arrangement having four replications and the net plot size of 6 m × 2.7 m. Data regarding

emergence, growth, allometry, grain filling, yield and related traits, and grain protein and

starch contents were collected using standard procedures. Data were analyzed statistically

using the Fisher’s analysis of variance (ANOVA) technique and the least significant

difference (LSD) test at 5% probability was used for comparison of treatments’ means.

Economic analysis was carried out to assess the economic feasibility. Brief description of

results from different experiments is given below:

Experiment 1: Potential role of seed priming in improving the resistance against

drought in barley

Seeds of two barley varieties (Haider-93 and Frontier-87) primed with water

(hydropriming), CaCl2 (osmopriming) and Enterobacter sp. strain FD17 (biopriming)

were sown in pots. Dry seed was taken as control. After seedling establishment, drought

levels (80, 60 and 40% water holding capacity) were imposed. Drought stress decreased

the plant growth, yield, chlorophyll contents, cell membrane stability, disturbed water

relations and decreased grain nutrient contents while enhanced osmolytes accumulation

235

and lipid peroxidation in both varieties of barley and the deleterious effects were

increased with increase in its severity. However, the negative effects of drought stress

were more pronounced in Frontier-87 than Haider-93. Seed priming improved the

emergence, plant height, leaf area, number of productive tillers, number of grains per

spike, 100-grain weight, grain yield, harvest index and chlorophyll contents under well-

watered and drought stress conditions, as compared to unprimed control. Moreover, seed

priming improved the water relation traits viz. leaf relative water content, leaf water

potential, leaf osmotic potential and leaf pressure potential, and cell membrane stability

by enhanced accumulation of osmolytes i.e. phenolics, total soluble proteins, free proline

and glycine betaine, and decreased lipid peroxidation in both barley varieties under severe

drought stress, as compared to unprimed control. The order of improvement in yield and

related traits by seed priming treatments was biopriming > osmopriming > hydropriming

> control. In addition, biopriming effectively improved the grain Zn, Mn and B contents

under well-watered and drought conditions, as compared to unprimed control.

Experiment 2: Potential role of seed priming in improving the salt resistance in

barley

In this experiment seeds of two barley varieties (Haider-93 and Frontier-87)

primed with water (hydropriming), CaCl2 (osmopriming) and Enterobacter sp. strain

FD17 (biopriming) were sown in pots. Dry seed was taken as control. After seedling

establishment salinity levels (50, 100 and 150 mM NaCl) were imposed. Salinity caused a

reduction in growth, yield, biosynthesis of chlorophyll, perturbed water relations and

decreased grain nutrient contents while exalted osmolytes, MDA and Na accumulation in

barley. The damaging effect of salinity was increased with increase in its severity.

Although salinity imposed its deleterious effects on both varieties but its negative effects

were more prominent on Frontier-87. Seed priming improved the emergence, plant

growth, number of productive tillers, number of grains per spike, 100-grain weight, and

grain yield and harvest index in both varieties under salt stress, as compared to unprimed

control. Seed priming improved the biosynthesis of chlorophyll a and b, leaf relative

water content, leaf water potential, leaf osmotic potential and leaf pressure potential by

exaggerated accumulation of osmolytes such as phenolics, total soluble proteins, free

proline and glycine betaine contents in both varieties under salt stress, as compared to

unprimed control. Cell membrane stability was improved by seed priming through

decreased lipid peroxidation under salt stress. Furthermore, seed priming decreased the

ion toxicity by lowering the Na content while increasing the K content in both barley 236

varieties, as compared to unprimed control. Barley performance regarding yield and

related traits under moderate salinity was improved the most by biopriming while under

severe salinity by osmopriming. Moreover, biopriming improved the grain Zn, Mn and B

contents under normal and salt stress conditions, as compared to unprimed control.


osmotic and salt stresses in barley

The experiment was carried out in hydroponics. Seedlings of two barley varieties

(Haider-93 and Frontier-87) primed with water (hydropriming), CaCl2 (osmopriming) and

Enterobacter sp. strain FD17 (biopriming) were raised in sand filled polythene bags. Dry

seed was taken as control. After seedling establishment the seedlings were transplanted in

hydroponics, and osmotic (-0.8 MPa using PEG) and ionic (-0.8 MPa using NaCl)

stresses were imposed. Osmotic and salt stress decreased the seedling growth, biomass

production, and chlorophyll a and b contents while increased the accumulation of

osmolytes and MDA in both varieties. Salt stress also caused ion toxicity through

enhanced accumulation of Na in barley plants. However, more reductions in biomass

were observed in Frontier-87. Seed priming improved the shoot and root length, and fresh

and dry biomass, chlorophyll a and b contents, and accumulation of phenolics, total

soluble proteins, free proline and glycine betaine while reduced the MDA content under

both osmotic and salt stress, and Na content under salt stress, as compared to unprimed

control. Among all seed priming treatments the biopriming was most effective in

improving barley performance under osmotic stress while osmopriming was superior in

improving barley stress tolerance against salt stress.


cadmium stress in barley

The experiment was carried out in hydroponics. Seedlings of two barley varieties

(Haider-93 and Frontier-87) primed with water (hydropriming), CaCl2 (osmopriming) and

Enterobacter sp. strain FD17 (biopriming) were raised in sand filled polythene bags. Dry

seed was taken as control. After seedling establishment the seedlings were transplanted in

hydroponics, and Cd toxicity stress levels (viz. 0, 8 and 12 mg L-1 water) were imposed.

Cadmium stress reduced seedling growth and biomass production, chlorophyll

biosynthesis and increased the osmolytes, MDA and Cd accumulation in tested barley

varieties depending on its severity. However, reductions in biomass of Haider-93 were

less as compared to Frontier-87. Furthermore, seed priming improved the shoot length

root length, and shoot and root fresh and dry biomass, chlorophyll a and b contents, 237

phenolics, total soluble proteins, free proline and glycine betaine contents while

decreased MDA and Cd contents in both varieties under Cd toxicity stress, as compared

to unprimed control. The order of improvement in barley stress tolerance was biopriming

> osmopriming > hydropriming > control.


terminal heat stress in barley

Seeds of USA cultivar Solum were primed with water (hydropriming) and CaCl2

(osmopriming), and sown in pots. Dry seed was taken as control. At reproductive stage

two levels of heat stress viz. control (25/18°C day/night) and high temperature (35/25°C

day/night) were applied. Terminal heat stress decreased the plant growth, yield,

photosynthesis, chlorophyll fluorescence, chlorophyll contents and cell membrane

stability while increasing lipid peroxidation, as compared to control. However, seed

priming improved plant height, number of productive tillers, number of grains per spike,

100-grain weight, grain yield and harvest index under terminal heat stress, as compared to

unprimed control. Moreover, seed priming improved the photosynthesis by enhancing

stomatal conductance, intercellular CO2 concentration, transpiration and CUE, as

compared to unprimed control. Chlorophyll contents, QY and ETR was improved by seed

priming which led to enhanced photosynthetic efficiency of barley under normal and

terminal heat stress conditions. Seed priming also improved the cell membrane stability

by enhancing the phenolics contents and decreasing the lipid peroxidation as compared to

unprimed control, under heat stress. The order of improvement in growth, yield

photosynthesis and stress tolerance was osmopriming > hydropriming > control.

Experiment 6: Influence of seed priming on the productivity of late sown barley

Seeds of two barley varieties (Haider-93 and Frontier-87) primed with water

(hydropriming), CaCl2 (osmopriming) and Enterobacter sp. strain FD17 (biopriming)

were sown in field at November 30 and December 30. Dry seed was taken as control.

Late sowing decreased emergence, growth, yield, dry matter accumulation, grain filling

duration, chlorophyll contents, and grain protein and starch contents in both barley

varieties, as compared to optimum sowing time. Haider-93 performed better regarding

growth and yield under late sown conditions than Frntier-87. Seed priming improved the

emergence, plant growth, LAI, TDM accumulation, CGR, grain filling rate, yield and

related traits, and grain protein and starch contents under both optimum and late sowing,

ascompared to unprimed control. The greatest improvement in grain yield and harvest

index was caused by osmopriming followed by biopriming. The economic analysis 238

revealed that late sowing decreased the economic returns and BCR which was improved

by seed priming treatments. Among all, biopriming caused maximum improvement in

BCR under both optimum and late sown conditions; while, highest MRR was produced

by osmopriming under optimum sowing time and hydropriming under late sowing.

Conclusion

Abiotic stresses and late sowing decreased the plant growth and yield of barley by

negatively affecting the plant physiological processes and grain filling attributes.

However, seed priming effectively improved the growth and productivity of barley

varieties under stressed conditions by improving the osmolytes accumulation, chlorophyll

contents, water relations, nutrient relations, photosynthesis, grain filling rate and

decreasing the lipid peroxidation under stressed conditions.

239

Future research thrusts

Proteomic and metabolomic basis of seed priming in inducing resistance against

abiotic stresses should be investigated

Influence of seed priming especially biopriming on root growth traits should be

explored

Enzymes responsible for grain formation (alpha-amylase, starch synthase and starch

synthetase) should be investigated under late sown conditions

240

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growth, water relations and photosynthesis. Emir. J. Food Agric. 24: 57-72.

275

Appendix 1: Fixed cost (Experiment 6)Sr.

No.

Operation/input No./Amount/

Quantity per ha

Rate/unit

(Rs.)

Cost/ha

(Rs.)

1 Land preparation operations

Ploughing 2 1475 2950

Planking 1 740 740

2 Seed and sowing operations

Seed 75 40 3000

Drill charges 1 1477 1477

3 Fertilizer cost

Fertilizer bags

Urea 1.6 1850 2923

DAP 1.5 3750 5700

SOP 1.0 2370 2370

Transportation charges 4.1 20 82

Fertilizer application charges 1 man day 400 400

4 Irrigation charges

Canal water charges - - 200

Water channel cleaning 1 man per day 400 400

5 Plant protection measures

Herbicide 2.5 L 650/L 1625

Application charges 1 man per 1/2 day 400 200

6 Markup on investment 9% annual 27830 2505

7 Land rent @ Rs. 62500 per anum 5 months 5208 26040

8 Agricultural income tax for 5 months - - 40

9 Harvesting charges 7.5 mounds 1600 12000

10 Artisan charges 10 kg 40 1000

11 Marketing cost - - 1500

12 Management cost 5 months 350 1750

Gross cost - - 66902

276

Appendix 2: Variable cost (Experiment 6)Treatments Cost of seed

priming (Rs.)Threshing

charges (Rs.)Total variable

cost (Rs.)

November 30 H-93 Control 0 9747 9747HP 250 11340 11590BP 3400 13327 16727OP 4000 12541 16541

F-87 Control 0 9502 9502HP 250 10800 11050BP 3400 12600 16000OP 4000 11711 15711

December 30 H-93 Control 0 7395 7395HP 250 8703 8953OP 3400 10102 13502BP 4000 9909 13909

F-87 Control 0 7176 7176HP 250 8732 8982OP 3400 9452 12852BP 4000 9911 13911

H-93: Haider-93, F-87: Frontier-87, HP: Hydropriming, OP: osmopriming, BP: Biopriming

277

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