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International ScientificJournal
VOL. 69_2016ISSN 2545-4315
INTERNATIONAL SCIENTIFIC JOURNALJOURNAL OF AGRICULTURAL, FOOD AND ENVIRONMENTAL SCIENCES
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Published by: “Ss. Cyril and Methodius" University in Skopje,
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EDITORIAL BOARD
Еditor in Chief
Vjekoslav Tanaskovikj, Skopje, MacedoniaKocho Porchu, Skopje, Macedonia
Associate Editor
Snezana Jovanovic, Belgrade, SerbiaJovica Vasin, Novi Sad, SerbiaRadmila Stikić, Belgrade, SerbiaBiljana Škrbić, Novi Sad, SerbiaAna Marjanovic Jeromel¸ Novi Sad, SerbiaBojan Srdljević, Novi Sad, SerbiaZoran Rajić, Belgrade, SerbiaJasmina Havranek, Zagreb, CroatiaMirjana Herak Ćustić, Zagreb, CroatiaVlasta Piližota, Osijek, CroatiaIvo Tursich, Zagreb, CroatiaDarko Vončina, Zagreb, CroatiaZlatan Sarić, Sarajevo, B&HJosip Ćolo, Sarajevo, B&HMuhamed Brka, Sarajevo, B&HVelibor Spalević, Podgorica, MontenegroBozidarka Marković, Podgorica, MontenegroNazim Gruda, Bonn, GermanyVenelin Roychev, Plovdiv, BulgariaNasya Tomlekova, Plovdiv, BulgariaIrena Rogelj, Ljubljana, SloveniaDrago Kompan, Ljubljana, SloveniaMichael Murković, Graz, AustriaHristaq Kume, Tirana, AlbaniaSonja Srbinovska, Skopje, MacedoniaMarjan Kiprijanovski, Skopje, MacedoniaMarina Stojanova, Skopje, MacedoniaBiljana Kuzmanovska, Skopje, MacedoniaMirjana Jankulovska, Skopje, MacedoniaDragi Dimitrievski, Skopje, Macedonia
JOURNAL OF AGRICULTURAL, FOOD AND ENVIRONMENTAL SCIENCESAddress
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Издава:Универзитет „Св. Кирил и Методиј“ во Скопје,Факултет за земјоделски науки и храна Скопје
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УРЕДУВАЧКИ ОДБОР
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Вјекослав Танасковиќ, Скопје, МакедонијаКочо Порчу, Скопје, Македонија
Уредници
Снежана Јованович, Белград, СрбијаЈовица Васин, Нови Сад, СрбијаРадмила Стикич, Белград, СрбијаБилјана Шкрбич, Нови Сад, СрбијаАна Марјанович Јеромел, Нови Сад, СрбијаБојан Срдљевич, Нови Сад, СрбијаЗоран Рајич, Белград, СрбијаЈасмина Хавранек, Загреб, ХрватскаМирјана ХеракЧустич, Загреб, ХрватскаИво Туршич, Осијек, ХрватскаВласта Пилижота, Загреб, ХрватскаДарко Вончина, Загреб, ХрватскаЗлатан Сарич, Сарајево, БиХЈосип Чоло, Сарајево, БиХМухамед Брка, Сарајево, БиХВелибор Спалевич, Подгорица, Црна ГораБожидарка Маркович, Подгорица, Црна ГораНазим Груда, Бон, ГерманијаВенелин Ројчев, Пловдив, БугаријаНасиа Томлекова, Пловдив, БугаријаИрена Рогељ, Љубљана, СловенијаДраго Компан, Љубљана, СловенијаМихаел Муркович, Грац, АвстријаХристаќ Куме, Тирана, АлбаниаСоња Србиновска, Скопје, МакедонијаМарјан Кипријановски, Скопје, МакедонијаМарина Стојанова, Скопје, МакедонијаБилјана Кузмановска, Скопје, МакедонијаМирјана Јанкуловска, Скопје, МакедонијаДраги Димитриевски, Скопје, Македонија
Адреса(Редакција)Универзитет „Св. Кирил и Методиј“ во СкопјеФакултет за земјоделски науки и храна Скопјеп. фах. 297, МК1000 Скопје,Република Македонија
*THE AUTHORS ARE RESPONSIBLE FOR THE CONTENT AND FOR THE LANGUAGE OF THEIR CONTRIBUTION
Journal of Agricultural, Food and Environmental Sciences
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JAFES, Vol 69 (2016)
TABLE OF CONTENTS
B. Popovski, M. Popovska CHEMICAL CONTENT OF FRUITS OF SOME PERSPECTIVE STRAWBERRY VARIETIES CULTIVATED ON OPEN FIELD 1-7 L. Lepaja, E. Kullaj, K. Lepaja, N. Krasniqi INFLUENCE OF RDI, MULCHING AND THEIR COMBINATIONS ON NUTRIENT CONTENT OF YOUNG "WILLIAM" PEAR STORED IN BASEMENT 8-13 M. Popovska, B. Popovski MORPHOMETRIC CHARACTERISTICS ON SELECTED CHERRY PLANTS, A PRIMARY EFFECT PRODUCT OF GAMMA RADIATION (Cz137) 14-20 V. Avdiu, F. Thomaj, S. Sylanaj, E. Kullaj, K. Lepaja EFFECT OF GROW REGULATORS ON THE STOMATA CONDUCTANCE IN THE APPLE TREE 21-25 A. Markovski, T. Arsov, V. Gjamovski ROOTING OF HAZELNUT (CORYLUS AVELLANA L.) VARIETIES HARDWOOD CUTTINGS 26-31 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj SOIL EROSION EVALUATION IN THE RASTOCKI POTOK WATERSHED OF MONTENEGRO USING THE EROSION POTENTIAL METHOD 32-40 G. Patamanska WATER RESOURCES PLANNING MODELING FOR EFFICIENT MANAGEMENT OF IRRIGATION CANAL 41-45 C. Berar, M. Silivasan, E. Pet, A. Groszler, C. Tota, D. Camen THE MANAGEMENT AND CAPITALIZATION OF THE LANDSCAPING POTENTIAL OF THE CRUCII SQUARE FROM TIMISOARA CITY 46-52 H. Knüpffer PLANT GENETIC RESOURCES FROM THE BALKAN PENINSULA IN THE WORLD’S GENEBANKS 53-68
Journal of Agricultural, Food and Environmental Sciences
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JAFES, Vol 69 (2016)
H. Kirchev, N. Semkova INVESTIGATION ON SOME MORPHOLOGICAL AND BIOLOGICAL CHARACTERISTICS OF EINKORN WHEAT (T. MONOCOCCUM L.) DEPENDING ON NITROGEN FERTILIZATION 69-74 Doneva S., Yordanova D., Daskalova N., Spetsov P. POLYMORPHISM OF ENDOSPERM PROTEINS IN AMPHIDIPLOIDS WITH THE G GENOME OF Triticum timopheevii (Zhuk.) 75-80 M. T. Stojanova, L. Karakashova, H. Poposka, I. Ivanovski, B. Knezevic THE INFLUENCE OF FOLIAR FERTILIZATION WITH ORGANIC FERTILIZERS ON THE YIELD AND THE CHEMICAL CONTENT OF POTATOES GROWN IN STRUMICA REGION 81-86 M. Yarnia, M. B. K.Benam, E. Farajzadeh, V. Ahmadzadeh, N. Nobari THE EVALUATION OF GRAIN AND OIL PRODUCTION, SOME PHYSIOLOGICAL AND MORPHOLOGICAL TRAITS OF AMARANTH ‘CV. KONIZ’ AS INFLUENCED BY THE SALT STRESS IN HYDROPONIC CONDITIONS 87-93 N. Mrkovački, D. Bjelić, D. Jošić, I. Đalović YIELD RESPONSE OF FIVE MAIZE HYBRIDS TO INOCULATION WITH RHIZOBACTERIA 94-97 D. Cvetkovic, D. Boshev, Z. Dimov, S. Ivanovska, M. Jankulovska YIELD AND YIELD COMPONENTS ON SOME WHEAT VARIETIES GROWN IN ALEKSINAC REGION 98-105
Journal of Agricultural, Food and Environmental Sciences
UDC 634.75:581.19(497.7)
Original scientific paper
____________________________________________________________________________________________________
CHEMICAL CONTENT OF FRUITS OF SOME PERSPECTIVE STRAWBERRY
VARIETIES CULTIVATED ON OPEN FIELD
B. Popovski1*, M. Popovska2
1Faculty of Agricultural Sciences and Food, Ss. Cyril and Methodius University,
Skopje, Republic of Macedonia 2Institute of Agriculturae, Ss. Cyril and Methodius University, Skopje, Republic of Macedonia
*corresponding author: bojanp@zf.ukim.edu.mk
Abstract
This research contains results concerning the chemical composition of 15 introduced varieties of
strawberries in Macedonia: Idea, Camarosa, Belrubi, Evita, Honeoye, Tethis, Chandler, Onda,
Miranda, Paros, Elsanta, Eris, Madalene, Favette and Marmolada and two controll varieties:
Pocahontas and Sengasengana. The analysis has been conducted on the following substances: soluble
dry matter, sugars (total and reductive), acids, pulp’s pH, sugar/acid ratio, vitamin C, anthocyanins
and mineral matters. The percentage of soluble dry matter is between 8.5% with the Eris variety and
11% with Idea. Idea has the highest concentration of sugars with 8.80% of total and 6.16% of
reductive sugars. Eris has the lowest concentration of 6.80% total and 4.76% reductive sugars. Lowest
amount of acids is 0.79% (Onda and Madalene) and highest is 0.94% (Evita). The range of pH value
goes from 3.5 (Tethis) to 4.2 (Chandler and Pocahontas). The Marmolada variety has the highest
sugar/acid ratio with 10.4 and Evita has the lowest of 8.1. The concentration of vitamin C goes
between the range of 72.49mg% (Pocahontas) and 113.73mg% (Camarosa). The anthocyanins
concentration with the Favette is to be the lowest with 37.06mg/kg, whereas the Elsanta reaches the
highest content with 48.88mg/kg. The content of mineral matter within the fruit is between 0.52%
(Chandler and Onda) and 0.94% (Tethis).
Key words: Fragariaananassa Duch., strawberry, variety, chemical content, open field.
Introduction
The strawberry plant fruit poses an attractive
fruit which is rich in important and essential
nutricious matter (Wozniak et al., 1997). The
fruit is composed of a wide variety of organic
and mineral substances responsible for its high
nutritional, medicinal, and dietary value
(Stančević, Stanisavljević 1986;Gavrilović,
1986;Благојевиќ, 1998). The chemical
composition points towards a real employable,
alimentary, and technological value of the
strawberries (Поповски, 2008).
The main nutritional substances within the
fruit are soluble dry matters, sugars (glucose,
fructose, and sucrose) as well as organic acids
which account for the refreshing flavour
strawberries are known for. The increased
number of sugary components results in a less
notable citrusy flavor. Strawberries are a
known source of various numbers of other
chemical substances with protective anti-
oxydant characteristics, such as vitamins and
couloured matter, vitamin C and antocyanins
in particular. (Mratinić-Nenadović, 1989,2003,
2006; Milivojević, 2003).
The chemical composition of the strawberry
fruit varies greatly within the mass of varieties.
Afore all, its composition depends on the
variety, degree of ripeness of the fruit, the
fecundity, the growth system, applied agro-
technical and protective measures for during
the produce period, climate factors and the
like.(Kiprijanovski, 2001; Milivojević, 2003;
Popovski, 2008).
The aim of this study is a firm analysis of the
chemical composition of the fruit of 17
different varieties of strawberries laid with a
modern technology under a polyethylenefoil in
an open field. The growing of strawberries out
on an open field has been a dominant trend
within the Skopje region and has been widely
adopted within the entire region of the
Republic of Macedonia.
2 B. Popovski, M. Popovska
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JAFES, Vol 69, (2016)
Materials and methods
The analysis was performed in an
experimental orchard of the Agricultural
Institute in Skopje during 2002–2004. The
experiment was established in the second half
of September 2001, with a frigo virus-free
planting material, in three repetitions in a line,
consisting of 30 plants of each repetition. The
cultivation system was an open field, in two-
row lines (long plots method), on black
polyethylene foil at distance of 40x30 cm. The
plants were irrigated with controlled quantities
of water, through the drop-by-drop system.
The soil was homogeneous, alluvial,
possessing a good water-air regime, suitable
for strawberry growing. The agrochemical
composition of the soil consisted of 0.93-
2.05% hummus, 9.32-10.38mg/100g N, 14.3-
21.1mg/100g P2O5, 10.06-22.2 mg/100g K2O,
6.49-7.25% CaCO3, pH 7.93-8.19 in H2O and
7.4-7.63 in KCl. Based on the analyses, the
soil has been ameliorative fertilized with
mineral fertilizer and organic fertilizer from
California worms. According to data for
meteorological parameters from the
Hydrometeorological Office Petrovec, the
climate of the Skopje Region featured warm
dry muggy summer and foggy cold winters.
Тhe chemical content was observed on
15introduction strawberry varieties: Idea,
Camarosa, Belrubi, Evita, Honeoye, Tethis,
Onda, Chandler, Miranda, Paros, Elsanta, Eris,
Madlen, Favette and Marmolada, and two
standard varieties: Senga Sengana and
Pocahontas. The analysis has been conducted
on the following substances: soluble dry
matter, sugars (total and reductive), acids,
pulp’s pH, sugar/acid ratio, vitamin C,
anthocyanins and mineral matters.
The composition of soluble dry matters is
determined with a Carl Zeiss™ binocular
refractometer, the sugars (total and reductive)
are determined by liquid chromatography,
whereas the total acids are differentiated by
means odd titration with 0.1 N/10 NaOH and
indicated as malic acid. The Tilman’s method
was employed to extract the values of Vitamin
C by means of titration with 2,6
dichlorophenol–indophenol, while the
antocyanins (mg/kg) have been determined
spectrophotometrically, where the pH has been
established by a PHmeter, and the content of
mineral matters through a 550 0C heat
exposure. The elication index was reached
through a relation between the total sugars
content and the total number of acids.
Analyses of variance were performed for
statistical analysis of the results. The results
were processed using LSD-test to prove the
statistical significance of the differences
between the varieties, with significance levels
of 0.05 and 0.01.Coefficient of variation
(CV%)of investigated characteristics is also
analysed.
Results and discussion
The percentage of solvable dry matters within
the tested varieties circles round a broad frame
of 8.5%with Eris and 11.0% with Idea with the
average content amounting to 10.0% (Table
1).In comparison to Pocahontas;Idea,
Marmolada, S. Sengana, Favetteand Paros
show a greater number of soluble dry matters,
while only Idea and Marmolada are richer in
content that S. Sengana. Some statistically
highly significant differences between dry
matters content within the varieties have been
established between the Ideaand Belrubi,
Tethis, Honeoye, Evita, Chandler, Onda,
Camarosaand the Eris variety. Another set of
differences have also been established between
Marmolada, S. Sengana, Favette, Paros,
Pocahontas, Miranda, Elsanta, Madlen,
Belrubiand Tethiswith Honeoye, Evita,
Chandler, Onda, Camarosaand Eris.
The great variation between the varieties exists
in terms of composition of sugars. The greatest
content in total and reductive sugars has been
established with Idea (7.17 and 5.02%
respectively), whereas the lowest with Eris
(6.80and 4.76). The average for all the
varieties amounts to 7.97% in total and 5.58%
in reductive sugars.
3 B. Popovski, M. Popovska
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JAFES, Vol 69, (2016)
Table 1. Chemical content of strawberry fruits
The S. Senganaand Pocahontasstandards are
high in almost the equal amount of sugars with
only the Idea variety showing higher values
than them.The greatest and statistically most
significant differences are there in the relation
between Ideaand Belrubi, Tethis, Honeoye,
Evita, Chandler, Onda, Camarosaand Erisas
well as Marmolada, S. Sengana, Favette,
Parosand Pocahontasand Evita, Chandler,
Onda, Camarosaand Eris, between Mirandaand
Elsantawith Onda, Camarosaand Eris, between
Elsanta, Madlenand Belrubiwith Camarosaand
Eris.
The total content of acids is 0.85% on average
and moves from 0.79% with Ondaand Madlen
to 0.94% withEvita. Belrubi, Idea, Miranda,
Tethis, Chandler, Favette и Evita show greater
values in total acids than S. Sengana, while
Pocahontas is characterized by lower values
than all of the aforementioned with the
Honeoye variety added to the list.The Evita
variety has statistically highly significant
content of total acids from all of the 15 tested
varieties. A significant difference does not
show only with the Favette variety. The
differences between Favette and Chandler are
similar, showing a highly significant higher
values of total acids with 13 tested varieties.
The difference with S. Senganais significant in
relation to theEris variety and highly
significant with Paros, Marmolada, Camarosa,
Ondaand Madlen. The differences between
Pocahontasand Camarosa, Ondaand Madlen
are highly significant.
The pulp acidity revolves around the figures of
3.5 (Tethis), and 4.2 (Chandler, Onda and
Pocahontas). The average for all of the
varieties is 3.9. Eris, Evita, Onda,
Pocahontasand Chandler show greater рН
values than S. Sengana.The ChandlerandP
ocahontas varieties show statistically higher
pH than S. Sengana, Parosand Elsantaand a
significantly higher value than the 9 varieties.
No differences have been established only
with Eris, Evitaand Onda. Statistically
significant differences of the S.
Senganavariety have been noted with the
Camarosa, Honeoyeand Favette varieties and
highly significant with Madlenand Tethis.
TheTethis variety, which is characterized by
the lowest pH value, shows statistically highly
significant differences of its values in relation
to 11 varieties. This varietis shows no relations
only with the Camarosa, Honeoye, Favette,
Madlenand Tethis varieties.
No. Variety
Soluble
dry
matters, %
Sugars Total
acids, %
Pu-lp’s
pH
Sugar/ acid
ratio
Vitamin
C, mg%
Antho-cyanins,
mg/kg Mineral
matters, %
Total Redu-ctive
1 Idea 11,0 8,80 6,16 0,87 3,9 10,2 100,46 40,94 0,88
2 Camarosa 9,0 7,17 5,02 0,80 3,7 9,0 113,73 38,94 0,84
3 Belrubi 9,9 7,89 5,53 0,86 3,8 9,2 82,01 45,20 0,77
4 Evita 9,4 7,55 5,28 0,94 4,1 8,1 87,58 43,11 0,87
5 Honeoye 9,6 7,68 5,38 0,85 3,7 9,0 101,88 40,06 0,90
6 Tethis 9,8 7,84 5,49 0,89 3,5 8,8 103,64 47,28 0,94
7 Chandler 9,3 7,41 5,19 0,91 4,2 8,2 86,60 38,06 0,52
8 Onda 9,2 7,33 5,13 0,79 4,2 9,3 77,20 39,07 0,52
9 Pocahontas 10,4 8,35 5,84 0,84 4,2 9,9 72,49 47,21 0,61
10 S.Sengana 10,6 8,51 5,95 0,86 4,0 9,9 75,03 47,96 0,72
11 Miranda 10,3 8,27 5,79 0,89 3,8 9,4 75,67 47,90 0,80
12 Paros 10,6 8,48 5,94 0,82 4,0 10,4 86,79 43,11 0,90
13 Elsanta 10,3 8,24 5,77 0,84 3,9 9,9 98,81 48,88 0,69
14 Eris 8,5 6,80 4,76 0,83 4,1 8,2 75,51 47,90 0,61
15 Madlen 10,3 8,21 5,75 0,79 3,6 10,4 89,32 41,06 0,69
16 Favette 10,6 8,51 5,95 0,92 3,7 9,3 82,91 37,06 0,66
17 Marmolada 10,7 8,53 5,97 0,82 3,9 10,4 89,72 47,21 0,70
Average 10,0 7,97 5,58 0,85 3,9 9,4 87,90 43,58 0,74
CV% 5,01 5,01 5,01 1,87 3,59 5,52 4,12 2,56 7,31
LSD0,05 0,83 0,66 0,47 0,03 0,23 0,86 6,03 1,86 0,09
LSD0,01 1,12 0,89 0,63 0,04 0,31 1,16 8,11 2,49 0,12
4 B. Popovski, M. Popovska
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JAFES, Vol 69, (2016)
Paros, Madlen и Marmolada show for the
greatest elication index(10.4), whereas Evita
the lowest(8.1). The average for all of the
varieties amounts to 9.4. The controls’ values
prove to be within the range of the average and
higher with a higher index established with the
Marmolada, Madlen, Parosand Idea varieties.
The Marmolada, Madlenand Parosvarieties
show statistically significant differences in
terms of mid values odd the elication index
with Miranda, Favetteand Ondaand highly
significant differences with Belrubi, Honeoye,
Camarosa, Tethis, Eris, Chandler and Evita.
The Pocahontas, S. Sengana and Elsanta
standards, are varietie showing statistically
significant differences within the mid values of
the elication index withHoneoye,
CamarosaandTethisand highly significant
differences with Eris, Chandlerand Evita.
Evitashows the lowest elication index and no
significant differences have been establish
apart from with Chandler, Erisand theTethis
variety.
During the process of establishing the
chemical composition of a fruit’s flesh, the
values of Vitamin C are of the utmost
significance as fruits rich in Vitamin C are of a
greater interest to anyone. The lowest in
Vitamin C values are theS. Sengana (87.90
mg%) and Pocahontas(72.49 mg%) varieties
whereas the highest figures are appointed to
Camarosa(113.73mg%). The Camarosa variety
shows a statistically highly significant
difference in relation to all the other 16
varieties under analysis. Other highly
significant differences are there between
Tethis, Honeoye, Ideaand Elsantawith 12
varieties (Marmolada, Madlen, Evita, Paros,
Chandler, Favette, Belrubi, Onda, Miranda,
Eris, S. Senganaand Pocahontas). S. Sengana и
Pocahontas show significant and highly
significant lower values for Vitamin C to all
the varieties with the exception of Onda,
MirandaandEris.
The alluring red color of the fruit is owed to
the antocyanins. The antocyanins and Vitamin
C are a vital source of anti-oxidants. The
Favette variety is the lowest in anthocyanin’s
(37.06mg/kg), and Elsantashows the highest
concentration of anthocyanin’s (48.88mg/kg).
The average amounts to43.58mg/kg.S.
Senganais characterized with a rather large
concentration of antocyanins
(47.96mg/kg)with only Elsantashowing a
greater content of antocyanins.
Pocahontastakes up as the sixth richest in
antocyanins. With Elsanta, S. Sengana,
Miranda, ErisandTethis filling in the spots
from first to fifth place, respectively.The
greatest statistically significant differences are
there between Elsanta, S. Sengana, Miranda,
Eris, Tethis, Pocahontasand Marmolada with
Belrubi, Evita, Paros, Madlen, Idea, Honeoye,
Onda, Camarosa, Chandler and Favette.
Favette shows for the lowest values of
antocyanins and has no established differences
apart from those with the Chandler and
Camarosa varieties. .
The mineral matters within a fruit if the
strawberry varies from 0.52% (Onda) to 0.94%
(Tethis) with the average being 0.74%. S.
Senganawith 0.72%, takes the ninth place
whereas Pocahontaswith 0.61% is at the
fifteeth place.Higher values thanS. Senganaare
noticed with Tethis, Paros, Honeoye, Idea,
Evita, Camarosa, MirandaandBelrubi, and
lower values than Pocahontashave been
establish only with Chandler и
Onda.Tethisshows no statistically significant
differences whereas Paros, Honeoye, Idea и
Evita. Paros, Honeoye, Ideaand Evitaare
notices to have a higher concentration of
mineral matters than Belrubi, S. Sengana,
Marmolada, Elsanta, Madlen, Favette, Eris,
Pocahontas, Chandlerand Onda.TheS.
Senganastandard is noted to have significant
differences with Erisand Pocahontas, and
highly significant differences with
Chandlerand Onda. Statistically,
Pocahontasshows significantly higher values
than Chandler and Onda.
According to the data on coefficients of
variation, the characteristics under analysis
vary only in the slightest percentage (Table 1).
The lowest variation coefficient has been
established with the total acid content
(CV%=1.87), whereas the highest with the
content of mineral matters (CV=7.31%).
The acquired results on the soluble dry matters
are similar to those of the analyses conducted
by Mratinić- Nenadović (1989) where the
author claims that the content between
varieties varies from од 8.5to 14.2%.
Stanisavljević et al. (1997), noted a
composition of soluble dry matters from
6.15to 9.50 %, Wozniak et al., (1997), from
9.46 to 9.57%, while Stančević, Stanisavljević
(1986) and Stanisavljevićet al.(1996) from
9.,5%, i.e.from6.3% дo 10.1%. According to
Nenadović - Mratinićet al.(2003, 2006)the
5 B. Popovski, M. Popovska
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
soluble dry matters content varies from 7.92 to
9.41%. Mratinić (1989) has established
content of soluble dry matters with the S.
Senganaraised in outdoor conditions with
figure varying from 8.50 to 14.25 %. For
Milivojević (2003), this variety showed
numbers of 9.70%, while Blagojević (1999)a
nalysed at 10.01%. In order to provide a
proper choice of industrial strawberries with a
high percentage of soluble dry matters fit to
dry, Vittenet al. (2008), have established
contents with 97 genotypes which ranged
between 7.5%and 18.5%.
Кипријановски (2001) in the Skopje region
analyses 8.1% dry matters with the
Pocahontas variety. Gavrilović (1986)with
theBelrubivariety notes 9.50% in dry matters.
The content of soluble dry matters withElsanta
(10.3%) and Marmolada (10.7%) are higher
than those reached by Milivojević (2003)in the
Belgrade region, of 8.30% i.e. 8.56%.
Wozniak et al. (1997), note a reductive sugars
content of 5.5 to 5.8% and an amount of total
sugars of 6.35% to 6.70 %. The values of
Vitamin C range between 59% and
99.4%mg/kg. Growing strawberries in
conditions of a drier and warmer climate is
always accompanied by a larger content in
sugars.
The average content of total acids, mineral
matters and antocyanins are a match with the
date acquired by Благојевиќ (1998) while the
content of total sugars (7.97%) and
antocyanins (43.58 mg/kg) is higher in
contract to his research. The author notes an
average content of total acids from 0.38% to
0,84 %, a total sugars contents within the
limits of 3.87%and 7.10% and antocyaninsof
31,79 mg/kg. The also notes an antocyanins
content with the Belrubi (34.63 mg/kg) and S.
Sengana (36.11mg/kg) varieties.
Stanisavljevićet al.(1996), state the average
values of total acids to be ranging from од
0.64%to 1.00%, while th рН values moves
from3.30 to 3.72.
Our results on the chemical composition of the
Marmolada variety are significantly higher
than those reached by Milivojević (2003). The
author has established a content of 5,.68% in
total and 4.48% in reductive sugars, 0.66%
total acids, 51.08mg% Vitamin С and 0.26%
of mineral matters.
According toWozniak et al. (1997), Elsantahas
6.70%in sugars and an elication index of
7.32.Voća et al. (2006), note a Vitamin С
content оf 58.32 mg% in anon-soiled
supstratum to 68.58 mg%in high tunnels,
within the Zagreb region. The fruit’s рН
values amounted to 3.70 onto an open fieldto
3.91 in a non-soiled substratum. Milivojević
(2003), on the other hand, shows figures for
this variety starting from5.52in totaland 4.
43% in reductive sugars, 0.71%in total acids,
13.,18 mg%of Vitamin Cand 0.24% of mineral
matters. Our results concerning the Elsanta
variety, show higher values in terms of the
chemical composition covering all the
parameters in contrast to the analysis by
Milivojević (2003), an equal content of
Vitamin С and рНvalues of the pulp which
concerns a non-soiled substratum Voća et al.
(2006) and elocation index higher than the one
reached byWozniak et al. (1997).
The acquired data on the chemical
composition the S. Senganavariety are higher
in contrast to all the parameters established by
Milivojević (2003)– 7.35in total and 6.11%in
reductive sugars, 0.84% in total acids, 11.61
mg%of Vitamin С and 0.34 % in mineral
matters, and those byБлагојевиќ (1998)– 6.61
in total and 4.41% in reductive sugars, 0.80%
in total acids, 2.87 pulp pHand 8.26 elication
index.
Mratinić-Nenadović (1989), had been
analyzing the chemical composition of the
fruit with the S. Senganavariety both out and
indoors and figures of 8.50% to 14.25% in
soluble dry matter, 6.35%to 4.56% in total
sugars, and 0.37%to 0.87% in total acids were
established with the plants raised outdoors.
The chemical composition of the plants raised
indoors shows for higher values over the same
parameters (soluble dry matters from 7.80to
15.60%, total sugars from 4.25 to 8.46%
andtotal acids from 0.62 to 0.97%).
During the analysis of the chemical
composition of Honeoye, Wozniak et al.
(1997) presented slightly lower values that
those we have in terms of total sugars (6.78%)
and total acids (0.71%).
Results on the total acids content (0.84%) and
Vitamin С (72,49mg%) with the Pocahontas
variety are higher in contrast to those reached
by Kiprijanovski (2001) who established
0.67% in toatal acids and 47,5 mg%in Vitamin
C.
Nenadović - Mratinićet al. (2003)conducted an
analysis over 7 varieties of strawberries with a
different planting distance among which were
the Favette, Evita, Erisand Madlen varieties.
6 B. Popovski, M. Popovska
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
The total sugars ranges between 6.31% and
8.00 %, inverterted sugars from 5.53% to 6.34
%, total mineral matters of 0.21%to 0.28 %
and Vitamin Cfrom 14.0 to 18.5 mg%. From
these figures a conclusion has been drawn that
a greater distance planting (30х30and
40х40cm) has a positive effect in raising the
values of the tested chemical characteristics.
The data acquired on the chemical
composition in soluble dry matters, total
sugars, Vitamin C and mineral matters with
the FavetteandMadlen varieties, are higher
than those reached byNenadović - Mratinićet
al.(2006) concerning the same varieties and
are insignificantly lower in the values of total
acids and reductive sugars. WithNenadović -
Mratinićet al.(2006), Favette contains 7.92%
soluble dry matter, 6.30% total sugars,
6.0%reductive sugars, 0.90% total acids, 18.8
mg%Vitamin С and 0.21% mineral matters.
Madlen contains 9.90% soluble dry matters,
7.81% total sugars, 5.86% reductive sugars,
0.96% total acids, 15.2mg%Vitamin С and
0.27% mineral matters.
The results reached in terms of soluble dry
matters, total and reductive sugars, and total
acids with the Evita and Eris varieties are
lower that thoe reached in the research of
Nenadović - Mratinićet al.(2006), over the
same varieties, however are significantly
higher in terms of Vitamin C and mineral
matters. According to Nenadović - Mratinićet
al.(2006), Evita contains 10.05% soluble dry
matters, 8.80% total sugars, 6.60% reductive
sugars, 0.98% total acids, 16.2 mg% Vitamin
С and 0.30% mineral matters. Eriscontains
9.30 % soluble dry matters, 8.14% total
sugars, 6.96% reductive sugars, 0.68% total
acids, 14.70 mg% Vitamin С and 0.28%
mineral matters.
Conclusions
With all the analyzed varieties a high content
of the tested values within the chemical
composition has been established.
The average content of soluble dry matters
amounts to 10.0%, and varies from 8.5 (Eris)
to 11.0% (Idea). The total and reductive sugars
within the fruit of the plant range between 6.8
and 4.76% (Eris) and 8.80% and 6,16% (Idea),
while the average amount to 7.97% and 5.58%
respectivelly.The total acid concentration
varies from0.79% (OndaandMadlen)to 0.94%
Evitaor 0.85%. A pulp рН has been
established between 3.5 (Tethis) to 4.2
(Chandler, Onda и Pocahontas) or a 3.9 pH on
average. The average elication index for all the
varieties amounts to 9.4.with Evita(8.1) with
the lower,and the Paros, Madlen and
Marmolada varieties with the highest
index(10.4).The tested varieties of strawberries
are characterized by a high content of Vitamin
C which ranges somewhere between 72.49
(Pocahontas) and 113.73 mg% (Camarosa)
with an average of 87.90mg%.The strawberry
poses a high source of antocyanins with the
average being 43.58mg/kgand a variation of
the figures between37.06 (Favette) and
48.88mg/kg (Elsanta).The mineral matters
within the fruit show for numbers between
0.52(Chandler и Onda)and 0.94 % (Tethis)
with an average value amounting to 0.74% for
all the analysedvarieties .
Out of all the tested caharcteristics the lowest
variation coefficient has been noted with the
content of total acids (CV%=1.87) whereas the
highest variation coefficient has been noted
with the content of mineral matters
(CV=7.31%).All of the analysed
characteristics show only a slight variation.
References
1. Благојевиќ Р. (1998). Проучување на
биолошките и технолошки особини кај
поважните сорти јагоди. Докторска
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uslovimaNiša.Jugoslovenskovoćarstvo, 33,
125-126:17-25.
3. Vitten M. D., Tiedke F., Olbricht K.
(2008). Dry Matter In Fragaria Fruit: A
New Breeding Goal. VI International
Strawberry Symposium, Spain.Spisanie,
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4. Voća Sandra, Duralija B., DružićJasmina,
SkendrovićBabojelić Martina,
DobrevićNadica, Čmelik Z. (2006).
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начинот на одгледување на јагодите врз
вегетативниот прираст и приносот.
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(FragariaananassaDuch.).
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Jasminka, Đurović D. (2006).Uticaj
rastojanja sadnjena kvalitet ploda
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Čačak.
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производни карактеристики на некои
перспективни сорти јагоди. Докторска
дисертација, Универзитет “Св. Кирил и
Методиј”-Скопје, Факултет за
земјоделски науки и храна, Скопје.
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J., Mitrović O. (1996). Važnijebiološko-
privredneosobinenovijihsortijagode.Jugoslo
venskovoćarstvo, Vol. 30, Br. 115-116:
385-390, Čačak.
13. Stanisavljević M., Srečković M., Mitrović
M. (1997). Field performance of some
foreign strawberry cultivars grown in
Yugoslavia.Proc.Third international
Strawberry Symposium, Acta
Horticulturae, 439, vol 1, ISHS.
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Biološko-tehnološke karakteristike elitnih
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77-78: 65-69, Čačak.
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(1997). Influence of different cultivation
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chemical features of strawberry fruits of
“Elsanta” and “Kent”. Proc.ThirdIct.
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Sieciechowicz A., Dejwor I. (1997). Sugar
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439 Vol. 1: 333-336.
Journal of Agricultural, Food and Environmental Sciences
UDC 634.13-167(497.115)
Original scientific paper
____________________________________________________________________________________________________
INFLUENCE OF RDI, MULCHING AND THEIR COMBINATIONS ON NUTRIENT
CONTENT OF YOUNG "WILLIAM" PEAR STORED IN BASEMENT
L. Lepaja1, E. Kullaj1, K. Lepaja1, N. Krasniqi2
1Agriculture University of Tirana, Koder-Kamez, Tirana, Albania
2University of Prishtina, Faculty of Agriculture and Veterinary, Kosovo
*corresponding author: lavdim_lepaja@hotmail.com
Abstract
The aim of this research was to determine the content of macro- and micro-elements in pear fruits
stored in basement after the application of regulated deficit irrigation (RDI) combined with mulching.
Using a water budged methodology, four levels of irrigation, specifically 100% of ET (control) and
deficits of 80%, 60% and 40%, were applied to 10 trees, 5 of which were mulched by a 10 cm layer.
The experiment was conducted in Kosovo (Dukagjini Plain) during 2013 on a pear orchard of 10 ha
on third year using a nested experimental design. Using ANOVA two-way with post hoc testing we
found significant changes in a series of nutrient elements. Irrigation levels significantly influenced
pH, acids, brix, carbohydrates, dry matter, organic matter, ash, Ca and Na, while mulch has influenced
brix, dry matter, pH, Cu, P, Fe, Mg and Na. The combination of irrigation and mulching have
influenced pH, acids, brix, carbohydrates, dry matter, organic matter, proteins and Na while changes
were not significant for fat, K, Pb and Zn. Young age of trees especially first year of production and
long-term plant responses to RDI are more accurate than short-term responses so experiment is
continuing.
Key words: water stress, Pyruscommunis, wood chips, nutrient elements, basement
Introduction
Production of pear considered
(Pyruscommunis) that is of particular
importance for the economy of Kosovo. Until
now about 600 ha are planted with pear.
Regulated deficit irrigation (RDI) was
developed to improve control of vegetative
vigour in high-density orchards in order to
optimize fruit size, fruitfulness and fruit
quality. RDI is usually applied during the
period of slow fruit growth when shoot growth
is rapid. However, it can also be applied after
harvest in early-maturing varieties.
Furthermore, RDI can generate considerable
water savings. Thus, it is useful for reducing
excessive vegetative vigour, and also for
minimizing irrigation and nutrient loss through
leaching RDI is an ideal water saving
technique. Its application and adaptation in
various environments have led to improved
understanding of the process, the benefits, and
the requirements for adoption (Goodwin and
Boland, 2002).
RDI consists of applying water in quantities
below those necessary to satisfy ETc during
certain periods of the crop cycle when
production and crop quality are hardly
affected, and in the application of all the water
needed during the rest of the cycle, especially
at critical periods of the cycle when the yield
and/or quality would be most affected by a
lack of water. RDI is normally applied during
stages of the cycle when reproductive growth
is relatively slow and when vegetative growth
and other plant processes may be affected,
9 L. Lepaja, E. Kullaj, K. Lepaja, N. Krasniqi
__________________________________________________________________________________
JAFES, Vol 69, (2016)
such effects frequently being translated into
improved fruit quality (Sanchez et al., 2010).
Fruit quantity and quality is directly connected
with optimum soil moisture. In other words,
irrigation plays a crucial role in achieving high
yields and quality besides other measures like
agricultural and pomological techniques.
Through their root system plants receive
nutrients dissolved in water thus reduction of
water absorbed by the roots reduces mineral
uptake. Drip irrigation, used also in our
experiment is the most effective irrigation
system and its application in fruit tree
production is spreading around the world after
its first discovery in Israel. The uniform
distribution of water for each tree cannot be
achieved with other types of irrigation. In
addition, other advantages of this way of
irrigation are: application in different terrains,
uniform soil wetting, prevention of crust
formation, free access for people and
machinery after every irrigation event,
avoidance of soil compression, prevention of
erosion, possibility for the use of fertigation,
etc. (Lepajaet al., 2015).
Today, irrigation is the largest single consumer
on the planet. Competition for water from
other sectors will force irrigation to operate
under water scarcity. Deficit irrigation, by
reducing irrigation water use, can aid in
coping with situations where supply is
restricted (Fereres and Soriano, 2007).
Responses of Asian pear (PyrusserotinaRehd.
'Nijisseiki') to water stress were studied by
(Behboudian and Lawes, 1994) and they gave
information that fruit concentration of N, P, K,
Ca and Mg decreased during the early stress
period. Water stress did not affect the
concentration of N, P, K, and Mg in fruit, but
tended to reduce Ca in early stressed fruit. The
latter had a higher concentration of sucrose,
glucose, fructose, and sorbitol than
nonstressed fruit after 35 days treatment.
Pliakoni and Nano, 2010 studied the effects of
deficit water and mulch in quality and storage
of peach fruit have found that peaches from
reflective mulched trees had the most
advanced maturity fruit at harvest compared to
the other treatments, and higher quality fruit
but also lower storage ability than control
fruit. In short, fruit quality of both cultivars
studied was improved due to deficit irrigation
or reflective mulching but their storage ability
was reduced from these treatments.
The objective of this study was to determine
the impact of RDI in combination with
mulching on quality parameters after fruits
stored in basement where water resources are
limited, and pear tress are in water stress.
Materials and methods
To determine the content of macro- and micro-
elements in pear fruits after the application of
regulated deficit irrigation (RDI) combined
with mulching, stored in basement were used
in a commercial pear orchard. Ten ha orchard
of pears was planted on April 2011 in Kosovo
(Dukagjini Plain). The experimental set up
was a nested or hierarchical design whereby
the categories of nested factor within each
level of the main factor are different, i.e.
different trees give rise to the leaf/fruit
samples within each of the main irrigation
treatment. Trees were belonging to cv.
‘Williams’ on BA29 rootstock, on third year
respectively on first year of production. Pear
orchard was in under antihail system. Four
levels of irrigation were applied during the
season, 100% of evapotranspiration (ET) as
control (1.6 liters of water/h per drip) and
water deficit in 80% of full ET (1.28 liters of
water/h per drip) 60% of full ET (0.96 liters of
water/h per drip) and 40% (0.64 liters of
water/h per drip). Drip distance in the lateral
pipe was 0.60 m. First irrigation was applied
on May 22, 2013, while the last irrigation was
applied on September 20, 2013. A total of 19
irrigations (one irrigation per two hours) were
applied. Each treatment (each level of
irrigation) has been in a row. For each
treatment we used 10 trees, 5 of which were
mulched with a 10 cm thick layer of wood
chips totalling 40 trees for the entire
experiment. Mulching material was placed in a
row of a width of 0.60 m on May 21, 2013.
Planting distances were 3.5 m between the
10 L. Lepaja, E. Kullaj, K. Lepaja, N. Krasniqi
__________________________________________________________________________________
JAFES, Vol 69, (2016)
rows and 1.3 m in the row. After harvesting on
September 6, 2013 for each trees two fruits
were stored in basement in temperature 12 °C,
for 21 days, then the same fruits were sent to
the laboratory where the following quality
indicators were analysed: pH, Brix, dry matter,
organic matter, acids, proteins, fats,
carbohydrates, Ca, K, Cu, Pb, Fe, Na, Mg, Zn,
P and ash.
Our state has a moderate continental climate
with a coastal impact which penetrates through
the valley of the Driniibardhë moderating
markedly continental climate elements (Lepaja
et al., 2014; 2015). In Kosovo average
temperature multiyear (1951-1980) is 10.3 °C,
that of vegetation 16.5 °C, the coldest month is
January (-0.9 °C) while the hottest month is
July with 20.1 °C. Regarding the annual
rainfall is 744.8 mm, and during vegetation is
346.7 mm which shows the need to intervene
with supplementary irrigation (Zajmi, 1996).
Water shortages in the territory of Kosovo,
especially during the vegetation period, need
supplemental irrigation.
The amount of rainfalls for Peja region for a
30 - year period are 907.4 mm and 352.5 mm
during the growing season. Rainfalls during
the period of the study were much lower
compared to the average 30 - year period with
a total of 571.7 mm and 309.8 mm during the
growing period. The first irrigation was
applied at the end of May when temperatures
started to raise and there were no rainfalls. The
average temperature and the temperature
during the growing period was 1°C higher
compared to the 30 - year average. Data from
the measurements were analysed using
ANOVA two–way with post hoc testing.
Result and discussion
Early cultivars need less water than late
cultivars. In Kosovo, at the beginning of the
vegetative period trees have enough moisture
supplied by the heavy spring rainfalls, as well
as water reserves accumulated in the soil
during winter from snow. This has happened
for centuries, but with global warming it also
can change, as it is increasingly witnessed in
many countries with dry winters in one side, or
spring floods on the other.
At the end of the treatment period (100%
irrigation as control, deficit of 80%, 60 and
40%),normal irrigation, two laterals, side
laterals, without irrigation), of RDI
application, we found changes in a series of
macro- and micro elements, after fruit stored
in basement and then were sent to the
laboratory.
Table 1, 2, 3 summarises the results of the
application of RDI in combination with
mulching on quality parameters of William
pears, after fruits stored in basement, with
differences between treatments according LSD
testing. Using ANOVA we found significant
changes in a series of nutrient elements.
Irrigation levels significantly influenced pH,
acids, brix, carbohydrates, dry matter, organic
matter, ash, Ca and Na, while mulch has
influenced brix, dry matter, pH, Cu, P, Fe, Mg
and Na. The combination of irrigation and
mulching have influenced pH, acids, brix,
carbohydrates, dry matter, organic matter,
proteins and Na while changes were not
significant for fat, K, Pb and Zn (table 3).
As seen in Table 1, to 7 elements (pH, brix,
dry matter, organic matter, acids, proteins and
carbohydrates) the highest values were
reaching in 100% irrigation, followed by 80%,
60% and lastly 40%. Higher values are
reached without mulch treatments, but the
same elements that have been made at the time
of harvest after applying the RDI, treatments
with mulch had higher value.
Unlike the elements of table 1 those in table 2.
(ash, Ca, Fe, Cu, Na, Mg and P) higher values
are reached with mulch treatments. The
highest values were found in 80% irrigation,
followed by 100%, while 60% and 40%
irrigation have had approximate value.
11 L. Lepaja, E. Kullaj, K. Lepaja, N. Krasniqi
__________________________________________________________________________________
JAFES, Vol 69, (2016)
Table.1. Average values of the parameters tested in fruits at harvest with differences between treatments
according LSD testing
Elements pH Brix Dry
matter
Org.
matter Acids Proteins
Carbohy
drates
Irrigation
100 %
Mulch + a 3.88 a 15.44 a 17.65 a 17.27 a 0.28 a 0.24 a 16.48
Mulch - 4.02 a 16.00a 18.06 a 17.52 a 0.24 a 0.32 a 16.61 a
Irrigation
80 %
Mulch + b 3.64 b 14.66 b 16.24 b 16.10 b 0.40 b 0.42 b 15.15
Mulch - 3.76 b 15.03b 16.77 b 16.35 b 0.38 b 0.24 b 15.62 b
Irrigation
60 %
Mulch + c 3.77 b 14.29 b 15.99 c 15.57 c 0.22 c 0.33 c 14.78
Mulch - 3.69 c 13.77c 15.66 c 15.19 c 0.33 c 0.27 b 14.28 c
Irrigation
40 %
Mulch + c 3.52 c 12.50 c 14.28 d 13.74 c 0.23 a 0.22 d 13.09
Mulch - 3.75 c 13.88c 15.44 c 14.92 d 0.26 a 0.37 c 14.08 c
Table.2. Average values of the parameters tested in fruits at harvest with differences between treatments
according LSD testing
Elements Ash Calcium
(Ca)
Cooper
(Cu)
Sodium
(Na)
Magnesium
(Mg)
Phosphorus
(P)
Irrigation
100 %
Mulch + a 0.33 a 10.00 a 0.42 a 3.60 a 9.97 a 5.83
Mulch - 0.32 a 13.33 a 0.09 a 3.10 a 8.57 a 4.67 a
Irrigation
80 %
Mulch + a 0.32 b 16.33 b 0.23 a 3.77 a 9.73 a 7.80
Mulch - 0.28 b 13.66 a 0.14 a 3.20 a 8.63 a 3.20 a
Irrigation
60 %
Mulch + b 0.23 a 10.00 c 0.08 a 3.57 a 9.63 a 8.50
Mulch - 0.27 b 12.33 a 0.08 a 4.30 b 8.00 a 4.80 a
Irrigation
40 %
Mulch + b 0.25 c 12.67 d 0.20 a 3.93 b 8.40 b 3.53
Mulch - 0.27 b 15.33 b 0.11 a 3.03 a 7.90 a 5.10 a
*In table 1 and 2. letters on the left in each column represent differences for mulch +, while on the right
represent differences for mulch- (without mulch).
In Table 3 are presented the elements, which
in based ANOVA variance analysis are not
found significant differences (K, Zn, Pb and
fat), but even here the highest values are
reached in without mulch treatments.
Table.3. Average values of the parameters tested in fruits at harvest in which there were no differences between
treatments
Elements Fat Iron
(Fe)
Potassium
(K)
Zinc
(Zn)
Lead
(Pb)
Irrigation
100 %
Mulch + 0.21 0.56 101.66 0.28 0.008
Mulch - 0.25 0.45 111.66 0.32 0.010
Irrigation
80 %
Mulch + 0.20 0.56 102.00 0.32 0.010
Mulch - 0.20 0.48 106.00 0.36 0.008
Irrigation
60 %
Mulch + 0.22 0.55 98.66 0.31 0.004
Mulch - 0.24 0.49 93.66 0.30 0.011
Irrigation
40 %
Mulch + 0.18 0.55 94.00 0.33 0.006
Mulch - 0.19 0.47 97.00 0.25 0.011
These results can be obtained primarily as a
result of weather conditions: temperature and
rainfall during the time the experiment,
furthermore long-term effects of deficit
irrigation, together with climatic conditions,
crop techniques variations, type of soil, age of
plants etc. must be considered, because the
long-term plant responses to RDI or PRD are
more accurate than short-term responses
(Lepajaet al., 2015).
12 L. Lepaja, E. Kullaj, K. Lepaja, N. Krasniqi
__________________________________________________________________________________
JAFES, Vol 69, (2016)
Conclusions
High nutritional values of pear fruit make this
crop highly demanded all around the world.
Different cultivars have different nutrient
values. However, changes in these values
depend also on a number of factors such as
climate, cultural practices, rootstocks,
irrigation etc.
In experiments in open field where irrigation is
applied, respectively deficit irrigation, RDI or
PRD, crucial factors in the results of the
research are the climatic conditions of that
region but on the other side the results of the
first year of the experiment, are only
preliminary results and for sustainable results
the experiment it must continue for many
years. Pear culture is very demanding on the
market throughout the year, as long
preservation of fruit without losing their
quality is an advantage.
The use of the four different levels of
irrigation (100%, 80%, 60% and 40%)
combination with mulch on Williams pear is a
new thinks (innovation), so each result
increases our understanding of the effects of
regulated water deficit practices, respectively
RDI practices. Based on our investigations on
the optimal deficit irrigation regime under the
agro ecological conditions of Kosovo and
Dukagjini Plain in particular, under an
intensive pear growing technology we can
deduct that harvesting of fruits for storage cv.
‘Williams’ is to be done earlier to the
beginning of August so that the fruits can be
stored longer although preserving fruits can be
affected by temperature. We found significant
changes in a series of nutrient elements.
Irrigation levels significantly influenced pH,
acids, brix, carbohydrates, dry matter, organic
matter, ash, Ca and Na, while mulch has
influenced brix, dry matter, pH, Cu, P, Fe, Mg
and Na. The combination of irrigation and
mulching have influenced pH, acids, brix,
carbohydrates, dry matter, organic matter,
proteins and Na while changes were not
significant for fat, K, Pb and Zn.
As the experiment is continuing, in the next
years we expect an attenuation of the RDI
effects in combination with mulching.
References
1. Behboudian, M. and Lawes S. 1994. Fruit
quality in ‘Nijisseiki’ Asian pear under
deficit irrigation: Physical attributes, sugar
and mineral content, and development of
flesh spot decay. New Zeland Journal of
crop and horticultural science. 22:4, 393-
400.
2. Caspari, H. 1993. The effects of water
deficits on the water balance and water
relations of Asian pear trees
(PyrusserotinaRend., cv. Hosui) growing in
lysimeters. Unpublished PhD thesis,
University of Bonn.
3. Caspari, H., Behboudian, M., Chalmers, D.,
Clotheir, B. and Lenz, Fritz. 1996. Fruit
Characteristics of ‘Hosui’ Asian Pears after
Deficit Irrigation. HortScience 31(1):162.
4. Fereres, E. and Soriano Maria Auxiliadora.
2007. Deficit irrigation for reducing
agricultural water use. Journal of
Experimental Botany. Vol. 58, No. 2, pp.
147-159.
5. Goodwin, I. and Boland AM. 2002.
Scheduling deficit irrigation of fruit trees
for optimizing water use efficiency. Deficit
Irrigation Practices. Water Reports
Publication n. 22, FAO, Rome., 67-79.
6. Griffiths, K.M., M.H. Behboudian, and M.
Dingle. 1992. Irrigation management and
fruit quality in Asian pear. HortScience
27:627. (Abstr.).
7. Lepaja, L., Kullaj, E., Lepaja, K., Shehaj,
M. and Zajmi, A. 2014.Fruit quality
parameters of five pear cultivars in western
Kosovo.J. International Scientific. Vol.
2:245-250.
8. Lepaja, K., Lepaja, L., Kullaj, E., Krasniqi,
N. and Shehaj, M. 2015. Effect of partial
rootzone drying (PRD) on fruit quality and
nutrient contents of ‘Albion’
strawberry.50th Croatian and 10th
International Symposium on
Agriculture.600-604.
13 L. Lepaja, E. Kullaj, K. Lepaja, N. Krasniqi
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JAFES, Vol 69, (2016)
9. Lepaja, L., Kullaj, E., Lepaja, K. and
Zajmi, A.2015.Effect of regulated deficit
irrigation, mulching and their combination
on fruit diameter growth of young
‘William’ pears.50th Croatian and 10th
International Symposium on
Agriculture.580-584.
10. Pliakoni, E.D. and Nanos, G.D. 2010.
Deficit irrigation and reflective mulch
effects on peach and nectarine fruit quality
and storage ability. Acta Hort. (ISHS)
877:215-222.
11. Sanchez, M.C., Domingo, R. and Castel
J.R. 2010.Deficit irrigation in fruit trees
and vines in Spain.Instituto Nacional de
Investigacion y TecnologiaAgraria y
Alimentaria (INIA).Spanish Journal of
Agriculture Research. 8(S2), S5-S20.
12. Zajmi, A. 1996.The opportunities of
utilizing the natural and biological
potentials, in the agriculture productivity in
Kosovo. Pp. 201-220. In: A scientific
conference: A MultidisiplinaryAproach of
Developing Possibilities of Kosova.
ASHAK.Prishtinë.
Journal of Agricultural, Food and Environmental Sciences
UDC 634.23:539.166
Original scientific paper
____________________________________________________________________________________________________
MORPHOMETRIC CHARACTERISTICS ON SELECTED CHERRY PLANTS, A
PRIMARY EFFECT PRODUCT OF GAMMA RADIATION (Cz137)
M. Popovska1*, B. Popovski2
1University ,,Ss. Cyril and Methodius“Institute of Agriculture – Skopje, Macedonia
2University ,,Ss. Cyril and Methodius“Faculty of Agricultural Sciences and Food – Skopje,
Macedonia
*corresponding author: m.popovska@zeminst.edu.mk
Abstract
A study has been conducted on the rootstock cross area, trunk cross area and total growth with 195
selected plants, a primary effect product from Bigareau Burlat, Pobeda Krimska and Kozerska cherry
varieties, during the first MV1 generation after the gamma radiation with Cz137. Graft branches were
exposed to dosages of 25Gy, 35Gy and 45Gy at the Institute of Radiobiology and Radiopreservation
in Sofia. The graft was taken during dormant buds onto a Prunus mahaleb rootstock. The average
values of all study parameters with the selected plants are 10 to 50% smaller in comparison with the
controls (plants not treated with radiation). The highest reduction of total plant growth is noticed at
Kozerska variety. The average value is 40% smaller in contrast to the control. The average values for
this characteristic provide statistical significant differences for all radiation dosages with the selected
plants in contrast to the control. The highest difference was noticed with the dosage of 25 Gy, where
the total growth is 50% smaller than the control. A very high positive correlation is determent
between the rootstock and trunk cross area, as well as between the rootstock and trunk cross area and
with the total growth in all of the tested varieties. Negative correlation between the radiation dosage
and the total growth is detected for Pobeda Krimska and Kozerska. This kind of correlation is not
present in Bigareau Burlat.
Key words: Prunus avium L., gamma radiation, dosage, rootstock and trunk cross area, total growth.
Introduction
The radiation treatment with gamma rays is
applied with the sole purpose of enhancing the
frequency of the natural variability, shortening
the process of selection, and enriching the
gene-fund with new initial material for
creating new gene- types (Popovska and
Popovski, 2012). The efficiency of the
ionization with the fruit species depends on the
type and intensity of the radiation, radio-
sensitivity of the variety, the part of the plant
that is exposed to the radiation, the units
stadium of development, the cells’
physiological condition and their dynamism at
the moment of treatment, the climate, the
temperatures during the winter period above
all, etc. (Kolesnikova, 1970; Ravkin, 1973;
Milenkov, 1974; Lapins, 1983; Donini et al.,
1991).
Appearance of the modification changes at
fruit plants after radiation treatment with
gamma rays, can be used as a diagnostic
measure for somatic mutations (Nybom, 1961;
Bishop,1967; Равкин, 1973; Миленков,1974;
Donini, 1975, Lapins,1983). All of the
changes are primary effect result of serious
damage of the apical meristem of the leaf
buds, as well as the secondary effect of the
physiological disbalance which emerges in the
affected cells (Guncle and Sparrow, 1961).
The authors mention that the regeneration area
of the affected cells emerges in the primary
brunches with an atypical position of the buds,
significantly fattened nodal regions, and an
atypical brunch color, presence of furcations
and fasciations and atypical leaves.
The changes which the radiation exposure
causes over the DNA molecule, directly slows
down its synthesis, as well as that of the RNA,
proteins, ATR and the cell’s mitosis (Gunchel
and Sparrow, 1961; Borojević, 1976; Pearson
15 M. Popovska, B. Popovski
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JAFES, Vol 69, (2016
et al., 1975; Mišić, 1999).The occurrence of
shortened internodes leads to a decreased
growth in the plants and poses one of the most
substantial modification changes which are a
result to the radiation treatment (Ravkin 1973,
Milenkov, 1974).
The aim of this paper is to analyze some
morphometric characteristics of selected
prospective cherry plants, as a primary effect
product from radioactive treatment of three
cherry varieties with three different dosages of
Cz137, and to compare them with the controls
(plants not treated with radiation). The
selected plants present a promising starting
material for further selection and creation of
new varieties or cherry rootstocks.
Materials and methods
Dormant buds from Bigareau Burlat, Pobeda
Krimska and Kozerska cherry varieties were
treatedwith radioactive Cz137 in doses of 25Gy,
35Gy and 45Gy. Graft branches were exposed
to radiation at the Institute of Radiobiology
and Radiopreservation in Sofia. Prunus
mahaleb L. was used as a rootstock for
grafting the buds, right after the treatment (30th
of August 2000 and 2001). Untreated buds
from each variety were used as a control
variant. Each variant was grafted onto two
hundred rootstocks.
An early diagnosis of the primary effects of
the radiation was made in the first MV1
generation following the treatment. Basic
criteria for first choice was made according to
the appearance of plants with the following
four characteristics: decreased vigorousness
and irregularly positioned leaf buds, presence
of furcations (bi-, three- and polyfurcations),
atypical leaves (shape, size, color, edginess,
deficiency of chlorophyll etc.) and expressive
outspread of the plants (Popovska et al.,2011).
A study has been conducted on the rootstock
cross area, trunk cross area and total growth
with 195 selected plants, a primary effect
product from radiation in the first year after
the treatment of dormant buds. The measures
were made in autumn, after falling of the
leaves. The obtained experimental results were
processed using t-test to prove the statistical
significance of the differences between the
controls and variants at levels of significance
0.05, 0.01 and 0.001 (Најчевска, 2002). The
correlation between the different traits is
established with a correlation analysis,
determining the strength of the connection
through a correlation coefficient, according to
Snedecor (1959) (Најчевска, 2002).
The research was performed at the
experimental field in the Institute of
Agriculture in Skopje. The soil type is silt -
clay loam, suitable for cherry production, with
moderate alkaline pH according to its reaction
in water and neutral according to its reaction
in KCl, very carbonate, with a low amount of
humus, with a good amount of hydrolyzing
nitrogen and optimal amount of easily
obtainable phosphorous and potassium. The
trial was watered with a drop irrigation
system.
Results and discussion
According to the basic criteria for early
diagnostic of the effects of treatment with
radioactive Cz137, 195 or 46,9% of the total
number of plants received after the treatment,
have been selected in MV1 generation
(Popovska et al.,2011). The decreased
vigorousness of the selected plants has the
most participation of 29,3% from all present
primary effects, followed by furcations (23%),
then plants with atypical leaves (6,1) and then
with expressive outspread (4,3%) (Popovska et
al., 2011).Respective to the variety,88 plants
are selected from Bigareau Burlat, 54plants
from Pobeda Krimska and 53 are from
Kozerska . Related to the dosage, 83 are
selected from radiation of 25Gy, 58 from
35Gy and 54 from 45Gy (Popovska еt al.
,2011).
The data about the tested morphometric
parameters are presented in Tables 1-3 and
Figures 1-3. The control Bigareau Burlat has
the lowest values for the three tested traits,
compared to the controls of the other varieties,
while Pobeda Krimska has the highest values
for rootstock cross area. Kozerska has the
highest values for trunk cross area and total
growth.
Almost all of the average values for the three
tested traits among the selected material are
lower than the control values, from 10 to 50%,
depending on the variety and the dosage. This
is expected, because the trait lower growth is
the most determined among the selected
material. Exception is established for the
variety Bigareau Burlat for the dosage of 35
Gy, where the values for rootstock cross area
and total growth are higher for 10-20%
16 M. Popovska, B. Popovski
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JAFES, Vol 69, (2016
compared to the control. The reason for this
result is found to be in the highest number of
plants with expressive outspread selected from
this variety.
The average rootstock cross area is 339.9 mm2
(Table 1). The smallest deviation from the
control value is determined at Bigareau Burlat,
which represents 10%. The differences
between the tested variants and the control are
statistically insignificant. Higher
dissimilarities are established for the varieties
Pobeda Krimska and Kozerska. For the both
varieties the total average is 40% smaller than
the control value and the difference is
statistically important at the level of
significance of 0.01. Statistically significant
differences are established among all of the
variants, but the highest differences and very
statistically significant are for the average
values of the 45 Gy dosages. Analyzing the
tested dosages, significantly smaller rootstock
cross area is determined for the dosages of 25
and 45 Gy. Overall, the rootstock cross area
from the whole selected material is lower for
30% and the difference is statistically
significant at the level of significance of 0.01.
The average trunk cross area of the selected
plants is 214.9 mm2, which is 30% smaller
than the control values (Table 2). Because the
rootstock and the graft branches are directly
connected, they influence each other’s growth.
A very strong positive correlation is
determined between the rootstock cross area
and the trunk cross area. The correlation
coefficient for Bigareau Burlat is 0.896 and is
statistically significant at the level of
significance of 0.05, according to Snedecor
(1959). For the varieties Pobeda Krimska and
Kozarskaa complete positive correlation is
established between the two traits. The
correlation coefficients are 0.969 and 0.961
accordingly and are statistically significant at
the level of significance of 0.01.
Table.1. Rootstock cross area of selected plants
Again, the smallest deviation from the control
value is determined for Bigareau Burlat, which
represents 10% and the differences between
the tested variants and the control are
statistically insignificant. The highest
difference is observed for the variety Pobeda
Krimska. The average value is 40% smaller
than the control value, which represents
statistically significant difference. The value is
the smallest for the 45 Gy dosages and the
plants have 50% smaller trunk cross area than
the control and the differences are statistically
highly significant. The smallest trunk crosses
area for the variety Kozerska is established for
the plants treated with 45 Gy dosages. The
trunks have 40% smaller cross area and the
Variety Dose Rootstock cross
area (mm2) Index T
CV
%
Bigareau
Burlat
Control 441.0 ± 35.4 1.0 31,5
25Gy 350.0 ± 49.5 0.8 1.495 60,2
35Gy 440.8 ± 72.9 1.0 0.002 57,9
45Gy 383.9 ± 78.1 0.9 0.666 68,0
25-45 391.6 ± 66.8 0.9 0.654 62,0
Pobeda
Krimska
Control 575.4 ± 51.3 1.0 32,6
25Gy 372.8 ± 42.6** 0.6 3.040 44,4
35Gy 364.1 ± 72.7* 0.6 2.684 65,9
45Gy 261.3 ± 52.8*** 0.5 5.491 67,0
25-45 332.7 ± 46.8** 0.6 3.493 59,1
Kozerska
Control 534.1 ± 48.9 1.0 34,8
25Gy 326.8 ± 55.2* 0.6 2.813 41,1
35Gy 326.2 ± 71.4 * 0.6 2.403 54,3
45Gy 232.9 ± 26.3*** 0.6 5.425 37,8
25-45 295.3 ±` 50.9** 0.6 3.382 44,4
Average of controls 516.8 ± 45.2 1.0 32,9
Average 25 Gy 349.9 ± 49.1* 0.7 2.503 48,6
Average 35 Gy 377.0 ± 63.0 0.7 1.796 59,3
Average 45 Gy 292.7 ± 43.2*** 0.6 3.584 57,6
Average 25- 45 Gy 339.9 ± 55.2** 0.7 2.490 55,2
17 M. Popovska, B. Popovski
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JAFES, Vol 69, (2016
difference from the control value is
statistically highly significant. The average
value is 220 mm2, which is 30% smaller than
the control. Analyzing the tested dosages,
statistically significant smaller trunk cross area
is determined for the 45 Gy dosage.
Table.2. Trunk cross area of selected plants
Variety Dose Trunk cross area
(mm2) Index t
CV %
Bigareau
Burlat
Control 285.4 ± 22.8 1.0 36,0
25Gy 216.8 ± 41.0 0.8 1.462 80,3
35Gy 324.1 ± 49.5 1.1 0.712 73,5
45Gy 211.2 ± 62.7 0.7 1.112 88,8
25-45 250.7 ± 51.1 0.9 0.620 80,8
Pobeda
Krimska
Control 286.5 ± 36.6 1.0 47,5
25Gy 172,0 ± 28.7* 0.6 2.465 52,8
35Gy 203.7 ± 57.7 0.7 1.212 89,6
45Gy 146,4 ± 25.3** 0.5 3.152 67,0
25-45 174,0 ± 37.2* 0.6 2.156 69,8
Kozerska
Control 314.5 ± 35.0 1.0 40,3
25Gy 240.3 ± 72.6 0.8 0.922 98,6
35Gy 248.3 ± 70.4 0.8 0.842 62,9
45Gy 171,3 ± 26.3** 0.6 3.272 37,8
25-45 220.0 ± 56.4 0.7 1.424 66,4
Average of controls 295.5 ± 31.4 1.0 41,3
Average 25 Gy 209.7 ± 47.4 0.7 1.508 77,2
Average 35 Gy 258.7 ± 59.2 0.9 0.548 75,3
Average 45 Gy 176,3 ± 38.1* 0.6 2.413 64,5
Average 25- 45 Gy 214.9 ± 48.2 0.7 1.399 72,4
The average total growth of the selected plants
is 224.5 cm and is 20% smaller compared to
the control average value (276.8 cm) (Table
3). For the Bigareau Burlat, the highest
number of plants with expressive outspreadis
determined, which resulted with the highest
average total growth from all of the tested
varieties. The average is 10% higher than the
control. Most of these plants are established
among the 35 Gy dosage. Accordingly, for this
dosage the highest total growth is measured,
which is 20% higher compared to the control.
Deviations were established, but the t-test did
not show statistically significant differences in
any of the variants for this variety. For the
variety Pobeda Krimska, a statistically very
high significant difference for the total plant
growth is established for the 45Gy dosage.
The tested plants have 40% smaller total
growth than the control. The biggest
deviations are determined for Kozerska. That
is a variety with the most branched crown. The
control has the highest total growth from all of
the tested varieties (334.8 cm). The radiation
effect gave a high number of plants with
decreased vigorousness, which also resulted in
high deviations in the total growth from the
control. The differences are statistically
significant for all of the dosages. In the other
variants, the plants have 40 to 50% smaller
total growth. The highest difference,
statistically significant at the level of
significance of 0.01 is established for the 45
Gy dosages.
18 M. Popovska, B. Popovski
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JAFES, Vol 69, (2016
Table.3. Total growth of selected plants
Variety Dose Total growth
(cm) Index t
CV
%
Bigareau
Burlat
Control 243.9 ± 24.2 1.0 37,1
25Gy 240.1 ± 45.4 1.0 0.074 86,9
35Gy 303.8 ± 65.7 1.2 0.857 72,9
45Gy 232.9 ± 50.0 1.0 0.198 70,3
25-45 258.9 ± 53.7 1.1 0.256 76,7
Pobeda
Krimska
Control 251.8 ± 22.9 1.0 33,2
25Gy 198.9 ± 39.3 0.8 1.163 57,4
35Gy 195.9 ± 42.4 0.8 1.162 70,2
45Gy 139.6 ± 25.3** 0.6 3.291 67,0
25-45 178.1 ± 35.7 0.8 1.739 64,8
Kozerska
Control 334.8 ± 39.7 1.0 43,7
25Gy 183.6 ± 41.1* 0.5 2.645 73,4
35Gy 211.0 ± 50.7* 0.6 1.921 55,7
45Gy 188.5 ± 26.3** 0.6 3.070 37,8
25-45 194.4 ± 39.4* 0.6 2.510 55,6
Average of controls 276.8 ± 28.8 1.0 38,0
Average 25 Gy 207.5 ± 41.9 0.7 1.361 72,6
Average 35 Gy 236.9 ± 52.9 0.9 0.662 66,2
Average 45 Gy 229.0 ± 33.9 0.8 1.074 58,4
Average 25- 45 Gy 224.5 ± 42.9 0.8 1.012 65,7
A statistically significant positive correlation
between the rootstock and trunk cross area,
and the total plant growth is established. The
correlation coefficients between the rootstock
cross area and total growth, as well as the
trunk cross area and total growth, for Bigareau
Burlat are 0.597 and 0.849, accordingly. These
coefficients show strong correlation between
the traits, statistically significant at the level of
0.05. Stronger and complete correlation is
determined for the other two varieties. For
Pobeda Krimska, the correlation coefficients
are accordingly 0.971 and 0.927 and for the
variety Kozerska are 0.945 and 0.839. The
correlation coefficients are statistically
significant at the level of significance of 0.01.
Also, complete and very strong negative
correlations between the height of the dosages
used and the total growth for the varieties
Pobeda Krimska and Kozerskaare determined.
The correlation coefficients are accordingly -
0.952 and -0.882 and are statistically
significant at the level of significance of 0.05.
This kind of correlation is not established for
the variety Bigareau Burlat. The correlation
coefficient r is 0.170. The reason for this is
that most of the plants with furcations are
determined in the variant with 35 Gydosage,
which led to higher total growth for this
variety.
The degree of variation for these three traits is
measured through the values of the coefficient
of variation (CV), given in Tables 1-3.
Overall, the tested traits in the selected plants
vary in much higher ranges, than in the control
variants. The highest variation is observed in
all of the varieties for the trait trunk cross area
(CV=72.4%), while the smallest variation is
monitored for the trait rootstock ross area
(CV=55.2%). Analyzing the varieties
separately, the three traits vary the most in the
variety Bigareau Burlat, in average from 62%
for rootstock cross area to 80.8% for trunk
cross area. The traits vary the least in the
variety Kozerska, from 44.4% for rootstock
cross area, to 66.4% for trunk cross area.
19 M. Popovska, B. Popovski
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JAFES, Vol 69, (2016
Figure1. Rootstock cross area of selected plants
Figure 2.Trunk cross area of selected plants
Figure 3. Total growth of selected plants
Analyzing overall, according to the height of
the dosages used, the rootstock cross area
varies the most for the dosage of 35 Gy, while
the trunk cross area and total growth for 25
Gy. The rootstock cross area varies the least
for the dosage of 25 Gy, while the trunk cross
area and total growth for 45 Gy.
Conclusions
The morphometric characteristics of the
selected cherry plants, as a primary effect from
the treatment with gamma rays, depend from
the traits and the number of plants who
according to the basic criteria were chosen in
the first MV1 generation following the
radiation treatment.
Most of the selected plants have decreased
vigorousnes, which leads to that, that the
selected material has in average 10-50% lower
values for all of the tested traits in comparison
with the control, depending on the variety and
the rootstock. Exception represents Bigareau
Burlat for the dosage of 35 Gy, where the
values for the rootstock cross area and total
growth are higher for 10-20% than the control,
because of the highest number of plants with
expressive outspread, selected from this
variety.
A very high positive correlation is determent
between the rootstock and trunk cross area, as
well as between the rootstock and trunk cross
area and with the total growth in all of the
tested varieties. Negative correlation between
the radiation dosage and the total growth is
detected for Pobeda Krimska and Kozerska.
This kind of correlation is not present in
Bigareau Burlat.
All of the tested traits vary in much higher
degree in the selected plants than in the control
variants. The trunk cross area is the trait with
highest variation, while the rootstock cross
area with least variation.
The three tested morphometric characteristics
vary the most in the variety Bigareau Burlat,
while they vary the least in the variety
Kozerska. The rootstock cross area varies the
most for the dosage of 35 Gy and the least for
25 Gy, while the trunk cross area and total
growth vary the most for 25 Gy and the least
for 45 Gy.
The selected 195 plants present a promising
starting material for further selection and
creation of new varieties or cherry rootstocks.
References
1. Bishop C.J. (1967). Radiation induced
mutations in vegetative propagated fruit
20 M. Popovska, B. Popovski
__________________________________________________________________________________
JAFES, Vol 69, (2016
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2. Borojević S., Borojević K. (1976).
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3. Donini B. (1975). Improvement of
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Vienna. IAEA, Vol1, pp. 35-51.
4. Donini et.al. (1991). Mutation breeding
programmes for the genetic improvement
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Proceedings of an International Symposium
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Ionizing radiations:biochemical,
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и биолошките истражувања.
Бона.Скопје.
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Journal of Agricultural, Food and Environmental Sciences
UDC 634.11-181.198
Original scientific paper
____________________________________________________________________________________________________
EFFECT OF GROW REGULATORS ON THE STOMATA CONDUCTANCE IN
THE APPLE TREE
V. Avdiu1*, F. Thomaj2, S. Sylanaj1, E. Kullaj2, K. Lepaja2
1Faculty of Agriculture & Veterinary, University of Pristina, Pristina, Kosovo
2Faculty of Agriculture and Environment, Agriculture University of Tirana, Tirana, Albania
*corresponding author: vahid_avdiu@hotmail.com
Abstract
This research paper presents the results of a field trial with managed yang orchard including apple
cultivar Gala Galaxy, on the rootstocks M9. In November 2012, nursery tree “knip” were planted in
the distance 3 m x 1 m. In the first vegetation season (2013) the experimental plot was separated in a
randomized block system of four treatments. For research are taken 12 apple trees, which were treated
with growth regulators in the stage of nursery trees production with Gerba 2.5% (benzyl adenine),
Progebalin2.5%, (gibberellins A4+7 + benzyl adenine) Pinching (i.e. removal of terminal leaves)and
Control (untreated). The stomata conductance was examined. During the period from July to
September are realized 15 measurements. In each plant measurements made in 10 leaves (5 inside and
5 on the periphery of the crown of the tree). Also in same time made measurement temperature of
leaf, soil temperature and moisture, to analyze the dependence between these ecological factors and
stomata conductance. By the results obtained the treatment with GerBA 2.5%, has given higher values
of leaf stomata conductivity (200.89 mmol m-² s-¹) in relation to treatments, Progerbalinin, Pinching
and Control, respectively; (174.76, and 141.94 162. 57 mmol m-² s-¹). It is also remark that exist
strong correlation between stomata conductance with soil moisture, soil and leaf temperature.
Key words: stomata conductance, grow regulators, ecological factors
Introduction
The process of plant function is quite complex
and the impacted of many factors internal or
external. It is quite important to recognition as
more as possible of these factors were their
role in the plants could be different. This could
help us in some processes interfering with the
aim of establishing an optimum balance in the
development of plants. Apical dominance is
the control exerted by the shoot apex over the
outgrowth of the lateral buds (Cline, 2000).
Also according Ibro (2008) the auxin have
essential role in apical dominance respectively
dominance top of the buds in relation with
lateral. The development of lateral shoots is in
direct correlation with the phenomenon of
apical domination (Avdiuet al., 2014; Martin,
1987; Cline, 1997; Wilson, 1994). Hormone
production and assimilate retention by the
branch are the most likely candidates for the
primary causes of apical control (Wilson,
2000). Apical dominance is exerted by the
shoot apex over the outgrowth of lateral buds
in apple (Wang, 1994). The environmental
impact on the organs of plants and their related
functions is conditioned very much by the
power and duration of certain factors, even by
the interaction of the factor with genetic
features of plants (Zlatevet al., 2012).
Defining and recognizing by vapour pressure
deficit (VPD) as an environmental factor is
necessary for the evaluation of evaporation -
transpiration (since it is the part of equations
that compute potential evapotranspiration -
PET), but along with global radiation (GR)
have the key impact on the stomata activity
and transpiration (Tonelloet al., 2012; Mugani,
2004). Stomata of leaves are a mechanism
through which is controlled the process of
transpiration and absorption of CO2 and
according to Tonelloet al., (2012) when we
want to determine the stoma response to
various climatic factors, potential impacts may
appear including all main elements that
participate in leaf’s function.
22 V. Avdiu, F. Thomaj, S. Sylanaj, E. Kullaj, K. Lepaja
__________________________________________________________________________________
JAFES, Vol 69, (2016)
Materials and methods
To establish of experimental orchards selected
the standardized apple nursery “knip” tree
with cultivar‘Gala Galaxy’, on the rootstock
M9 at the distance 3 m x 1 m. For research 12
apple trees were taken (3 for each variant),
which were treated with growth regulators in
the stage of nursery trees production
GerBA2.5% (benzyl adenine), and Progebalin
2.5%, (gibberellins A4+7 + benzyl adenine).
Besides, two other treatment were included:
pinching (i.e. removal of terminal leaves) and
control (untreated).
The soil in which saplings were planted was of
good quality, up to 60 cm deep and in average
contained: humus 2.36 %, (moderate) N 0.13
% (moderate), P2O5 10.69 mg/100g (low), soil,
K2O 43 mg/100g soil (high), Ca101.73
mg/100g soil (moderate), Mg 47.14 mg/100g
soil (moderate). pH value in water was 6.8
whereas in KCl 5.8 (slightly acid)
Ploughing was made at 50 cm depth, organic
and mineral fertilizer was distributed in
advance: organic 5kg/m2 and mineral NPK
15:15:15 100g/m2.The plot was tilled 5 times;
plants were drip irrigated and have received 3
treatments with fungicides and insecticides.
The model and experiment design
For research is taken stomata conductance and
impact of ecological several factors which
connected with this process inside of the 10.07
- 06.09.2013 period.
In 12 plans taken for research, 12
measurements were carried, where in each
plant are selected 10 leaves for measurements
(5 inside and 5 outside the apple tree shape).
In same time to the all cases, exanimate
temperature of leaves. The Porometer
measures stomata conductance using a sensor
head with a fixed diffusion path to the leaf. It
measures the vapor concentration at two
different locations in the diffusion path. It
computes vapor flux from the vapor
concentration measurements and the known
conductance of the diffusion path using the
following equation:
Where CvL is the vapour concentration at the
leaf, Cv1 and Cv2 are the concentrations at the
two sensor locations, Rvs is the stomata
resistance, and R1 and R2 are the resistances
at the two sensors. If the temperatures of the
two sensors are the same, conductance can be
replaced with relative humidity, giving:
Conductance is the reciprocal of resistance, so
gvs = 1/Rvs.
The soil temperature depth 15 cm measured
with Sensor type ”WET 2” whereas the soil
moisture in two levels 20 and 40 cm depth,
measured with “DELMHORS” Sensor.
Results and discussion
Stomata conductance is an important indicator
that shows that the behaviour of the stomata is
a necessary reaction of the plant to climate
factors. Through them, it controls two
important physiological processes;
transpiration and absorption of CO2 that is the
basis for photosynthesis. Tonelloet al., (2012)
point out that when we want to determine the
reaction of stomata to different climatic
factors, potential impacts may pluck including
all the main elements that take part in the
functions of the leaf.
3
2 1
Figure 1. The process of measures: 1.Porometer
(stomata conductance), 2. Delmhorst (soil moisture
20-40 cm depth), 3. WET 2 (soil temperature 15 cm
depth)
23 V. Avdiu, F. Thomaj, S. Sylanaj, E. Kullaj, K. Lepaja
__________________________________________________________________________________
JAFES, Vol 69, (2016)
Table 1. Obtained means for some ecological and physiological factors during the period 10.07-06.09.2013 to
the apple cultivar “Gala Galaxy” on the rootstock M9
Date
Soil
moisture
(20-40cm)
KS-D1
Soil temp. oC
(0-15cm)
Leaf
temp. oC
Stomata conductance mmol m⁻² s⁻¹
Progerbalin
2.5%
Gerba
2.5% Pinching Control
10.07. 13 96.00 23.80 21.93 123.9 144 117.5 102.7
13.07. 13 96.20 26.87 28.52 195 229 207.6 173.5
16.07. 13 96.30 21.67 19.83 124.2 122.3 123.2 147.1
19.07.13 96.80 32.47 31.83 179.9 225.4 186.3 171.4
22.07. 13 96.35 31.07 29.68 198.1 212.5 174.2 139.4
25.07. 13 92.30 31.00 33.85 163.5 176.6 165 115.8
29.07. 13 74.90 33.63 36.15 159.1 165.5 131.6 95.38
31.07. 13 69.60 30.67 28.87 180.9 190.4 189.8 157.4
03.08. 13 63.85 35.40 34.54 122.6 176.7 95.54 77.26
06.08. 13 80.40 31.80 35.67 138.4 141.8 113.6 84.32
09.08. 13 60.62 37.93 37.34 132.3 141.2 88.68 63.42
28.08. 13 95.9 27.93 29.18 220.1 242.8 207.1 212.5
31.08. 13 95.75 27.93 26.75 230.6 310 226.6 223.4
03.09. 13 94.95 25.30 27.33 260.9 299.4 250.5 218.3
06.09. 13 94.95 29.30 29.05 191.7 232.6 161.3 176.4
The data presented in Figure 2 shows that
existed a strong connection between stomata
conductance and soil moisture, temperature
soil and leaf. Another interesting phenomenon
that finds compliance with studies of Cechinet
al., (2010), is that the fall of stomata
conductance of leaf aging, which stands very
well in the last part of the above figure that
coincides with the decade first of September.
In this case, although temperature and
humidity indicators remain almost constant
values, whereas have a noticeable decrease of
stomata conductance for all variants.
Figure 2. Comparison of stomata conductance between Soil moisture (Sm), Soil temperature (St) and Leaf
temperature (Lt) according the variants
According to the results obtained on the
stomata conductance presented in the Table 2
and Figure 3, distinguish the difference
between the average values achieved in each
of the analyzed variant. The variant treated
with Gerba 2.5%, has given higher values
24 V. Avdiu, F. Thomaj, S. Sylanaj, E. Kullaj, K. Lepaja
__________________________________________________________________________________
JAFES, Vol 69, (2016)
leaf’s stomata conductance (200.89 mmol m-²
s-¹) in relation to options, Progerbalin,
Pinching and Control respectively; (174.76,
162. 57 and 141.94 mmol m-² s-¹).
Table 2. Comparison of several statistical descriptive parameters of stomata conductance (mmol m⁻² s⁻¹) means, control and three (Progerbaline, Gerbadhe Pinching) during the comparison period
Level Mean Significantly different
Gerba 2.5% 209.58* A
Progerbalin 2.5% 182.79 AB
Pinching 170.09 AB
Control 150.55 B
Means Comparisons q* Alpha
Tukey-Kramer HSD
2.64794 0.05
3.25848 0.01
Levels not connected by same letter are significantly different, * significantly in level 0.05,
Figure 3. Stomata conductance [mmol m-² s-¹] by Variants Gerba2.5%, Progerbalin 2.5%, Pinching and Control
Conclusions
Reduction of moisture in soil stimulates ABA
synthesis of the root that further is transported
through xylem up to the leaves and causes a
slight closure of stoma, whereas, cytokinin
stimulate the opening of the stoma and
transpiration growth rates (Kullajet al., 2014;
Mameli, 2007). This cytokinin effect to the
stoma opening is associated with water
potential in the other parts of the plant. There
occur several interactions between cytokinins,
ABA and CO2 concentration (Blackman and
Davies, 1984; Das and Raghavendra, 1976).
Decagon, (2006) emphasizes that the
conductance is reciprocal with the stomata
resistance. This means that trees derived from
seedlings treated with grow regulator of
cytokinins content (Gerba 2.5%) have higher
stomata conductance but lower resistance,
while the opposite is true for trees untreated
(control) which have lower stomata
conductance and higher resistance of stoma.
This brought the stoma, match quite well with
ecological factors as soil moisture,
temperature soil and leaf, but to take into
consideration the development phase of the
plant within the vegetation.
25 V. Avdiu, F. Thomaj, S. Sylanaj, E. Kullaj, K. Lepaja
__________________________________________________________________________________
JAFES, Vol 69, (2016)
References
1. Avdiu V, Thomaj F, Sylanaj S, Kullaj E,
(2014) Effect of “knip” Method in Apple
Nursery Tree Production on the Apical
Dominance cv Gala Galaxy. J. Int.
Environmental Application & Science,
No.9(2), pp. 323-327.
2. Avdiu V, Thomaj F, Sylanaj S, Kullaj E,
(2014) Effect of “Knip” method in apple
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Procedings of the 4th Interational
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Cataneo CA, (1980) Differential responses
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Reversal of abscisic and induced stomatal
closure bybenzyladenine. New Phytologist,
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course.html Ibro V, (2008) Fiziologjia e
bimëve (parimetëpërgjithshme).Universiteti
Bujqësori Tiranës.
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Model Unveils Changes in Stomatal
Conductance in Apple Saplings after Use
of Bioregulators. Physiological Principles
and Their Application to Fruit Production
(ISHS)
10. Kullaj E, Avdiu V, Lepaja L, Kucera J,
Thomaj F, (2014) Modelling Canopy
Transpiration and Stomata Conductance of
Young Apples Using a Parameterized
Penman-Monteith Equation. Physiological
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Production (ISHS).
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idrico (CRAS) Mugani S, (2004) Elementi
di ecofisiologiavegjetale. QuadernoArsia,
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de tresespeciesarboreasnativas da mata
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13. Wilson SJ, Jarassamrit N, (1994) Nursery
factors influencing lateral shoot
development in a spur type apple cultivar.
ScientiaHorticulturae, No.56, pp. 207-
215.
14. Wilson BF, (2000) Apical control of branch
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601-607.
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Apple (MalusdomesticaBorkh): The
Possible Role of Indole-3-Acetic Acid
(IAA). J. Aamer. Soc. Hort. Sci.,
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on drought induced changes in plant
growth, water relations. J. Food Agric.,
No.24 (1), pp.57-72
Journal of Agricultural, Food and Environmental Sciences
UDC 634.54(497.7)
Original scientific paper
____________________________________________________________________________________________________
ROOTING OF HAZELNUT (CORYLUS AVELLANA L.) VARIETIES HARDWOOD
CUTTINGS
A. Markovski1*, T. Arsov2, V. Gjamovski1
1Institute of Agriculture-Skopje, Ss. Cyril and Methodius University in Skopje, Skopje, R.
Macedonia. 2Faculty of Agricultural Sciences and Food-Skopje, Ss. Cyril and Methodius University in Skopje,
Skopje, R. Macedonia
*corresponding author: maraleks@yahoo.com
Abstract
Intensity of rooting on hardwood hazelnut cuttings is evaluated during two consecutive years. The
evaluation is conducted on 6 hazelnut varieties (Istarski, Tonda Romana, Extra Yagli, Ludolf, Hall’s
Giant, Devianna) in greenhouse conditions at experimental greenhouse of Institute of Agriculture,
Skopje. The cuttings are collected during dormancy of the plants, before start of vegetation. Two
types of auxins IBA (indole-3-butyric acid) 2%, and NAA (α-naphthalene acetic acid) 0.2% are used.
From evaluated varieties, Tonda Romana has the highest percentage of rooting (85.5%) and it is
characterized with the highest value of rooted cuttings of first class. At all evaluated varieties,
treatment with higher concentration of IBA gives higher percentage of rooted cuttings and higher
value of rooted cuttings of first class.
Key words: Hazelnut, variety, hardwood cuttings, rooting, biohormone
Introduction
The European hazelnut (Corylus avellana L.)
is the fruit kind which increasingly spread in
the world due to high income and profitability
in the orchards. This culture attract increasing
attention especially when and where the
difficult and expensive manual harvest of the
kernels is replaced with harvest
mechanization. The biggest production of
hazelnut kernels in the world has the Turkye
with about 75% of the total world production
from which 80% go for export (Faostat, 2012).
In the hazelnut cultivation has the inention for
decreasing of plant distances in orchards, with
aim to achieve the higher yields per ha, which
is in maximum utilized in USA, where the
yields is reached up to 3 t/ha kernels and with
200% increasing of the Hazelnut plantations
area (Faostat, 2012). In this country is going
with the interspecies crossing (Corylus
avellana x Corylus americana) with aim to
create hybrids for expansion of the cultivation
zone to the drier and colder areas (Demchik et
al., 2011). Hazelnut is a feedstock that is
widely used in food industry especially in
chocolate. Eighty percent of the world
hazelnut production is used in chocolate
sector, 15% in cake, biscuit and sweet sector
and 5% in marketing as appetizers
(Fiskobirlik, 2003). The increased appetites of
the world market for the hazelnut kernels can
be satisfied with the increased and more
efficient production of the plant material from
this culture. The most common techniques of
hazelnut propagation are by stool layering and
root suckers. Micropropagation is the safest
and most productive form of propagation, but
in hazelnut it still shows low yield due to
contamination during culture establishment
and the limited adaptability of the explants to
in vitro conditions (Bacchetta et al., 2008).
The propagation by cuttings can be considered
as rapid and relatively economic method but,
in spite of the numerous studies conducted for
the hazelnut, the technique has not yet been
transferred to an industrial scale due to poor
rooting ability and cutting survival of most
cultivars (Contessa et al, 2012). Without usage
of the chemical agents for root initiation
(auxins), the plant material production in this
way becomes impossible. Except that, the bud
abscission is a limiting factor to propagation of
hazelnut stem cuttings, even though the
27 A. Markovski, T. Arsov, V. Gjamovski
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
rooting percentage may be acceptable (Bassil
et al., 1991). Actually, the auxins are using for
the annulation of the ethylene inhibitory effect
on rooting, which is releasing from the cutted
plant parts used for rooting. The ethylene
disable the rooting process (Serek et al., 2006).
Therefore, as the ethylene inhibitors in rooting
process can be used some other compounds
except the auxins, like silver nitrate (AgNO3)
or silver tiosulphate (AgS2O3) (Contessa et al,
2012). The hazelnut can be propagated with
softwood cuttings or with hardwood cuttings.
The softwood cuttings have good rooting with
bottom heating and influence of biohormons,
except that in the period of 6th to 10th week of
rooting, the development of the bud stops
(Lagerstedt 1983). At the hardwood cuttings,
cold survival and acclimatization problems
have been observed. The best rooting has been
obtained from semi-hardwood cuttings taken
from mid-June to mid-July (Contessa et al,
2011). The using of IBA gives excellent
results in rooting of the cuttings from some
fruit kinds (Ercisli, Read, 2001). But, other
studies show that some modified combinations
can provide the better results. According to
Agele (2013), coconut water and NAA were
found better than IBA and IAA in terms of bud
retention and rooting, leaf development and
survival of plantlets. In most of the tested
species (pepper fruit, guava, bush mango and
cashew), wilting of leaves commenced 6
weeks after planting (WAP) and attained
100% mortality thereafter except for pepper
fruit cuttings dipped in coconut water. With
aim to determine the rooting ability of the
different hazelnut varieties (Corylus avellana
L.) we have used the concentration of different
auxins.
Materials and methods
In the period 2004-2005 are collected the
hardwood cuttings from six hazelnut varieties
(Istarski, Tonda Romana, Extra Yagli, Ludolf,
Hall’s Giant, Devianna) in the beginning of
tree dormancy (November), then stored in
sand. At the end of February and in the
beginning of March, the cuttings are prepared
for the rooting with the mitter cut from the
bottom, 5-6 mm below the bud, and flat cut
from the top, 8-10 mm above the last top bud,
by limiting the cutting length of 30-35 cm. The
environmental, and the treatments influence
over variety Tonda Romana is also studied.
For that purpose, the cutting basal part is
treated with biohormons: 2% IBA (C12H13NO2
(Indole-3-butyric acid)) in talc carrier, 0.2%
NAA (C10H7CH2CO2H (1-Naphthaleneacetic
acid)) and the control variant, without treating.
The cuttings are set in inert substrate (sand), 4-
5 cm in depth. Thirty cuttings in three
replications are used. During the vegetation is
performed mist with automized system, and
shading, depending on the conditions. The
rooting is performed in green house
conditions. Through the rooting process, two
times are performed the protection with
Previcur and foliar feeding. All rooted cuttings
which have certain superior vegetative
characteristics (over 30 roots, over 10 cm root
length, and over 5 cm high of the growth) we
classify them in the first class, and other that
do not met provided characteristics are
separated in the second class.
At the end of the vegetation, in November,
after the leaves fall, the hardwood cuttings are
extracted from the sand and then are study the
following parameters:
- Number of set cuttings;
- Number of rooted cuttings;
- Number of I class cuttings;
- Number of II class cuttings;
- Number of roots;
- Length of roots;
- Height of vegetative growth.
The data are statistically analysed by
ANOVA and Fisher’s multiple comparision
test at level of 0.05 using the Minitab software.
Results and discussion
There are many methods for vegetative
propagation of the hazelnut: with grafting,
basal shoots, root suckers, layerings, and with
cuttings. For most of this methods a large
number of mother trees, and the large
propagating area is needed, which is mean
prolonged period for the mass plant material
production and meeting the increased needs
for that. The only possible way to starts in the
short period the large production of plant
material, is to obtain them from rooting of
cuttings.
28 A. Markovski, T. Arsov, V. Gjamovski
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
Figure 1. Percent of hazelnut variety Tonda Romana rooting cuttings in different years and its participation in
different class.
Figure 2. Quality characteristics of the rooted cuttings in different years.
The mother plants from which are taken the
branches, needed as material for cuttings, were
in excellent condition, without presence of
pests and diseases. Our investigations show
that the hazelnut (Corilus avellana L.), as a
species, has affinity to rhizogenesis from the
vegetative plant parts, in our case, from one
year branches. The rooting intensity vary due
to the influence of the different factors.
Successively investigations in different years
show statistically insignificant influence of the
environmental conditions, over total rooting.
So, the percent of the rooting at hazelnut
variety Tonda Romana in the first year was
smaller (61.4%), unlike the next year when the
percent reach 68.5% (Fig.1.). The cuttings
classification by quality shows that the
environmental factors which affect the rooting
of the cuttings, not affect the quality of the
cuttings. At the same hazelnut variety in the
first year, although there was weaker rooting,
it was obtained the higher percent of first class
0
10
20
30
40
50
60
70
80
2004 2005
perc
en
t (%
)
rooting
I-class
II-class
0
10
20
30
40
50
60
I-class 2004 I-class 2005 II-class 2004 II-class 2005
nu
mb
er
of
roo
ts
0
10
20
30
cm
root number growth length of roots
29 A. Markovski, T. Arsov, V. Gjamovski
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
material (55.8%) in equal greenhouse
conditions (Fig.1.). The quality characteristics
of the rooted cuttings indicate that in the
second investigation year is obtained slightly
better quality of the rooted cuttings (53.5
roots, 13 cm length of the roots and 10 cm
over ground growth) in the first class and in
second class (15 roots, 5 cm length of the roots
and 3 cm over ground growth). It can be
noticed the high difference in the quality
between the classes in the first and also in the
second year (Fig.2.)
The influence of the treatments with different
biohormons (IBA 2% and NAA 0.2%) over
the cuttings from the variety Tonda Romana is
significantly higher. The highest positive
influence over the rooting of cuttings is
determined at the treatment with 2% IBA,
when is obtained almost ninety percent (89,
5%) rooted cuttings, which is 55% more than
in the control (Fig.3.).
Is also determined statistically significant
difference in the treatment with 0.2% NAA
(71.1%), compared with control. The
treatments with different concentrations (500
mgL-1 and 1000 mgL-1) of IBA show almost
equal influence of the rooting percent of the
cuttings (70% and 72.5%) at the variety Tonda
Gentile delle Langhe, even, at the lower
concentration of the IBA is obtained more
rooted cuttings with live buds (56%) (Contessa
et al., 2012).
In our case, the differences are more
noticeable when are analysed the participation
of the different classes in the total amount of
the rooted cuttings. So, is noted statistically
significant difference in terms of the first class
rooted cuttings percent (92.6%) in the
treatment with 2% IBA compared with
treatment with 0.2% NAA (48.1%) and also
with control (15.4%) (Fig.3.). The influence of
the different auxins over the rooting can be
different. At some fruit kinds (Guava) NAA
gives the better results than the IBA (Agele et
al., 2013).
Figure 3. Influence of different auxins on percent of rooting cuttings of the hazelnut variety Tonda di Romana
* Footnote: The means followed by the same letter in similar column are not significantly different at P ≤ 0.05
by Fisher’s multiple comparisons test.
The investigation of the different hazelnut
varieties shows partial influence of the
genotype (Tonda Romana) over the ability for
rooting of the hardwood cuttings. With
statistically significant higher percent of
hardwood cuttings rooting is characterized the
variety Tonda Romana (85.4%) (Fig.4.).
Among the other five varieties is not noticed
statistically significant difference. The variety
Tonda Romana also is characterized with
significantly higher percent of first class
cuttings (92.9%), than the other hazelnut
varieties. In some variety investigations with
the rooting of semi-hardwood cuttings, the
a
b
c
c
b
a
c
b
a
0
10
20
30
40
50
60
70
80
90
100
control 0.2% NAA 2% IBA
cuttings basal treatment
perc
en
t (%
)
rooting I-class II-class
30 A. Markovski, T. Arsov, V. Gjamovski
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JAFES, Vol 69, (2016)
variety Tonda Romana shown the lowest
percent of rooting, which alluded that the time
of taking the branches for the cuttings has
different influence over the ability for rooting
at the same varieties (Contessa et al, 2011).
The variety Devianna is characterized with the
lowest percent of rooting and with the lowest
percent of first class rooted cuttings (37.7%
and 38.8%) (Fig.4.).
Figure 4. Influence of the genotype on rooting capability of the cuttings.
* The means followed by the same letter in similar column are not significantly different at P ≤ 0.05 by Fisher’s
multiple comparisons test.
Figure 5. Different Hazelnut varieties rooting cuttings
Conclusions
The investigations show that the rooting of the
hazelnut hardwood cuttings gives numerous
and quality planting material with much better
developed root system than in the usually most
used propagating method-with suckers. The
using of the auxin IBA (2%) contribute for the
much higher rooting percent and for the better
quality of the rooted cuttings. The variety
Tonda Romana is especially suitable for
propagation with hardwood cuttings due to the
high rooting percent.
References
1. Agele, S.O., Aiyelari, O.P., Obi, E.A.
(2013). Pattern of rooting and growth of
cuttings of some species of insecticidal and
medicinal importance as affected by growth
promoting substances. Oct. Jour. Env. Res.
Vol. 1(2): 151-160
bb
bbb
aa
b bbc
cdd
d
c cbc
aba
0
10
20
30
40
50
60
70
80
90
100
Tonda
Romana
Istarski Extra jagli Ludolf Hall’s
Giant
Devianna
Hazelnut variety
perc
en
t (%
)
rooting I-class II-class
31 A. Markovski, T. Arsov, V. Gjamovski
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JAFES, Vol 69, (2016)
2. Bacchetta, L., Aramini, M., Bernardini, C.,
Rugini. E. (2008). In vitro propagation of
traditional Italian hazelnut cultivars as a
tool for the valorization and conservation of
local genetic resources. HortScience 43,
562-566.
3. Bassil, N.V., Proebsting, W.M., Moore,
L.W., Lightfoot, D.A. (1991). Propagation
of hazelnut stem cuttings using
Agrobacterium zhizogenes. HortScience
26(8), 1058-1060.
4. Contessa C., Valentini N., Botta R. (2012).
Decreasing the concentration of IBA or
combination with ethylene inhibitors
improve bud retention in semi-hardwood
cuttings of hazelnut cultivar ‘Tonda Gentile
delle Langhe’. Scientia Horticulturae,
Volume 131, 22 November 2011, Pages
103–106.
5. Contessa C., Valentini N., Caviglione M.,
Botta R. (2011). Propagation of Corylus
avellana L. by Means of Semi-hardwood
Cutting: Rooting and Bud Retention in
Four Italian Cultivars. Europ.J.Hort.Sci., 76
(5/6). S. 170–175, 2011, ISSN 1611-4426.
6. Demchik M., McCown B., Fischbach J.,
Kern A., Zeldin E. (2011). A new Hazelnut
development Program in the lake states.
Agroforestry: A profitable land use.
7. Ercisli S. Read P.E. (2001): Propagation of
hazelnut by softwood and semi-hardwood
cuttings under Nebraska condition. Acta
Hort. 556, 275–279.
8. Fiskobirlik, (2003). Records of Union of
Agriculture Cooperatives for the Sale of
Hazelnut. Giresun, Turkye.
http://www.fiskobirlik.org.tr/
9. Lagerstedt H.B. (1983). The American nut
industry-filberts (Corylus avellana L.),
cultivars, culture production. North. Nut
Grow. Assoc. Annu. Rep. 74: 179-185.
10. Serek, M., Woltering, E.J., Sisler, E.C.,
Frello, S., Sriskandarejah, S. (2006).
Controlling ethylene at the receptor level.
Biotechnol. Adv. 24, 368-381.
Journal of Agricultural, Food and Environmental Sciences
UDC 631.459
Original Scientific Paper
____________________________________________________________________________________________________
SOIL EROSION EVALUATION IN THE RASTOCKI POTOK WATERSHED OF
MONTENEGRO USING THE EROSION POTENTIAL METHOD
V. Spalevic1*, D. Vujacic1, G. Barovic1, I. Simunic2, M. Moteva3, V. Tanaskovikj4
1*Department of Geography, Faculty of Philosophy Niksic, University of Montenegro
2Faculty of Agriculture, University of Zagreb, Croatia 3University of Architecture, Civil Engineering and Geodesy, Dpt. of Land Management, Sofia,
Bulgaria 4Agricultural Sciences and Food, Ss. Cyril and Methodius University, Macedonia
*corresponding author: velibor.spalevic@gmail.com
Abstract
Soil erosion is the most important factor of land degradation worldwide, causing significant
environmental problems in the region of South East Europe also. We studied soil erosion processes in
the RastockiPotok Watershed of Montenegro using the Erosion Potential Method (EPM) of
Gavrilovic, which is created in Yugoslavia and is the most suitable on catchment level for the
watershed management needs in this Region. The peak discharge (Qmax) is calculated on 150 m3s-1
and there is a possibility for large flood waves to appear in the studied basin. According to our
analysis, the coefficient fs, (portion under forest) is 0.45; ft (grass) is 0.41 and fg (bare land) is 0.14
and the coefficient of the river basin planning, Xa, is 0.52. Real soil losses, Gyr, were calculated on
1472m3yr-1, specific 250m3km-2yr-1. The value of the Z coefficient of 0.488indicates that the studied
watershed belongs in the Destruction Category III: the erosion process is medium. This study
confirmed the findings of the other Balkan researchers that the EPM method of Professor Gavrilovic
is a useful tool for calculating sediment yield in the South East Europe.
Keywords: Montenegro, watershed, soil erosion, runoff, Erosion Potential Method (EPM)
Introduction
Soil is an essential resource for the food chain
and our society. Soil formation is a slow
process, while soil destruction can be rapid.
Hence, soil is considered a non-renewable
resource, and its sustainability is important.
Among the threats to soil is erosion, which is a
natural phenomenon that can be impacted by
global change (Paroissien, 2015).
The issue of sediment yield and runoff and
their factors is one of the hot spots in
hydrological science. Various studies show
that sediment yield and runoff in a river basin
are mainly affected by local natural conditions,
such as precipitation, vegetation coverage,
terrain, lithology, and soil structure, as well as
human activities (Xu 2006). Quantitative
information on sediment yield and runoff is
needed for erosion risk assessment. Besides
field and laboratory investigation, erosion risk
models have proved to be good tools to
understand these processes (Boardman, 2006).
This study aims to estimate the annual
sediment yield, due to rainfall and runoff, at
theoutlet of RastockiPotok River basin, which
is located in north Montenegro. The main
processes quantified in the study are runoff
resultingfrom rainfall, soil erosion due to
rainfall and runoff, inflow of soil erosion
products intostreams, and sediment transport
in streams. The quantification leads to the
computation of sediment yield at the basin
outlet.
Erosion Potential Method (EPM) of Gavrilovic
(1972) was chosen for this study as it is widely
used in different studies in the Region (Bosnia
and Herzegovina, Macedonia, and Serbia).
Blinkov and Kostadinov (2010) evaluated
applicability of erosion risk assessment
methods for the Balkan region, considering
dependence on scale and different needs. The
EPM was, according to them, the most suitable
for the watershed management needs in this
Region. The EPM model was earlier validated
for simulating the processes of soil erosion and
33 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj
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JAFES, Vol 69, (2016)
sediment transport over the Polimlje River
Basin in North of Montenegro (Spalevic,
2011).
The new detailed report about the state of the
runoff and sediment yield in this format may
be used further in watershed management
sector of Montenegro, illustrating the
possibility of modelling of sediment yield with
such approach.
Materials and methods
We studied the area of the Rastocki Potok
drainage basin (6 km2), a right-hand tributary
of the river Lim.In terms of geomorphology
and climate, it is a part of the natural entity of
the Bijelo Polje Valley of the Polimlje region,
North of Montenegro (Figure 1).
Figure 1. Study area of the Rastocki drainage basin
The river basin of Rastocki Potok stretches
from its inflow to the River Lim (Hmin, 540 m)
to the tops of the hills over the villages
Cerovar and Krusev Do where the Hmax is
1278m. There is a flat area on the lower
alluvial terrace close to the inflow of the
34 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj
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JAFES, Vol 69, (2016)
RastockiPotok to the River Lim. The average
river basin decline, Isr, is calculated at 25.5%
and indicates that steep slopes prevail in the
studied river basin. The average river basin
altitude, Hsr, is calculated at 840 m; the
average elevation difference of the river basin,
D, is 300 m.
The detailed information on the soil erosion
processes were collected during the field visit.
This includes also the analysis of the status of
plant cover, the type of land use, and the
measures to reduce the erosion processes, as
well as determination of the slopes, specific
lengths, the exposition, the depth of the
erosion base and the density of erosion rills.
We used the data of Soils of Montenegro
(Djuretic and Fustic, 2000) for the studied area
of the RastockiPotok. Furthermore, some
pedological profiles had been reopened, and
soil samples were taken for physical and
chemical analysis. The granulometric
composition of the soil was determined by the
pipette method; the soil samples were air-dried
at 105°C and dispersed using sodium
pyrophosphate. The soil reaction (pH in H2O
and nKCl) was determined with a
potentiometer. The total carbonates were
determined by the volumetric Scheibler
method; the content of the total organic matter
was determined by the Kotzman method;
easily accessible phosphorous and potassium
were determined by the Al-method, and the
adsorptive complex (y1, S, T, V) was
determined by the Kappen method (Spalevicet
al., 2013).
Understanding of soil erosion processes is
essential in appreciating the extent and causes
of soil erosion and in planning soil
conservation. According to the previous
experience in the Region, the most reliable
method for determining the sediment yields
and the intensity of the erosion processes for
the studied area is the Erosion Potential
Method (EPM). This method was created,
developed, and calibrated in Yugoslavia
(Gavrilovic, 1972).
With the increased computing powers of the
last 20to 30 years, there has been a rapid
increase in the explorationof catchment
erosion and sediment transportthrough the use
of computer models (Merritt et al., 2003) and
have also been demonstrated in Montenegro,
specifically in the Region of Polimlje (Barovic
and Spalevic, 2015; Fustic and Spalevic, 2000;
Gazdic et al, 2015; Spalevic et al., 2015a;
Spalevic et al., 2015b; Spalevicet al., 2015c;
Spalevic et al., 2015d; Spalevic et al., 2015e;
Spalevic et al., 2014a; Spalevic et al., 2014b;
Spalevic et al., 2014c; Spalevic et al., 2014d;
Spalevic et al., 2013a; Spalevic et al., 2013b;
Spalevic et al., 2013c; Spalevic et al., 2013d;
Vujacic&Spalevic, 2015). That approach was
used in the research on the RastockiPotok river
basin.
These methods involve several steps: data
acquisition, model specification and estimation
(Madureiraa et al., 2011). We used the
program package Intensity of Erosion and
Outflow - IntErO (Spalevic, 2011) in this
research. This program is an integrated, more
modern second-generation version of the
program „Surface and Distance Measuring”
(Spalevic, 1999) and the program “River
basins” (Spalevic, 2000). We used this
program to obtain data on forecasts of
maximum runoff from the basin and the
intensity of the soil erosion. The EPM is
embedded in the algorithm of IntErO
computer-graphic method.
Results and discussion
Climatic characteristics.The climate and
human pressure on the land in the Rastocki
Potok river basin is very variable. The area is
characterised by short, fresh, dry summers;
rainy autumns and springs, and cold winters.
The absolute maximum air temperature is
39.2OC. Winters are severe, so much so that
negative temperatures can fall to a minimum
of -27.6 OC.
The temperatures are highest on average in
July, at 20.8 °C. January is the coldest month,
with temperatures averaging -5.6 °C.
It is well well-known fact that the
precipitations and runoff are direct driving
forces of soil erosion and sediment transport.
The least amount of rainfall occurs in July
(and August). Most of the precipitation here
falls in November (Figure 2).
35 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj
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JAFES, Vol 69, (2016)
Figure 2. Climate graph
The average annual air temperature, t0, is
8.9°C. The average annual precipitation, Hyr, is
873.7 mm. Temperature coefficients for the
region, T, is calculated at 0.99. The torrential
rain, hb, is calculated at 157.6 mm.
The geological structure of the area consists
mainly of Paleozoic clastic, carbonate and
silicate volcanic rocks and sediments of the
Triassic, Jurassic, Cretaceous-Paleogene and
Neogene sediments and Quaternary. In the
structural-tectonic sense, the area belongs to
the Durmitor geotectonic unit of the inner
Dinarides of Northern and North-eastern
Montenegro (Zivaljevic, 1989).
In order to define the permeability of the rocks
of the studied area we used both: the
Geological Atlas of Serbia (Dimitrijevic,
1992) and Geological Map of Montenegro
(Zivaljevic, 1989) and extracted a map of
permeability for the study area.
Figure 3: The structure of the river basin, according to bedrock permeability (fpp: medium; fo: low
permeability)
The coefficient of the region's permeability,
S1, is calculated to be 0.98. Within the studied
basin, the area with medium permeable rocks
(class fp) is 7% and the rest has poor
permeability (class fo) is 93%.
Soil characteristics of the area. According to
the results of the filed visits and
supplementary laboratory analysis, but also
using the previous research data of the project
Soils of Montenegro (1964-1988) of the team
of the Biotechnical faculty (Fustic & Djuretic,
2000), the most common soil types in the
studied river basin are: Dystric Cambisols and
Eutric Cambisols.
36 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj
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JAFES, Vol 69, (2016)
Figure 4: The structure of the river basin, according to the soil types
Land use. The structure of the Rastocki Potok
watershed, according to the land use is
presented in the Figure 5.
Figure 5: The structure of the river basin, according to the land use
According to our analysis, the coefficient fs,
(part of the river basin under forests) is 0.39, ft
(grass, meadows, pastures and orchards) is
0.45 and fg (bare land, plough-land and ground
without grass vegetation) is 0.16.
The coefficient of the river basin planning, Xa,
is 0.54. Of the total river basin area, related to
the river basin structure, degraded forests are
the most widespread form (25.41%). The
proportion is further as follows: Meadows,
24.72%; Plough-lands, 15.56%; Orchards and
vineyards, 13.72%; Well-constituted forests,
13.68%; Mountain pastures, 6.91%.
Soil erosion. The dominant erosion form in
the study area is sheet erosion with the
uniform detachment and removal of soil and
sediment particles from the soil surface by
overland flow and raindrop impact distributed
across slopes of the watershed. It has taken
place in all soils on slopes, being the most
pronounced on steep slopes with scarce or
denuded vegetation cover.
37 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj
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JAFES, Vol 69, (2016)
We used the software IntErO to process the
input data required for calculation of the soil
erosion intensity and the peak discharge.
A complete report for the Rastocki Potok river
basin is presented in Table 1.
Table 1. Part of the IntErO report for the RastockiPotok Watershed
Input data
River basin area F 5.88 km²
The length of the watershed O 10.55 km
Natural length of the main watercourse Lv 3.24 km
The shortest distance between the fountainhead and
mouth Lm 2.97 km
River basin length measured by a series of parallel
lines Lb 4.44 km
The area of the bigger river basin part Fv 3.46 km²
The area of the smaller river basin part Fm 2.42 km²
The area between the two neighboring contour lines fiz 0.76 km²
Altitude of the first contour line h0 600 m
Equidistance Δh 100 m
The lowest river basin elevation Hmin 540 m
The highest river basin elevation Hmax 1278 m
Very permeable products from rocks fp 0
Medium permeable rocks fpp 0.07
Poor water permeability rocks fo 0.93
A part of the river basin under forests fš 0.39
Grass, meadows, pastures and orchards ft 0.45
Bare land, plough-land and ground without grass
vegetation fg 0.16
The volume of the torrent rain hb 157.6 mm
Incidence Up 100 years
Average annual air temperature t0 8.9 °C
Average annual precipitation Hyr 873.7 mm
Types of soil products and related types Y 1.2
River basin planning, coefficient of the river basin
planning Xa 0.54
Numeral equivalents of visible erosion process φ 0.28 Results:
Coefficient of the river basin form A 0.64
Coefficient of the watershed development m 0.38
Average river basin width B 1.32 km
(A)symmetry of the river basin a 0.35
Density of the river network of the basin G 0.55
Coefficient of the river basin tortuousness K 1.09
Average river basin altitude Hsr 840.01 m
Average elevation difference of the river basin D 300.01 m
Average river basin decline Isr 25.49 %
The height of the local erosion base of the river basin Hleb 738 m
Coefficient of the erosion energy of the river basin's relief Er 150.86
Coefficient of the region's permeability S1 0.98
Coefficient of the vegetation cover S2 0.75
Analytical presentation of the water retention in inflow W 1.7325 m
Energetic potential of water flow during torrent rains 2gDF^½ 186.03 m km s
Maximal outflow from the river basin Qmax 150.81 m³ s-1
Temperature coefficient of the region T 0.99
Coefficient of the river basin erosion Z 0.488
Production of erosion material in the river basin W yr 5476.8969 m³ yr-1
Coefficient of the deposit retention Ru 0.269
Real soil losses G yr 1472.09 m³ yr-1
Real soil losses per km2 G yr km² 250.39 m³ km-² yr-1
38 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj
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JAFES, Vol 69, (2016)
(A) symmetry coefficient indicates that there
is a possibility for large flood waves to appear
in the river basin. The value of G coefficient of
0.55, indicates there is medium density of the
hydrographic network.
The value of 25.49% indicates that in the river
basin prevail steep slopes. The value of Z
coefficient of 0.488 indicates that the river
basin belongs to III destruction category. The
strength of the erosion process is medium, and
according to the erosion type, it is surface
erosion.
The value of 250.39 m³ km² yr-1indicates,
according to Gavrilovic, that the river basin is
a region of very weak erosion.
Conclusion
Several factors influenced the erosion
processes in the territory of the RastockiPotok
river basin. The most significant factors are
the area’s climate, relief, geological substrate
and pedological composition, as well as the
condition of the vegetation cover and the land
use. The peak discharge (incidence of 100
years) from the river basin, Qmax, is 150.81 m³
s-1and is suggesting the possibility of a large
flood. The strength of the erosion process is
medium, and the erosion type is surface
erosion. The predicted soil losses were 1472
m³ yr-1, specific, 250m³ km-² yr-1. According to
Babic et al (2003) from the “Jaroslav Cerni”
Institute for the Development of Water
Resources (JCI), the leading research
organization in Serbia’s water sector, real soil
losses are 350 m³ km-² yr-1for the Lim river
basin. By using the IntErO software to
estimate the soil losses per km2 in 57 river
basins of Polimlje, the average value
was331.78 m³ km-² yr-1(Spalevic, 2011). This
study confirmed the findings of the other
Balkan researchers that the EPM method of
Professor Gavrilovic is a useful tool for
calculating sediment yield in the South East
Europe. EPM is embedded in the algorithm of
IntErO computer-graphic method.
Acknowledgement
This research was funded by the Ministry of
Science of Montenegro, Project: Soil erosion
processes in the Polimlje Region, Montenegro.
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(2015e): Soil erosion in the River Basin of
Provala, Montenegro. Agriculture and
Forestry 61(4): 133-143.
16. Spalevic, V., Curovic, M., Andjelkovic, A.,
Djekovic, V., Ilic, S. (2014a): Calculation
of soil erosion intensity in the Nedakusi
Watershed of the Polimlje Region,
Montenegro. International Scientific
conference: Challenges in modern
agricultural production, December 11,
2014, Skopje, Macedonia.
17. Spalevic, V., Tazioli, A. Djekovic, V.,
Andjelkovic, A., and Djurovic, N. (2014b):
Assessment of soil erosion in the Lipnica
Watershed, Polimlje, Montenegro. The 5th
International Symposium “Agrosym 2014”,
Jahorina, 23-26 October 2014, Bosnia and
Herzegovina, p 723-729.
18. Spalevic, V., Hübl, J. Hasenauer, H. and
Curovic, M. (2014c): Calculation of soil
erosion intensity in the Bosnjak Watershed,
Polimlje River Basin, Montenegro. The 5th
International Symposium “Agrosym 2014”,
Jahorina, 23-26 October 2014, Bosnia and
Herzegovina, p 730-738.
19. Spalevic, V., Curovic, M., Billi, P., Fazzini,
M. Frankl, A., and Nyssen, J. (2014d): Soil
erosion in the ZimPotok Watershed,
Polimlje River Basin, Montenegro. The 5th
International Symposium “Agrosym 2014”,
Jahorina, 23-26 October 2014, Bosnia and
Herzegovina, p 739-747.
20. Spalevic, V., Djurovic, N., Mijovic, S.,
Vukelic-Sutoska, M., Curovic, M. (2013a):
Soil Erosion Intensity and Runoff on the
Djuricka River Basin (North of
Montenegro). Malaysian Journal of Soil
Science, Vol. 17: p.49-68.
21. Spalevic, V., Curovic, M. Tanaskovik, V.,
Oljaca, M., Djurovic, N. (2013b): The
impact of land use on soil erosion and run-
off in the Krivaja river basin in
Montenegro. The First International
Symposium on Agricultural Engineering,
4th - 6th October 2013, Belgrade–Zemun,
Serbia, VI: 1-14.
22. Spalevic, V., Nyssen, J., Curovic, M.,
Lenaerts, T., Kerckhof, A., Annys, K. Van
Den Branden, J., Frankl, A. (2013c): Тhe
impact of land use on soil erosion in the
river basin Boljanska Rijeka in
Мontenegro. In proceeding of the 4th
International Symposium “Agrosym 2013”.
p. 54-63.
23. Spalevic, V., Curovic, M., Uzen, N.,
Simunic, I., Vukelic-Shutoska, M. (2013d):
Calculation of soil erosion intensity and
runoff in the river basin of Ljesnica,
Northeast of Montenegro. In proceeding of
the 24th International Scientific-Expert
Conference on Agriculture and Food
Industry, Sarajevo, Bosnia and
Herzegovina.
24. Spalevic, V. (2011): Impact of land use on
runoff and soil erosion in Polimlje.
Doctoral thesis, Faculty of Agriculture of
the University of Belgrade, Serbia, p 1-260.
25. Spalevic V., Dlabac A., Spalevic B., Fustic
B., Popovic V. (2000): Application of
computer - graphic methods in the research
of runoff and intensity of ground erosion - I
program "River basins". Agriculture and
Forestry.46(1-2): 19-36.
26. Spalevic, V. (1999): Application of
computer-graphic methods in the studies of
draining out and intensities of ground
erosion in the Berane valley. Master
thesis.Faculty of Agriculture of the
University of Belgrade, Serbia, p.1-131.
27. Xu, J. X. 2006. Effect of the changing rural
socio-economic factors on sediment yield
40 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj
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of the Jialinjiang River Basin. Journal of
Mountain Science, 24(4), 385-394..
28. Vujacic, D., Spalevic, V. (2015):
Assessment of runoff and soil erosion in
the Radulicka Rijeka Watershed, Polimlje,
Montenegro. The 6th International
Symposium Agrosym 2015, Jahorina, 15-
18 October 2015, Bosnia and Herzegovina.
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SR Crne Gore, 1:200 000;
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VIII, Titograd.
Journal of Agricultural, Food and Environmental Sciences
UDC 626.82
Original Scientific Paper
____________________________________________________________________________________________________
WATER RESOURCES PLANNING MODELING FOR EFFICIENT MANAGEMENT
OF IRRIGATION CANAL
G. Patamanska1*
Institute of Soil science, Agrotechnologies and Plant Protection, Sofia, Bulgaria
*coresponding author: patamanska_g@yahoo.com
Abstract
In the last years the spreadsheet-based models are widely applied for water resources planning and
management. In this report, a model for planning water allocation from irrigation canal is presented.
Algorithm based on the water balance which allows for allocation of available water resources of the
source according to water requirements of crops in irrigated area, considering current technological
constraints was developed and implemented in Excel environment. An existing canal was as a case
study. The spreadsheet-based model provides support for efficient management of the irrigation canal.
Keywords: irrigation canal, water allocation, planning, spreadsheet-based model
Introduction
Planning of water allocation in irrigation
canals is an important managerial activity
aimed efficient use of water for irrigation,
minimizing yield losses of the irrigated crops
due to water deficit and water stress, also
preventing over supply and the negative
outcomes such as water logging and
salinization agricultural land.
Using the optimization methods and
computers, the operation of irrigation canals
can be planned effectively. Last decades many
models based of the integer linear
programming and mixed integer linear
programming techniques have been developed
for solving the problem of optimal water
allocation in irrigation canal (Anwar et al.,
2001; Ramesh et al., 2009; Santhi et al., 2000).
By reason of certain limitations in their
formulation few of the developed models were
used for water resources planning and
management. For practical use, computer
implementation of the planning algorithms is
good to be done in an accessible manner for
use of the engineering staff in charge of
operational management of irrigation system
(Steele et al., 2010). An alternative is the
software application EXCEL, which as part of
Microsoft Office is widespread and required
basic computer knowledge.
In this paper a model for planning water
allocation from run-of-the river irrigation
canal is presented. Algorithm based on the
water balance which allows for allocation of
available water resources of the source
according to water requirements of crops in
irrigated area, considering current
technological constraints was developed and
implemented in Excel environment. The
model was validated for an existing irrigation
canal.
Material and methods
Water delivery network of the most of the
existing irrigation systems consists of main
canal, which is flowing all irrigation season
and distributaries canals, which are controlled
periodically for need of delivery of irrigation
water to its command area. As water
requirements of the agricultural crops are
varied in the different growth stages, total of
the days of the irrigation season is divided to
the equal time intervals, a length of a week or
a decade (10 days). Water distribution
schedule is prepared on any day during the
time interval that enables allocation of
available water in terms of actual irrigation
water requirements considering the
technological constraints.
Mathematical formulation of the model
The planning model works on daily basis and
10-days irrigation period. As the main canal is
feeding variable river discharge, the river flow
is measured on any day of the time period.
Available net water discharge (daily supply at
42 G. Patamanska
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
the head of main canal minus losses in main
canal) is allocated to the distributary canals to
fulfill their demands in terms of water for
irrigation of the crops.
For proper execution of the plan of water
supply of manually operated distributary
canals, it is essential that the canal operation is
to be simple. In the present operation scenario,
distributary canals will be running at full, half
or nil capacity on every day during the
irrigation period. To keep daily water balance
in the main canal one of the canals will be
running in variable supply (Ramesh et al.,
2009).
Objective function
The objective function is defined as
maximization of the total supply to the
distributary for the entire irrigation period.
Mathematical representation of the objective
is:
Max
10
1 1k
lk
N
lii
ik QQ (1)
where k = day number, N= distributary canals
number, i = the distributary canal number, l =
distributary canal with varied supply number,
Qlk= daily supply in the lth distributary canal
on kth day (m3/s), Qik= daily supply in the ith
distributary canal on kth day(m3/s).
.day kon open fully isry distributa iwhen
day kon open half isry distributa iwhen 5.0
day kon closed isry distributa i when0
thth
thth
thth
i
iik
q
where qi= capacity of ith distributary canal
(m3/s).
In daily allocation of the net available
irrigation water at the head of the main canal
to the distributaries should be kept the
following technological constraints.
Main Canal Supply Constraint
To ensure the balance of water amounts in the
main canal the sum of supplies to distributary
on any day should be less than or equal to net
daily supply in the main canal:
kvlk
N
lii
ik QQQ 1
k=1,2…….10 (2)
where Qvk=net supply in the main canal on kth
day.
Distributary canal demand constraint
The sum of daily supply of the distributaries
for the irrigation period should be less than or
equal to demand for 10– day period.
Mathematical representation of this constraint
is:
i
k
ik DQ
10
1
i =1,2,…….N
And ≠l (3.1)
and for the distributary canal with
variable supply:
10
1k
llk DQ (3.2)
where Di= demand for ith distributary canal for
10–day period (m3/s), Dl = demand for ith
distributary canal with varied supply for 10–
day period (m3/s).
Canal capacity constraint
The water supplies to canals should not exceed
the capacity of the canals on any day during
the time period.
ii
vkv
max
max
(4)
where Qvmax= design capacity of the main
canal(m3/s), qmaxi=design capacity of the ith
distributary canal (m3/s).
In addition the distributary canal with variable
supply should be supplied discharge at least
equal to half design capacity to maintain
sufficient flow depth in the canal. This
limitation is expressed as follows:
llk
l qQq
max
max
2 k=1,2,……..10 (5)
These equations and constraints constitute a
mathematical model of plan of supply and
distribution of water in irrigation canal. Since
an optimization problem is formulated the
solution is an optimal water allocation plan
which enables water supply of distributaries
canals in accordance with the water
requirements of the irrigated crops.
In this study an approach to be found in Excel
environment an approximate solution for the
optimization problem (1)-(5) is adopted.
43 G. Patamanska
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
Figure 1. Layoutof the main canal of "Stryama-Chirpan” Irrigation system
Results and discussion
The spreadsheet model for operational
planning of supply and distribution of water
was developed and validated with data main
canal "Stryama-Chirpan" irrigation system
(Figure 1). The water source for this irrigation
system is the Stryama River. The main canal
works during the irrigation season from May
to October and irrigates 1,843 ha agricultural
area planted with rice, corn and vegetables.
The canal has five distributaries. Water for
rice fields is supplied by two open canals.
Three conduits are located on the canal course.
Details of the distributaries have been given in
Figure 1.
The proposed algorithm based on the water
balance was built in this table using Excel
capabilities for consecutive estimates and
available logic functions. No Visual Basic
macros were used for the model development
in Excel environment. The only macro was
designed to reset the table before any new
estimate thus provides an opportunity for
repeated use of the table. The spreadsheet
layout is shown on Figure 2.
0 кm
Р-1 2 m3
/s
Р-2 4,2 m3
/s
Р-2-1
ГВ-2 1,5 m3
/s
ГВ-4 1 m3
/s
ГВ-5 2,2 m3
/s
Legend: Р - Irrigation canal
ГВ - Conduit
44 G. Patamanska
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
Figure 2.Spreadsheet layout for planning of water allocation from main canal of "Stryama-Chirpan” Irrigation
system.
The input data needed to start the calculations
are daily river discharge, minimum river flow
rate, canal losses, demands of the distributaries
canals for 10–day period (m3/s), defined on the
basis of net irrigated norms of irrigated crops.
Input data are entered in the boxes from the
table, colored in purple.
The net supply values at the head of the main
canal for any days of the irrigation period are
located in the third column of the table. In the
next columns each of the distribution canals
has a box in which the values of supply for
each day of the interval are entered. The head
cell of this box contains maximum capacity of
the distributary.
Preparation of the water allocation plan
For each day of the period initially the daily
measured value of river discharge is entered
and on its basis the net daily supply at the head
of the main canal is calculated as the
difference of measured river discharge minus
the sum of the amount of canal losses and the
minimum river flow rate. Then selection of the
operational discharges of distributary canals is
made.
When entering a value of operational
discharge of a distributary canal, the water
balance in the main channel is monitored from
the result in the cell in the last column of the
table "Canal Outflow ". In obtaining a
negative result, the supply to the canal should
be reduced or stopped.
Based on the entries of distributary canals on
any day of the period, water discharge value of
the distributary canal P-1, which is assumed to
operate at variable supply is automatically
calculated from the water balance equation
and in accordance with the restrictions (2) -
(5). Implementation of the target (1) is
monitored by calculating the deviation of
water delivery to each distributary from the
requested.
The model was tested with data for flow of the
Stryama River for the lastten days of June. At
the beginning of the period the flow rate of the
river is high 8-10 m3/s, but in the last days the
main canal can be supplied less water
discharge 5.3 m3/s The model shows how to manage
distributaries in the 10-day period to fulfill the
requests. Request of the canal P-2 is satisfied,
when it runs at maximum capacity during the
irrigation period. Request of conduits ГВ-2,
ГВ-4 и ГВ-5 are met for 3consecutive days at
work at half capacity. The obtained delivery
schedule for the canal with a variable supply is
shown on Figure 3. Its implementation does
not require frequent changes of the regulating
structure at its head. Total, the accuracy of
45 G. Patamanska
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JAFES, Vol 69, (2016)
meeting the requests of canals is relatively
high - 4.9%. For the conduits the deviations
are greater. This is due to the fact that the
canals are oversized relative to the actual
needs of the water for irrigation. Also,
assuming that the distributaries work
completely open or half capacity brings
approach in determining the solution of the
problem for optimal operational planning.
Figure 3. Delivery schedule for the canal with a variable supply
It is appropriate to choose the days that water
will be delivered in the canals that do not work
continuously close to the dates for watering
the crops cultivated in the command area of
the distributary. In order to minimize
operational losses of the water is also
appropriate to adopt operational sequence of
distributaries canals "down-up" as the water
supply to the canal up stream can immediately
begin after stopping the supply of canal
downstream.
Conclusions
The main objective of the modeling in this
study is daily allocation of the net available
irrigation water at the head of the main canal
to the distributaries in accordance with water
requirements and technological constraints.
The model developed was validated for
existing irrigation canal. Its use for preparation
a schedule for distribution and supply of water
in the irrigation canal does not create
particular difficulties and satisfactory results
were obtained. The spreadsheet-based model
can provide support for efficient management
of the irrigation canal.
References
Anwar A., Clarke D., (2001). Irrigation
Scheduling Using Mixed-Integer Linear
Programming, Journal of Irrigation and
Drainage Engineering, 127(2), pp. 63-69.
Ramesh R., Venugopal K., Karunakaran K.
(2009).Zero One-programming model for
Daily Operation Scheduling of Irrigation
Canal, Journal of Agricultural Science, 1(1).
Santhi C., Pundarikanthan V.N. (2000). A
New Planning Model for Canal Scheduling of
Rotational Irrigation. Agricultural Water
Management, Vol. 43, pp. 327-343.
Steele, D.D., Scherer T.F., Hopkins D.G.,
Tuscherer S.R., Wright J. (2010).Spread shee
timplementation of irrigation scheduling by
the checkbook method for North Dakota and
Minnesota. Appl. Engr. Agric.26(6) pp. 983-
995.
Journal of Agricultural, Food and Environmental Sciences
UDC 712.25(498)
Original Scientific Paper
____________________________________________________________________________________________________
THE MANAGEMENT AND CAPITALIZATION OF THE LANDSCAPING
POTENTIAL OF THE CRUCII SQUARE FROM TIMISOARA CITY
C. Berar 1*, M. Silivasan1, E. Pet1, A. Groszler1, C. Tota1, D. Camen1 1Banat’s University of Agricultural Sciences and Veterinay Medicine
“King Michael I of Romania” from Timisoara
*corresponding author: cristianberar@yahoo.com
Abstract
The Crucii Square is situated in the Elisabetin district in the city of Timisoara, in a residential area.
According to a map from 1849, the current Crucii Square is situated on the very line of the building
injunction circle around the fortress of Timisoara. The square name originates from an old cross
which was preserved until today. Taking into the age of the oldest trees, the square was set as a green
space after 1920. The current landscaping consists in tracing and slabbing the allies and building a
new hero monument, also dates from after 1920. The square’s surface is of 6255mp. In the present
paper we carried out an estimate of the green space and determined the current vegetation state, since
green cadastre is the only way to determine the real state of green spaces belonging to a city’s
patrimony, including parks and squares as well as the entire street vegetation (Ciupa et al., 2005). The
paper‘s character is thus that of a vegetation fund inventory, as well as organisational design based on
ecologic and landscaping criteria. The paper also comprises a square landscaping proposal,
highlighting the site’s historic character and the high vegetation value.
Key words: Crucii Square, green cadastre, identification, capitalization, management
Introduction
The existence of a green cadastre in a big city
is indispensable for a modern approach of the
optimal relation issue, of ecologic and social
nature, between a city’s manager and its
inhabitants. It is the only way to get to know
the reality of green spaces which enter a city’s
patrimony, including parks as well as the
entire street vegetation. It is also the only way
to properly manage, from a technical as well
as economic point of view, this important city
component.
Material and methods
For each woody vegetation element identified
in the field according to its position in the
plan, after the topographic determinations, the
following characteristics have been collected
and registered in code as follows (Primaria
Municipiului Timisoara, 2001):
1. Identification number corresponding to the
one in the plan –NRI.
2. Scientific name – SPE.
3. Age – VIR: 1– 10 years – code 11; 11– 20
years – code 12; 21– 40 years – code 20; 41–
60 years – code 30; 61– 80 years – code 40;
81–100 years – code 50; over 100 years – code
60.
4. Height classes – INA: 1 - 1 – 5 m; 2 - 6 –
10 m; 3 - 11 – 15 m; 4 - 16 – 20 m; 5 - 21 - 25
m; 6 - 26 – 30 m; 7- 31 – 35 m.
5. Crown diameter – DCO.
6. Crown structured (standard) volume – VRE.
7. Ecologic value – VAE.
Tree and shrub ecologic value is determined
by their influence on the surrounding areas’
physical-climatic factors. This influence
depends directly especially on the tree and
shrub crown, respectively on its volume and
branch and leaf density. The effects of the tree
and shrub crown reflect on the following
climatic elements: solar energy absorption;
atmospheric turbulence – wind intensity
reduction; CO2 absorption; oxygen emission;
filter effect on the solid particles from the
atmosphere; negative ion emission; phytoncide
emission; phonic isolation.
In order to determine this relative structured
volume, we can use the following formula:
Ecologic value = crown volume x crown
density indices
47 C. Berar , M. Silivasan, E. Pet, A. Groszler, C. Tota, D. Camen
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JAFES, Vol 69, (2016)
As a maximum crown density index, with the
value 1, one may take the de sycamore, linden,
spruce, fir crown one. For all other species,
this index is established by estimation, its
minimum possible value being 0.5.
For the efficiency in the ecologic value
expression, absolute values are grouped as
follows: standard crown value 2 mc - cod
1; 2,1 - 10 mc - cod 2; 10,1 - 20 mc - cod 3;
20,1 - 40 mc - cod 4; 40,1 - 80 mc - cod 5;
over 80,1 mc - cod 6.
8. Landscaping value –VPE.
The landscaping value is an element of high
importance in characterizing the park’s woody
vegetation. The park’s recreational and
educational function is fully correlated with
this value.
This value generally depends on three
characteristics: general species physiognomy
in singular port; the specimen’s height, crown
and trunk, which depend especially on the age;
trunk anomalies such as: tree forks, twisting
etc. Regarding the general species
physiognomy, the following are basic
elements: general crown shape, leafage and
structure, leaf colour, including its variation in
time, blooming, remnant fructification.
Another basic characteristic is the specimen’s
size which impresses through its grandeur and,
implicitly, through the specimen’s age
estimation. Anomalies impress because of
their rarity and singularity. From these
characteristics, the last two have a permanent
character, while the first presents a
conjunctural, dynamic character and thus of a
variable impressive value. Resineferous trees
are the exception, for whom this characteristic
is permanent, thus increasing their value.
The landscaping estimation stages used in the
project are: Very low – code 1; Low – code 2;
Medium – code 3; High – code 4; Very high –
code 5; Exceptional – code 6 .
9. Global value – VGL. It is established by the
computer using the formula: VGL = VAE x
VIT x VPE
This value may vary between 0 when the
vitality is 0 – dried tree and 108, at maximum
values (VAE = 6; VIT = 3; VPE = 6). The
maximum value is encountered very rarely, as
in the example of a monumental sycamore
forest. This global value bears a special
significance for the establishment of a park’s
importance, or for the establishment of
penalties in the case of some element
destruction.
10. Proposed works.
Several works are foreseen: intact maintenance
— code 1; toileting, pruning — code 2; dry
extraction — code 3; biologically inadequate
extraction — code 4; landscaping inadequate
extraction — code 5.
Results and discussion
31 species have been identified, which
represent a quite high variety for the square
surface. The resineferous proportion is of 20%,
and the shrub’s also of 20%. From this aspect,
the structure is relatively close to that of a
park. The high young specimen number, under
20 years, representing 83%, determine a rather
high density: 193 specimens / ha. There are
also some older specimens, even above 80
years, proving just how old the landscape is.
. Picture 1. Crucii Square – Google Earth view
48 C. Berar , M. Silivasan, E. Pet, A. Groszler, C. Tota, D. Camen
______________________________________________________________________________________________________________________________________________________
JAFES, Vol 69, (2016)
Picture 2. Crucii Square – current situation plan
The cover index is reduced, 24%, and the
ecologic layer thickness carries a medium
value of 0.80 m. The square is designed in a
mixed style. As elements of a regular style,
one can mention: the regular and somewhat
symmetrical style of the alley network, the
execution of a central focal point,
“monumental – cross”, towards which the
perspective of most alleys tends, bench
alignment, facing towards the central focal
point, the central high vegetation placement,
thus achieving a premises effect. All in all, the
square displays a balanced design and achieves
a valuable impressive effect. Due to lack of
space, in Table 1 is presented trees and shrubs
description inventory only for 40 specimens
out of a total of 191.
Table 1. Trees and shrubs description inventory
No Species denomination Age
class Height
Crown
diam.
Struct.
volume
Ecol.
value
Landsc.
value
Proposed
works
1 AESCULUS HIPPOCASTANUM 40 3 6.0 135.68 6 4 1
2 ABIES ALBA 12 1 1.0 0.56 1 3 1
3 SPIRAEA VANHOUTTEI 12 1 3.0 11.28 3 2 1
4 AESCULUS HIPPOCASTANUM 11 1 2.0 2.48 2 2 2
5 SPIRAEA VANHOUTTEI 12 1 2.0 5.04 2 2 1
6 ROBINIA PSEUDOACCACIA 11 1 2.0 2.17 2 1 1
7 ROBINIA PSEUDOACCACIA 11 1 2.0 2.17 2 1 1
8 ROBINIA PSEUDOACCACIA 30 2 5.0 47.12 5 4 1
9 AESCULUS HIPPOCASTANUM 40 3 7.0 134.61 6 4 1
10 FRAXINUS AMERICANA 20 2 7.0 107.73 6 3 1
11 ABIES ALBA 12 1 1.0 0.64 1 3 1
12 AESCULUS HIPPOCASTANUM 40 4 8.0 241.12 6 4 1
13 ACER NEGUNDO 40 3 9.0 228.90 6 4 1
14 PICEA ABIES 30 3 3.0 21.18 4 4 1
15 FRAXINUS AMERICANA 30 4 5.0 70.68 5 4 1
16 AESCULUS HIPPOCASTANUM 40 4 10.0 384.65 6 5 1
17 ABIES ALBA 12 1 1.0 0.64 1 3 1
18 THUJA ORIENTALIS 20 1 0.8 0.80 1 4 1
20 PRUNUS CERASIFERA 11 1 1.0 0.35 1 1 1
21 BETULA VERRUCOSA 11 1 0.6 0.18 1 1 1
22 THUJA ORIENTALIS 20 1 1.0 1.28 1 3 1
23 ACER PLATANOIDES 12 2 4.0 17.57 3 2 1
49 C. Berar , M. Silivasan, E. Pet, A. Groszler, C. Tota, D. Camen
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JAFES, Vol 69, (2016)
24 PINUS STROBUS 12 2 2.0 7.52 2 4 1
25 ROBINIA PSEUDOACCACIA 12 2 4.0 17.57 3 2 1
26 JUGLANS REGIA 12 2 5.0 47.10 5 2 1
27 ACER PLATANOIDES 12 2 3.0 33.92 4 2 1
28 ACER NEGUNDO 40 2 7.0 103.86 6 4 1
29 JUGLANS REGIA 20 2 5.0 78.48 5 3 1
30 FRAXINUS AMERICANA 40 4 10.0 329.70 6 4 1
31 AESCULUS HIPPOCASTANUM 40 2 6.0 39.55 4 4 1
32 ROBINIA PSEUDOACCACIA 30 1 1.0 0.64 1 4 1
33 ACER PLATANOIDES 12 2 2.0 6.58 2 2 1
34 ACER PLATANOIDES 12 2 2.0 6.58 2 2 1
35 AESCULUS HIPPOCASTANUM 40 3 6.0 98.91 6 4 1
36 AESCULUS HIPPOCASTANUM 40 4 7.0 242.34 6 4 1
37 ACER PLATANOIDES 12 2 2.0 2.17 2 2 1
38 AESCULUS HIPPOCASTANUM 40 4 7.0 161.56 6 4 1
39 ABIES ALBA 12 1 1.0 0.56 1 3 1
40 ACER PLATANOIDES 12 2 3.0 19.81 3 2 1
Table 2. Centralizing species situation – specimen no. and crown surface
Centralizing species situation – specimen no. and crown surface
No. Species denomination Crown surface
Specimen no.
1 ABIES ALBA 3.140 4
2 ACER NEGUNDO 228.435 5
3 ACER PLATANOIDES 43.175 7
4 AESCULUS HIPPOCASTANUM 364.240 11
5 BETULA VERRUCOSA 12.843 2
6 CATALPA BIGNONIOIDES 22.765 3
7 DEUTZIA SCABRA 31.400 13
8 FORSYTHIA INTERMEDIA 5.495 4
9 FRAXINUS AMERICANA 164.065 7
10 FRAXINUS EXCELSIOR 445.095 13
11 JUGLANS REGIA 39.250 2
12 JUNIPERUS SQUAMATA MEYERI 0.785 1
13 LONICERA FRAGRANTISSIMA 10.990 3
14 PHILADELPHUS CORONARIUS 8.831 6
15 PICEA ABIES 28.260 4
16 PINUS NIGRA 43.960 6
17 PINUS STROBUS 20.410 8
18 PINUS SYLVESTRIS 25.120 2
19 PLATANUS ACERIFOLIA 63.585 1
20 PRUNUS CERASIFERA 87.920 5
21 PRUNUS PISSARDI 45.530 4
22 ROBINIA PSEUDOACCACIA 230.005 41
23 SALIX MATSUDANA 69.865 2
24 SAMBUCCUS NIGRA 12.560 1
25 SPIRAEA VANHOUTTEI 13.345 3
26 TAXUS BACCATA 25.120 6
27 THUJA OCCIDENTALIS 0.785 1
28 THUJA OCCIDENTALIS
AUREO-VARIEGATA 0.785 1
29 THUJA ORIENTALIS 4.427 3
50 C. Berar , M. Silivasan, E. Pet, A. Groszler, C. Tota, D. Camen
______________________________________________________________________________________________________________________________________________________
JAFES, Vol 69, (2016)
30 TILIA CORDATA 127.170 5
31 TILIA PLATYPHYLLOS 58.090 2
TOTAL 2237.446 176.000
Proposal for the re-landscaping of the
Crucii Square
The landscaping way aims to fulfil the
following functions: social, decorative, and
recreational. The decorative or aesthetic
function will be achieved through material
alternation, succession, chromaticity as well as
various textures, in vertical as well as
horizontal plain turning the park into a living
mechanism in continual transformation.
Picture 3. Top view proposal
The decorative function is supported by the
usage of dendrologic material already existent
which forms a „curtain", conferring the space
an intimacy nuance. The vegetation influence
is directly or indirectly reflected in the
people’s health. Air purity, lower day or
season temperature amplitudes or the tree
shadow exercise a direct physical-sanitary
action on the organism, while the line, shape
and colour harmony, the aesthetic tree, shrub
and flower grouping enchant the eye, creating
a positive state of mind which, in its turn,
positively influences the general state of mind.
Through oxygen production and carbon
dioxide consumption, the vegetation,
especially the woody one, contributes to the
obvious air composition improvement,
insuring life maintenance. Today, we
acknowledge the fact that negative ions have a
positive influence on the psyche. Their
presence is insured by natural ionizing factors,
by ion generators, alongside which the woody
vegetation, through the photosynthesis
process, contributes to a large extend to air
ionization. Also, the sharp points of the leaf
needles facilitate, under certain atmospheric
conditions, electricity discharge in the soil.
Picture 4. 3D perspective
Through subtle means like colour and shape
harmony, suave perfumes, leaf murmuring,
fragile grace or impressive firmness, life pulse
in every leaf, flower, branch, the vegetation
touches people’s sensitivity, positively
influencing their psychological tonus (Iliescu,
2003). It is known that people’s health is
influenced not only by environmental balance,
but also by compensating the physical and
intellectual effort and nervous strain through
recreational activities (Florincescu, 1999). For
city inhabitants, the open air recreation option
is conditioned by the necessary moving time,
the movement facilitation, the landscape
organization and design, their natural
ambiance etc. The benches introduced in the
51 C. Berar , M. Silivasan, E. Pet, A. Groszler, C. Tota, D. Camen
______________________________________________________________________________________________________________________________________________________
JAFES, Vol 69, (2016)
landscape will be placed in the centre focal
area but also on the entire alley length. There
will be an adequate garbage bin number and
the lighting will also be optimal. There shall
be easy access, all alleys being traced in a
hierarchical order (secondary alleys flowing
into main alleys). The composition is unitary,
coherent and simple.
Picture 5. 3D perspective
The harmony is achieved by identity, as well
as resemblance, and the succession of certain
elements is accomplished by logical order,
harmonizing the various spaces complex.
Within this landscape the harmonious
combination of simplicity and variety was
achieved. The visitor perceives the space as a
unitary whole. The proportionality principle is
especially highlighted by the use the individual
scale so as to offer visitors heightened comfort
impression and to eliminate the overwhelming
element sensation. The space must offer a
welcoming place that is why where elements
were designed on an individual scale. The
rhythm is differentiated by means of various
dimension circle usage, even though it may
create monotony. Due to the fact that the
elimination of the existing vegetation was
avoided as much as possible, as well as the
fact that local, rustic plants were integrated in
the landscape, from the start conditions were
created for the plant biologic potential
achievement as well as the harmonious
development of all existing species. From a
technical point of view, we adopted solutions
to satisfy movement safety and comfort
requirements, but which are simultaneously
aesthetic and harmonizing with other
landscape elements. For the landscaping, we
used natural elements instead of manufactured
ones, as well as the maximum capitalization of
the terrain possibilities, function adaptation
and the establishment of the equipment in
relation with the previous elements,
interweaved with the compositional and
aesthetic organization. The landscape can be
accessed through four entrances. The alleys
follow itineraries linking the main interest
focal point (compositional centres, entrances,
objectives). They are of various widths. Their
functional role is organically intertwined with
their compositional importance. The
landscaping needs to encompass circulation
itineraries which firstly answer some
functional requirements such as insuring
visitor access to well-chosen points, leading
visitors to several areas fulfilling various
functions, connecting objectives included in
every part of the landscape, insuring
movement comfort and influencing traffic on
drive areas. Species proposed for the
landscaping: trees (Tilia tomentosa, Acer
palmatum, Populus tremula, Quercus rubra,
Acer saccharineum, Citrus bergamia, Fagus
grandifolia), shrubs (Sambucus cerulea,
Lonicera caerulea, Hibiscus rosa-sinensis,
Chaenomeles superba Texas Scarlet), flower
plants (Coreopsis gigantea, Anagallis
arvensis, Aster alpinus, Centaurea cyanus, Iris
croatica, Petunia hybrida, Impatiens new
guinea, Aster amelus).
Conclusions
The following works are foreseen: toileting
and pruning, dried branch cutting, extraction
of the dried specimens, as well as of the
inadequate ones, from a biological and
landscaping point of view, the execution of a
minimum of 4-5 mowing in summer, with
immediate grass collecting. On surfaces where
the carpet density is reduced, we propose
either the rehabilitation of the entire vegetal
carpet, or the execution of Lolium perene over-
seeding. The following maintenance works are
deemed necessary: alley repairing, repairing or
replacing deteriorated benches, garbage bin
supplementing.
52 C. Berar , M. Silivasan, E. Pet, A. Groszler, C. Tota, D. Camen
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JAFES, Vol 69, (2016)
References
Ciupa V., Radoslav R., Oarcea C., Oarcea Z.
(2005). Timisoara verde – sistemul de spatii
verzi al Timisoarei. Editura Marineasa.
Timisoara. pp. 116-117.
Florincescu Adriana (1999). Arhitectura
peisajului. Editura Divya. Cluj-Napoca. pp.
69-80.
Iliescu, Ana-Felicia (2003). Arhitectura
peisagera. Editura Ceres. Bucuresti pp. 189-
247.
Primaria Municipiului Timisoara (2001).
Cadastrul Verde al Primariei Municipiului
Timisoara. Editura Brumar. Timisoara pp. 37-
52.
Journal of Agricultural, Food and Environmental Sciences
UDC 631.526.4(497)
Original scientific paper
__________________________________________________________________________________________
PLANT GENETIC RESOURCES FROM THE BALKAN PENINSULA IN THE
WORLD’S GENEBANKS
H. Knüpffer*
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr. 3, D-
06466 Stadt Seeland, Germany
*corresponding author: knupffer@ipk-gatersleben.de
Abstract
An overview is given of plant genetic resources that originate from countries of the Balkan Peninsula
and are preserved in genebanks worldwide. For each country, the number of genebanks holding ma-
terial from this country, and the number of accessions are presented. A summary is also provided by
crops (scientific names). The survey is based on databases such as FAO WIEWS (World Information
and Early Warning System), EURISCO (European search catalogue for plant genetic resources), and
Genesys (worldwide database on plant genetic resources).
Key words: genebanks, Balkan Peninsula.
Introduction
The Balkan Peninsula, also called the Balkans,
is considered to include Albania, Bosnia and
Herzegovina, Bulgaria, Croatia, Greece,
Kosovo, the Republic of Macedonia,
Montenegro, Serbia, Slovenia, Romania, and
the European part of Turkey. For the present
study, we exclude the European part of Turkey
(which is difficult to distinguish from Turkey
as a whole by the data accessible through the
sources used), and additionally include the
Republic of Moldova.
According to the FAO World Information and
Early Warning System (WIEWS), the total
number of genetic resources accessions
preserved in genebanks worldwide is
7,199,179 (WIEWS 2015). Of these, 126,230
accessions (or 1.8 percent) are originating
from countries of the Balkan Peninsula. Based
on data from three international information
systems on plant genetic resources, namely,
WIEWS, EURISCO and Genesys (details see
below), we present information on the number
of accessions originating from each of the
Balkan countries, their distribution across
genebanks worldwide, and their taxonomic
composition (major species and genera).
For individual countries of the Balkan region,
similar overviews have been carried out (e.g.
Knüpffer 2010a, b for Greece), and for
Albania, the composition of the genetic
resources collections was studied (Gixhari et
al. 2013), but for the complete Balkan region,
this is the first study of its kind.
Material and methods
There are three international online databases
available that contain data relevant for this
study.The following databases were searched
in September 2015: WIEWS (WIEWS 2015),
Genesys (a worldwide database on plant
genetic resources; Genesys 2015), and
EURISCO (European search catalogue for
plant genetic resources; EURISCO 2015).
WIEWS gives summary information on
germplasm preserved in genebanks worldwide;
the data were last updated between 1984 and
2014 (the majority in 2008 and 2009). Genesys
includes accessions from EURISCO
(transferred on request), the genebanks of the
CGIAR centres, and the USDA genebank. The
majority of records related to Balkan-origin
accessions were last updated in April, and
some in September 2015. Data in EURISCO
are being updated whenever a National Focal
Point (person authorizedto collect data within
the country and to upload them to EURISCO)
updates the respective National Inventory.
For the same holding institution (genebank),
data in Genesys are generally more up-to-date
than in WIEWS, and even more so in
EURISCO, since Genesys is receiving
EURISCO data from time to timeon request.
54 H. Knüpffer
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
A selection was made for accessions
originating from any of the Balkan countries,
and relevant data fields were extracted or
calculated, i.e. number of accessions, holding
genebank, genus, species, country of origin,
status of sample, source of information, and
date of last update of the information. These
data were transformed into the same format
and combined into a single table. For
genebanks appearing in more than one of the
databases, only the most recent data were
used.
Holding institutions are coded by FAO
institution codes downloadable from the FAO
WIEWS website (FAO 2015). An institution
may receive a new code if its name or
affiliation changes; thus the same institution
may occur under different codes. By taking
this into account, the number of different hold-
ing genebanks of Balkan material was reduced
from 359 to 345, and the total number of
accessions reported from 135,359 to 126,230.
There may be institutions that do not exist any
longer, but are still documented in WIEWS.
This is known to be the case in Albania (all
genetic resources collections have been
transferred recently to the centralized Albanian
genebank).
Scientific namesare a problematic issue in
databases, especially when the information is
compiled from a large number of different
sources (Hintum and Knüpffer 2010).
Therefore, they were checked for major
problems (format, contents of the field, and
spelling). The resulting list of names was sub-
mitted for analysis to the “List matching
service” of the Catalogue of Life (CoL 2015),
which returns for each scientific name its
status (e.g. accepted or synonym), and lists
unidentifiable names. Synonyms and
unidentifiable names were checked against the
taxonomic system of GRIN (USDA Genetic
Resources Information Network) (GRIN
2015). Thus, the number of different genus
names could be reduced from 752 to 697, and
the number of different species names
(combinations of genus and species) from
2,748 to 2,415. Names not found in GRIN
taxonomy were generally left unaltered.
Therefore, the number of different genera and
species reported is likely to be slightly biased
(too large).
Countries of origin. “Yugoslavia” is still
reported in many records as country of origin;
this could not be resolved into the single
follower-countries. In addition, the FAO
WIEWS database often combines material
from different countries into a single record,
without indicating the number of accessions
for each of the countries. The records
containing Balkan countries (together with
others) refer to a total of more than 13,000
accessions in 15 genebanks. Such records were
excluded from the statistics.
Results and discussion
Overview by holding genebanks and countries
Germplasm from the Balkans is reported tobe
held in a total of 345 genebanks in 61
countries. The genebanks holding the largest
collections of this material are located in
Bulgaria, Romania and Germany. Genebanks
with more than 200 Balkan-origin accessions
are shown in Table 1. Some countries have
more than one genebank; countries holding the
largest numbers of accessions of Balkan origin
are Romania, Bulgaria, USA, Australia and
Germany. Countries holding more than 200
such accessions are listed in Table 2.
Table 3 shows the countries of the Balkan
region, and the numbers of accessions
conserved in genebanks worldwide from each
of these countries. There are approximately
30,000 accessions each from Romania,
Bulgaria and Greece, followed by ca. 9,700
accessions from former Yugoslavia (present
country not specified). Material from Kosovo
(79 accessions) is reported by a single
genebank in the U.S.
In Table 4, the total numbers of germplasm
accessions held by genebanks in the Balkan
countries are compared with the numbers of
accessions originating from the holding
countries. In Albania, Croatia, Greece,
Montenegro, and Slovenia, more than 75
percent of the accessions originate from the
holding country.
Overview by status of the samples
According to the sample status, the germplasm
from the Balkans can be divided into various
categories, including wild, weedy forms,
landraces, advanced cultivars, and other
categories (cf. Table 5). The largest proportion
of the Balkan material belongs to traditional
cultivars and landraces, followed by breeding
or research material (with several
subcategories).
55 H. Knüpffer
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
For more than 17,000 accessions, the status is
unknown or not stated.
Taxonomic composition of plant genetic
resources from the Balkans
With respect to the taxonomic composition,
the germplasm from the Balkan Peninsula
belongs to 697 genera (Table 6) and 2,415
species (Table 7). These are likely to be slight
overestimates, since some of the synonyms
may not have been resolved. In fruit trees, for
example, the genus Prunusas well as a number
of smaller genera such as Amygdalus,
Armeniaca, Cerasus, Persica and others be-
longing to the same taxonomic group, were
reported as separate genera in the databases –
they were brought together under Prunus. In
addition, scientific names given at the level of
genus (e.g. Triticum sp.) are counted as
separate species. For 57 accessions, even the
genus name is not known (reported as
“unidentified” or “unknown”).
The most highly represented genera are
Triticum, Zea, Phaseolus, Hordeum, and
Trifolium (Table 6). At the species level, Zea
mays, Triticum aestivum, Phaseolus vulgaris,
and Hordeum vulgarehave the largest numbers
of accessions (Table 7).
Conclusions
Overviews of genetic resources material
originating from a particular country or region
provide a first indication of the wealth of crop
plant species and their wild relatives, and they
may assist in identifying gaps (need for further
collecting). They may also be a good starting
point for compiling checklists of cultivated
plant species (and possibly their wild relatives)
for certain areas, as has been shown by us for a
number of countries such as Italy (Hammer et
al. 1992, 1999).
The study was based solely on the three
databases, which have different geographical
scopes (from worldwide to European), and
which differ in their up-to-dateness. Therefore,
some recent changes may not have been
reflected. It is known that in some countries of
the Balkans, not all genetic resources
collections are completely included in
EURISCO, for example, in Bulgaria (N.
Velcheva, pers. comm., June 2015) or Mace-
donia (S. Ivanovska, pers. comm., October
2015). Thus, contacting the curators of the
individual genebanks of the Balkan countries,
and those of other genebanks known to have
Balkan material, may have resulted in more
precise figures.
Acknowledgements
I am grateful to the organisers of the
2ndInternational Symposium for Agriculture
and Food in Ohrid, Republic of Macedonia, 7-
9 October 2015, for providing the possibility
to present this topic. I want to thank my
colleagues Stephan Weise and Markus
Oppermann for critical reading of the manu-
script, and for valuable comments.
References
1. CoL (2015) Catalogue of Life. List
matching service.
http://www.catalogueoflife.org/listmatching
/ – accessed October 2015
2. EURISCO (2015) European search
catalogue for plant genetic resources.
http://eurisco.ecpgr.org– accessed
September 2015
3. FAO (2015) FAO Institution Codes.
Downloaded from
http://www.fao.org/wiews-
archive/wiewspage.jsp?i_l=@@&show=D
ownloadinstEN.jsp – accessed October
2015
4. FAO/Bioversity (2012) FAO/Bioversity
Multi-Crop Passport Descriptors.Version 2.
June 2012.
5. http://www.bioversityinternational.org/filea
dmin/user_upload/online_library/publicatio
ns/pdfs/FAO
6. Bioversity_multi_crop_passport_descriptor
s_V_2_Final_rev_1526.pdf – accessed
October 2015
7. Genesys (2015) Genesys – the Global
Gateway to Genetic Resources.
https://www.genesys-pgr.org– accessed
September 2015
8. Gixhari B, Ismaili H, Lashi F, Ibraliu A,
Dias S (2013) Diversity of Albanian plant
genetic resources inventory assessed by
EURISCO passport descriptors. Alban J
Agric Sci 12:741-746
9. GRIN (2015) GRIN [Genetic Resources
Information Network] Taxonomy for
Plants. http://www.ars-grin.gov/cgi-
bin/npgs/html/queries.pl – accessed
October 2015
10. Hammer K, Knüpffer H, Laghetti G,
Perrino P (1992) Seeds from the past. A
catalogue of crop germplasm in South Italy
56 H. Knüpffer
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JAFES, Vol 69, (2016)
and Sicily. Institut für Pflanzengenetik und
Kultur pflanzenforschung, Gatersleben,
Germany; Istituto del Germoplasma, Bari,
Italy. ii+173 pp.
11. Hammer K, Knüpffer H, Laghetti G,
Perrino P (1999) Seeds from the past. A
catalogue of crop germplasm in Central and
North Italy. IPK Gatersleben, Germany;
Germplasm Institute of C.N.R., Bari,
Italy.iv+255 pp.
12. Hintum T van, Knüpffer H (2010) Current
taxonomic composition of European
genebank material documented in
EURISCO. Plant Genet Resour 8:182-188
13. Knüpffer H (2010a) Plant genetic resources
from Greece preserved in the German
Genebank in Gatersleben, with emphasis on
Hans Stubbe’s Balkan collections in 1941-
1942. In: Proc 12th Panehellenic Congr,
Hellenic Sci Soc Plant Breed & Genet, 8-10
Oct2008, Naoussa, Greece, pp16-29 (on
CD-ROM)
14. Knüpffer H (2010b) The Balkan collections
1941-1942 of Hans Stubbe in the
Gatersleben Genebank. Czech J Genet
Plant Breed 46 (Special Issue): S27–S33
15. WIEWS (2015) FAO World Information
and Early Warning System for Plant
Genetic Resources.
http://www.fao.org/wiews-
archive/germplasm_query.htm?i_l=EN –
accessed September 2015
57 H. Knüpffer
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JAFES, Vol 69, (2016)
Tables
Table 1. Genebanks (FAO institution codes, explained below) holding more than 200 germplasm accessions of Balkan origin, and number of accessions per country
of origin. ALB — Albania, BIH — Bosnia and Herzegovina, BGR — Bulgaria, HRV — Croatia, GRC — Greece, XKX — Kosovo (not an official FAO country
code), MKD — Macedonia, MNE — Montenegro, MVA — Moldova, ROU — Romania, SRB — Serbia, SVN — Slovenia, YUG — (former) Yugoslavia
Accs Holding institution Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
13602 Institute for Plant Genetic Resources “K. Malkov”,
Sadovo, Bulgaria
9 — 12408 — 149 — 10 — 9 559 — 24 434
11050 Suceava Genebank, Romania — — 78 — 18 — — — 39 10859 — — 56
8227 Leibniz Institute of Plant Genetics and Crop Plant
Research (IPK), Gatersleben, Germany
1051 — 1723 522 2835 — 10 — 21 1453 2 8 602
5641 N. I. Vavilov Institute of Plant Production, St. Pe-
tersburg, Russian Federation
42 49 1919 68 271 — 25 8 1589 742 — 32 896
5638 International Centre for Agricultural Research in the
Dry Areas (ICARDA), Aleppo, Syria
67 46 952 59 3385 — 338 42 85 463 93 — 108
4823 National Small Grains Germplasm Research Facility,
USDA-ARS, Aberdeen, Idaho, USA
36 292 375 135 919 — 1407 259 9 — 1391 — —
4774 Greek Genebank, Thessaloniki, Greece 2 — 13 — 4701 — — — — — — — 58
3910 Australian Medicago Genetic Resources Centre,
Adelaide, Australia
— — 241 — 3400 — — — — 113 — 2 154
3553 Plant Genetic Resources Center, Tirana, Albania 3443 — 53 — 42 — 5 — — 10 — — —
2823 Plant Gene Resources of Canada, Saskatoon, Canada 32 82 304 79 1462 — 458 — 22 336 — 48 —
2597 Institute for Agrobotany, Tápiószele, Hungary 12 — 534 3 93 — — — 2 1491 1 1 460
2377 Gene Bank, Prague-Ruzyne, Czech Republic 19 1 742 109 232 — 7 1 35 475 43 146 567
2330 Western Regional Plant Introduction Station, USDA-
ARS, Pullman, Washington, USA
87 78 965 42 1017 — 63 29 13 — 36 — —
2328 Maize Research Institute “ZemunPolje”, Belgrade,
Serbia
— 324 61 285 29 — 221 — — 25 — 103 1280
2228 Millennium Seed Bank Project, Royal Botanic Gar-
dens, Kew, Wakehurst Place, UK
— 48 761 37 1111 — 53 11 — 31 12 164 —
2225 Faculty of Agriculture, University of Zagreb, Croatia — 96 — 2124 — — 4 — — 1 — — —
2214 Research Institute for Cereals and Technical Plants
Fundulea, Romania
— — 167 — 25 — — — 33 1911 — — 78
2030 Australian Temperate Field Crops Collection,
Horsham, Victoria, Australia
21 5 605 10 1160 — 6 — 25 44 — 1 153
58 H. Knüpffer
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
Accs Holding institution Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
1976 Australian Trifolium Genetic Resource Centre, South
Perth, Australia
— — 65 — 1835 — — — — 7 — — 69
1832 Dobrudja Agricultural Institute, General Toshevo,
Bulgaria
— — 1829 — — — — — — 3 — — —
1828 Institute of Plant Production “V. Y. Yurjev”,
Kharkiv, Ukraine
6 — 573 80 36 — — — 417 389 19 4 304
1775 Plant Breeding and Acclimatization Institute,
Radzików, Poland
128 — 567 12 251 — 34 — 161 388 3 2 229
1560 Agricultural Institute of Slovenia, Ljubljana, Slove-
nia
— — — — — — — — — — — 1560 —
1545 Faculty of Agriculture, University Ss. Cyril and
Methodius, Skopje, Macedonia
19 — 120 8 11 — 1086 — 1 1 — 6 293
1217 Agricultural Research Station Simnic-Dolj, Romania — — 3 — — — — — 5 1208 — — 1
1141 Plant Production Research CenterPiešťany, Slovakia 1 — 467 32 65 — — — 50 255 6 35 230
1092 Fruit Growing Research Institute Mărăcineni-Argeş,
Romania
— — 56 — 4 — — — 7 982 — — 43
1016 Centro Internacional de Agricultura Tropical (CIAT),
Cali, Colombia
— 10 514 4 41 — 420 — 4 15 — — 8
949 Satellite Collections North of IPK, Oil and Fodder
Crops, Malchow, Germany
27 — 262 169 52 — — — 3 399 — — 37
851 Asian Vegetable Research Development Center,
Taiwan
— — 177 — 19 — — — 3 — — — 652
805 Australian Winter Cereals Collection, Tamworth,
Australia
29 — 121 15 209 — — — — 96 — — 335
780 Agricultural Research Station PoduIloaiei-Iași, Romania
— — 3 — — — — — 5 770 — — 2
739 Agricultural Research Station Suceava, Romania — — 1 — 3 — — — 12 721 — — 2
663 University of Agricultural Sciences and Veterinary
Medicine,Timișoara, Romania
— — — — — — — — — 663 — — —
652 North Central Regional Plant Introduction Station,
USDA-ARS, Ames, Iowa, USA
37 22 114 17 164 — 269 4 17 — 8 — —
633 Ustymivka Experimental Station of Plant Production,
Ukraine
4 — 229 1 56 — 1 — 159 49 10 2 122
617 Agricultural Research Station Turda-Cluj, Romania — — 12 — 1 — — — 7 595 — — 2
59 H. Knüpffer
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JAFES, Vol 69, (2016)
Accs Holding institution Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
608 Department of Applied Genetics, John Innes Centre,
Norwich, U.K.
— — 54 12 100 — — — — 63 — — 379
596 Department of Genetic Resources I, National Insti-
tute of Agrobiological Sciences, Tsukuba, Japan
— — 132 1 45 — — — — 90 — — 328
583 Western Australia Department of Agriculture, South
Perth, Australia
— — 4 — 575 — — — — — — — 4
567 Vine Institute, National Agricultural Research
Foundation, Lykovrissi, Athens, Greece
— — — — 567 — — — — — — — —
527 Medicinal and Aromatic Plants Research Station
Fundulea, Romania
1 — 13 — — — — — 27 482 — — 4
503 Centre for Genetic Resources The Netherlands, Wa-
geningen, Netherlands
4 1 138 7 99 — 25 — 17 59 42 15 96
492 Centro Internacional de Mejoramiento de Maíz y
Trigo (CIMMYT), México, Mexico
4 3 41 — 324 — 6 1 1 35 6 — 71
474 Genetic Resources Unit, Aberystwyth University,
U.K.
— 10 127 8 121 — 1 — — 101 — 10 96
439 Institute of Vegetable and Melon Growing, S. Sel-
ektsiine, Kharkivs’ka obl., Ukraine
1 — 50 — 4 — — — 336 19 — — 29
437 Fruit Growing Research Station Băneasa-Bucureşti,
Romania
— — 2 — 1 — 46 — 8 377 — — 3
435 Fruit Growing Research Station Constanța, Romania — — 12 — 10 — 5 — 22 383 — — 3
429 Plant Genetic Resources Conservation Unit, Southern
Regional Plant Introduction Station, University of
Georgia, USDA-ARS, Griffin, Georgia, USA
11 6 179 13 176 — 37 1 3 — 3 — —
428 Northeast Regional Plant Introduction Station, Plant
Genetic Resources Unit, USDA-ARS, New York
State Agricultural Experiment Station, Cornell
University, Geneva, New York, USA
12 2 66 1 23 — 310 — 8 — 6 — —
384 Grassland Research Institute Braşov. Romania — — — — 1 — — — — 383 — — —
368 Central Research Station for Crops on Sandy Soils
Dăbuleni-Dolj, Romania
— — 2 — — — — — — 366 — — —
367 Nikitskyi Botanical Gardens, Yalta, Crimea, Ukraine 18 — 29 — — — — — 292 19 — — 9
367 Station INRA, Saint Martin de Hinx, France — — 212 — 22 — — — — 133 — — —
332 Institute of Agriculture, Podgorica, Montenegro — 2 1 — — — 1 248 — — 3 77 —
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Accs Holding institution Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
310 Institute of Grape and Wine ‘Maharach’, Yalta,
Crimea, Ukraine
— — 86 — 33 — — — 108 31 — — 52
302 Fruit Growing Research Station Valcea, Romania — — 5 — — — — — — 282 — — 15
298 Fruit Growing Research Station Bistrița, Romania — — 1 — — — — — 3 294 — — —
275 Fruit Growing Research Station Iaşi, Romania — — 5 — — — — — — 268 — — 2
274 Nordic Genetic Resource Center, Alnarp, Sweden 6 — 117 7 113 — — — — 28 — — 3
272 Wine Growing Research Station Odobești-Vrancea,
Romania
8 — 47 — 21 — — — 20 174 — — 2
264 Centro Nacional de RecursosFitogenéticos, Alcalá de
Henares,Madrid, Spain
12 — 37 — 194 — — — 1 9 — — 11
256 Wheat Genetics Resource Center, Manhatta, Kansas,
USA
11 13 13 16 90 79 3 5 — 18 6 — 2
249 AGRITEC, Research, Breeding and Services Ltd.,
Šumperk, Czech Republic
1 — 109 — 37 — — — — 69 — 1 32
241 International Crop Research Institute for the Semi-
Arid Tropics (ICRISAT), Hyderabad, India
2 — 170 — 39 — — — 4 — — — 26
233 Banco de Germoplasma, EscuelaTécnica Superior de
IngenierosAgrónomos, Madrid, Spain
— — — — 223 — — — — — — — 10
232 National Germplasm Repository USDA, ARS, Uni-
versity of California, Davis, California, USA
68 1 11 — 151 — — — 1 — — — —
228 Institute of Genetics Academy of Sciences of Mol-
dova, Chișinău, Moldova
— — 9 — — — — — 184 29 — — 6
225 Soybean Germplasm Collection, USDA-ARS, Ur-
bana, Illinois, USA
— 2 34 4 — — — — 161 — 24 — —
213 Genetics and Plant Breeding Station, ESRA-INRA
SGAP, Mauguio, France
— — 98 — 3 — — — — 74 — — 38
212 Botany Department, University of California, Davis,
California, USA
9 2 21 2 160 — — — 8 — 10 — —
207 National Genebank of Kenya, Crop Plant Genetic
Resources Centre,Muguga, Kenya
— — 10 — 73 — — — — 20 — — 104
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Table 2. Countries holding the largest numbers of germplasm accessions (over 200) from the Balkans, and number of accessions per country of origin. For explana-
tion of country codes, see Table 1.
Accessions Holding country Genebanks Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
23094 Romania 45 9 — 440 — 86 — 52 — 208 22079 — 1 219
15454 Bulgaria 4 9 — 14257 — 149 — 10 — 9 562 — 24 434
10103 USA 27 378 484 1855 295 2753 79 2128 321 228 32 1498 16 36
9449 Australia 8 50 5 1065 25 7201 — 9 — 25 311 — 3 755
9420 Germany 15 1078 — 2039 702 2921 — 11 — 37 1911 4 17 700
5878 Greece 7 2 — 13 — 5805 — — — — — — — 58
5641 RussianFederation 1 42 49 1919 68 271 — 25 8 1589 742 — 32 896
5638 Syria 1 67 46 952 59 3385 — 338 42 85 463 93 — 108
4380 Ukraine 39 29 — 1278 81 164 — 2 — 1501 641 33 17 634
3578 U.K. 7 — 58 1004 74 1384 — 56 11 1 230 32 178 550
3553 Albania 1 3443 — 53 — 42 — 5 — — 10 — — —
3300 Czech Republic 15 23 3 1043 131 307 — 9 1 40 735 44 182 782
2823 CAN –Canada 1 32 82 304 79 1462 — 458 — 22 336 — 48 —
2653 Croatia 8 — 96 — 2547 — — 5 — — 1 4 — —
2597 Hungary 1 12 — 534 3 93 — — — 2 1491 1 1 460
2328 Serbia 1 — 324 61 285 29 — 221 — — 25 — 103 1280
2287 Poland 10 139 — 754 13 326 — 34 — 161 564 6 14 276
1669 Slovenia 2 — — — — — — — — — — — 1669 —
1545 Macedonia 1 19 — 120 8 11 — 1086 — 1 1 — 6 293
1456 Slovakia 9 2 — 573 34 74 — — — 61 354 6 40 312
1018 Colombia 2 — 10 514 4 43 — 420 — 4 15 — — 8
949 Italy 36 190 2 143 36 314 — — 2 30 16 37 3 176
916 Spain 20 58 — 76 11 658 — 2 — 3 22 3 — 83
851 Taiwan 1 — — 177 — 19 — — — 3 — — — 652
691 France 7 — — 347 2 80 — — — — 217 — — 45
602 Japan 2 — — 132 1 51 — — — — 90 — — 328
507 Netherlands 2 4 1 138 7 102 — 25 — 17 60 42 15 96
492 Mexico 1 4 3 41 — 324 — 6 1 1 35 6 — 71
403 Moldova 3 — — 16 — — — — — 311 67 — — 9
354 Montenegro 2 — 2 1 — — — 1 270 — — 3 77 —
332 India 2 2 3 220 — 54 — — — 4 13 — 3 33
274 Sweden 1 6 — 117 7 113 — — — — 28 — — 3
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Accessions Holding country Genebanks Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
235 Austria 7 3 1 20 45 21 — — — 1 38 8 69 29
207 Kenya 1 — — 10 — 73 — — — — 20 — — 104
Table 3. Countries of originin decreasing order of number of Balkan germplasm accessions held in genebanks worldwide. The percentage is given in relation to the
total number of Balkan accessions, i.e. 126,230
Accessions Percentage Country of origin Number of
holding countries holding genebanks genera species
31382 24.9 Romania 45 187 296 675
30659 24.3 Bulgaria 52 211 468 1280
28735 22.8 Greece 45 181 318 941
9743 7.7 former) Yugoslavia 42 165 125 286
5616 4.4 Albania 29 70 148 247
4905 3.9 Macedonia 22 40 80 148
4529 3.6 Croatia 27 71 291 457
4399 3.5 Moldova 32 111 91 147
2524 2.0 Slovenia 23 45 178 276
1822 1.4 Serbia 17 42 47 82
1181 0.9 Bosnia and Herzegovina 18 33 101 146
656 0.5 Montenegro 8 18 38 57
79 0.1 Kosovo 1 1 4 15
Table 4.Total numbers of accessions in genebanks of Balkan countries (according to EURISCO data), and numbers of “own” accessions for each country. The gene-
banks of Macedonia and Serbia also report accessions from former Yugoslavia.
Country Genebanks Total accessions Ownaccessions AccessionsfromYugoslavia
Albania 1 4105 3443
Bulgaria 3 63608 14241
BosniaandHerzegovina 2 434 10
Greece 4 6265 5492
Croatia 8 3264 2547
Moldova 3 1211 311
Macedonia 1 2158 1086 293
Montenegro 2 356 270
Romania 37 42837 21979
Serbia 1 5475 0 1280
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Country Genebanks Total accessions Ownaccessions AccessionsfromYugoslavia
Slovenia 2 1776 1669
Table 5. Accessions from the Balkans grouped by sample status according to the FAO/Bioversity Multi-Crop Passport Descriptors, Version 2 (FAO/Bioversity
2012). In FAO WIEWS, the sample status is coded by two-letter abbreviations, which have been transformed into the three-digit codes, which are hierarchical, i.e.
100 also includes 110, 120 etc.
Accessions Sampstat — Status of sample FAO WIEWS codes included
17431 Unknown or not stated
18044 100 — Wild WS: Wild
3942 110 — Natural
444 120 — Semi-natural/wild
643 130 — Semi-natural/sown [onlyusedforforagecrops]
1078 200 — Weedy WE: Weedy
42453 300 — Traditional cultivar/landrace CU: Cultivated; LR: Traditional cultivar/Landrace; OL: Old cultivar
12641 400 — Breeding/research material
7574 410 — Breeder’sline BL: Breeder's line
225 411 — Syntheticpopulation
792 412 — Hybrid
446 413 — Founder stock/basepopulation
3725 414 — Inbredline (parent of hybrid cultivar)
21 415 — Segregatingpopulation
401 420 — Mutant/genetic stock GS: Genetic stock; MT: Mutant
13510 500 — Advanced/improved cultivar AC: Advanced cultivar
2860 999 — Other (to be elaborated in the REMARKS field)
Table 6. Genera of germplasm from the Balkans with more than 100 accessions, and number of accessions per country of origin. For explanation of country codes,
see Table 1.
Accessions Genus Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
18831 Triticum 945 222 6425 284 2773 58 935 209 358 3018 1057 19 2528
15629 Zea 856 338 2919 609 284 — 408 71 890 7093 2 116 2043
10232 Phaseolus 445 10 2728 193 676 — 483 — 472 3835 8 1049 333
6897 Hordeum 122 115 1317 176 2306 1 916 61 70 1018 240 39 516
5143 Trifolium 24 104 571 155 3461 — 91 24 2 344 24 122 221
4283 Medicago 18 8 472 55 3202 — 7 6 21 292 16 37 149
4134 Vicia 118 8 1335 21 1520 — 21 — 53 733 15 59 251
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Accessions Genus Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
3422 Vitis 291 1 499 163 1011 — 94 27 254 559 26 77 420
3348 Prunus 275 4 216 43 225 — 75 4 183 2149 12 — 162
3092 Aegilops 49 13 610 28 2124 19 84 14 — 47 35 — 69
2672 Avena 105 83 448 90 746 — 163 27 21 447 185 12 345
2427 Pisum 92 — 1100 19 551 — 13 1 34 497 10 — 110
2399 Capsicum 112 1 1028 28 80 — 125 — 66 327 1 4 627
2036 Lycopersicon 165 1 658 32 68 — 202 — 365 345 2 5 193
1851 Linum 3 — 337 3 130 — — 1 3 1341 — 10 23
1834 Secale 54 8 886 6 36 — 346 14 — 407 53 7 17
1472 Lens 21 12 533 41 685 — 24 22 2 39 16 1 76
1435 Nicotiana 146 1 329 8 783 — 5 3 2 71 4 2 81
1372 Glycine 6 2 123 25 — — 1 — 597 329 25 2 262
1341 ×Triticosecale — — 776 1 21 — — — 64 463 — 1 15
1280 Lupinus — — 22 4 1190 — 1 — — 31 — — 32
1249 Allium 69 — 488 39 297 — 72 — 20 219 3 6 36
1208 Cucurbita 33 — 376 29 59 — 177 — 18 429 1 3 83
1175 Beta 8 — 66 9 758 — 27 — 8 267 1 2 29
1093 Malus 106 — 21 47 4 — 13 19 256 550 3 9 65
1026 Festuca 2 3 226 69 98 — 57 — 2 478 — 49 42
993 Dactylis 3 8 289 35 229 — 4 2 3 317 — 62 41
991 Cicer 18 — 451 5 336 — 2 12 110 21 2 — 34
988 Lactuca 13 — 244 47 160 — 6 — 1 251 1 187 78
986 Lolium 11 — 293 57 168 — — — 3 425 — 13 16
948 Lathyrus 55 3 172 5 651 — — 1 13 15 1 10 22
907 Brassica 28 — 142 90 336 — 74 1 15 148 2 20 51
900 Cucumis 102 — 338 19 75 — 16 — 58 209 2 3 78
808 Helianthus 9 — 126 3 4 — — — 6 562 — 2 96
729 Oryza — — 270 — 67 — 124 — — 243 — — 25
702 Pyrus 150 — 53 21 5 — 37 3 120 267 4 — 42
594 Solanum 9 1 92 2 24 — 27 52 23 282 — 19 63
555 Arachis — — 408 1 16 — 15 — — 106 — 2 7
456 Salvia 163 37 19 133 57 — 3 11 4 13 — 10 6
399 Daucus 10 1 58 28 155 — 2 — 19 95 — 2 29
388 Lotus 3 5 46 13 222 — 2 — 1 45 2 15 34
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Accessions Genus Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
378 Gossypium 11 — 156 — 177 — — — — 9 — — 25
360 Papaver 1 1 81 22 3 — 1 — 1 234 — 3 13
324 Citrullus 14 — 154 5 12 — 3 — 52 62 2 — 20
299 Vigna 8 — 36 1 42 — 2 — 1 206 — — 3
286 Sesamum — — 200 — 74 — 10 — — 1 — — 1
284 Dasypyrum 7 2 23 10 237 1 2 1 — — — — 1
277 Juglans 19 — 28 — 3 — — — 9 210 4 — 4
273 Panicum 1 1 60 5 3 — — — 27 115 — 2 59
261 Satureja 115 1 31 27 3 — 2 — 1 73 — 7 1
246 Sorghum 18 — 149 8 15 — — — 4 45 — 3 4
241 Origanum 139 — 4 46 21 — — — — 27 — 3 1
238 Ornithopus — — 7 — 231 — — — — — — — —
228 Bromus 1 — 61 8 66 — 13 — 5 58 4 6 6
216 Phleum 3 — 53 8 30 — 1 — 1 66 — 35 19
207 Petroselinum 7 — 48 11 18 — 43 — 8 67 3 — 2
205 Cannabis 1 — 10 1 — — — — 1 155 — 4 33
199 Poa 2 — 88 27 12 — — — — 58 — 8 4
197 Olea 92 — — 37 45 — — 15 — — — — 8
193 Silene — 8 66 11 64 — 18 3 — 13 — 10 —
182 Fagopyrum 2 2 3 10 — — — 7 2 19 2 118 17
181 Mentha 6 1 32 37 2 — — — 12 87 — — 4
179 Astragalus — — 47 2 84 — — — 7 35 — 3 1
172 Trigonella 2 — 18 1 145 — — — — 6 — — —
166 Anethum 4 1 45 17 14 — 1 — 21 62 — 1 —
164 Hypericum 13 3 25 109 2 — — — — 8 — 4 —
147 Onobrychis — — 42 — 48 — 1 — 3 33 2 7 11
137 Cydonia 27 — 20 — — — — — 19 62 3 — 6
136 Raphanus 4 — 40 1 28 — 4 — 6 48 — 1 4
127 Hymenocarpos — — 2 — 123 — — — — — — — 2
116 Ficus 72 — 14 16 13 — — — — — — — 1
112 Melilotus 1 — 31 3 43 — — — 7 14 3 8 2
109 Datura 1 — 8 3 3 — — — — 91 — — 3
108 Brachypodium 2 — 20 3 78 — — — — 3 — 2 —
108 Tanacetum — — 7 80 1 — — — 3 16 — 1 —
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Accessions Genus Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
107 Thymus 51 — 12 24 4 — — — — 16 — — —
102 Agrostis — — 34 1 2 — — — 1 56 — 5 3
Table 7. Species of germplasm from the Balkans with more than 200 accessions, and number of accessions per country of origin.For explanation of country codes,
see Table 1.
Accessions Species Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
15612 Zea maysL. 856 338 2917 594 284 — 408 71 890 7093 2 116 2043
13772 Triticum aestivumL. 422 181 4738 247 1136 4 695 121 305 2620 977 18 2308
8771 Phaseolus vulgarisL. 434 10 2552 173 647 — 465 — 464 3644 8 43 331
6357 Hordeum vulgareL. 120 115 1260 175 1884 — 914 61 70 995 239 38 486
3023 Vitis viniferaL. 291 1 377 163 1008 — 94 27 154 425 25 77 381
2397 Pisum sativumL. 91 — 1089 19 538 — 13 1 34 497 10 — 105
2384 Capsicum annuumL. 112 1 1021 28 80 — 125 — 66 320 1 4 626
2380 Triticum durumDesf. 294 — 1297 4 518 — 68 — 48 122 — — 29
2058 Avena sativaL. 48 83 431 81 306 — 159 23 21 413 174 12 307
1809 Secale cerealeL. 52 8 877 6 27 — 346 14 — 403 53 6 17
1771 Lycopersicon esculentumMill. 164 1 547 32 65 — 202 — 299 306 2 5 148
1706 Linum usitatissimumL. 3 — 327 3 117 — — — 2 1226 — 5 23
1534 Triticum turgidumL. 28 36 183 27 815 28 169 84 5 45 58 — 56
1531 Vicia sativaL. 50 1 703 5 607 — 6 — 22 29 7 — 101
1529 Vicia fabaL. 23 — 204 10 456 — 14 — 17 646 — 48 111
1419 Nicotiana tabacumL. 145 1 324 8 780 — 5 3 2 68 4 — 79
1417 Phaseolus coccineusL. 10 — 156 20 25 — 17 — 8 182 — 997 2
1385 Lens culinarisMedik. 21 1 532 3 684 — 24 6 2 39 16 — 57
1341 ×Triticosecale sp. — — 776 1 21 — — — 64 463 — 1 15
1326 Glycinemax(L.) Merr. 6 2 123 25 — — 1 — 597 313 25 2 232
983 Cicer arietinumL. 18 — 444 5 335 — 2 12 110 21 2 — 34
974 Dactylis glomerataL. 3 8 270 35 229 — 4 2 3 317 — 62 41
913 Beta vulgarisL. 6 — 39 9 527 — 27 — 8 267 1 2 27
873 Cucurbita pepoL. 25 — 241 22 26 — 125 — 14 360 — 3 57
836 Trifolium subterraneumL. — — 12 — 785 — — — — — — — 39
830 Lactuca sativaL. 12 — 199 39 72 — 6 — 1 242 1 181 77
821 Lolium perenneL. 5 — 252 47 115 — — — 3 384 — 9 6
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Accessions Species Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
785 Prunus sp. — 2 76 — 6 — — — 23 623 — — 55
769 Helianthus annuusL. 9 — 106 3 4 — — — 4 553 — 2 88
748 Malus domesticaBorkh. 1 — 14 47 3 — 13 19 215 367 3 9 57
747 Medicago sativaL. 14 6 218 51 94 — 5 4 21 218 15 26 75
737 Trifolium pratenseL. 10 39 95 105 104 — 53 21 1 219 5 57 28
729 Oryza sativaL. — — 270 — 67 — 124 — — 243 — — 25
724 Lupinus angustifoliusL. — — 2 — 719 — — — — 1 — — 2
722 Prunus armeniacaL. 17 — 37 — 34 — 55 1 72 486 6 — 14
700 Aegilops triuncialisL. 4 — 168 6 474 1 30 1 — 5 7 — 4
656 Triticum monococcumL. 177 5 71 4 127 24 3 4 — 149 19 1 72
550 Medicago polymorphaL. — — 28 — 498 — — — — 3 — — 21
549 Arachis hypogaeaL. — — 407 — 13 — 15 — — 106 — 1 7
546 Allium cepaL. 39 — 232 17 48 — 56 — 8 139 1 1 5
545 Brassica oleraceaL. 23 — 100 65 155 — 74 1 14 62 2 18 31
518 Prunus avium(L.) L. 67 — 40 4 57 — 2 — 9 324 — — 15
499 Prunus persica(L.) Stokes 20 — 23 2 35 — — — 42 367 — — 10
479 Medicago orbicularis (L.) Bartal. — — 23 — 438 — 1 — — 6 — — 11
455 Cucumis sativusL. 37 — 118 10 16 — 5 — 41 178 2 — 48
450 Festuca pratensisHuds. — — 125 17 2 — 52 — 1 217 — 18 18
431 Medicago truncatulaGaertn. — — 2 — 426 — — — — 1 — — 2
404 Trifolium repensL. 1 15 105 17 186 — 7 — — 38 1 22 12
400 Aegilops biuncialisVis. 1 6 98 — 261 1 18 — — 1 12 — 2
371 Gossypium hirsutumL. 11 — 150 — 176 — — — — 9 — — 25
370 Solanum tuberosumL. — — 54 — — — — 52 9 207 — 19 29
369 Aegilops geniculataRoth 34 1 83 11 206 2 7 4 — 11 1 — 9
358 Cucumis meloL. 65 — 154 9 58 — 11 — 11 28 — 3 19
358 Pyrus communisL. 123 — 28 21 — — 19 1 110 21 1 — 34
352 Lupinus albusL. — — 14 2 302 — 1 — — 16 — — 17
348 Aegilops neglectaReq. ex Bertol. 7 6 85 11 200 1 21 8 — — 1 — 8
329 Papaver somniferumL. — — 72 18 1 — — — 1 225 — — 12
322 Daucus carotaL. 8 1 57 27 83 — 2 — 19 94 — 2 29
316 Citrullus lanatus(Thunb.) Matsumuraet Nakai 14 — 149 5 10 — 3 — 51 62 2 — 20
315 Lathyrus sativusL. 48 — 101 4 143 — — 1 9 5 — — 4
315 Vitis sp. — — 103 — 3 — — — 39 132 — — 38
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Accessions Species Country of origin
ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG
311 Triticum sp. 23 — 73 2 115 — — — — 57 — — 41
306 Aegilops comosaSm. — — 5 — 301 — — — — — — — —
302 Salvia officinalisL. 162 37 1 73 2 — 3 11 — 11 — — 2
300 Prunus domesticaL. 90 1 16 21 40 — 12 3 35 34 2 — 46
291 Festuca arundinaceaSchreb. — — 29 10 70 — 2 — 1 157 — 5 17
289 Pyrus sp. 3 — 21 — 2 — — 1 8 246 2 — 6
288 Aegilops lorentiiHochst. 1 — 9 — 277 — — — — — — — 1
285 Vigna unguiculata(L.) Walp. 7 — 32 1 37 — — — 1 205 — — 2
284 Dasypyrumvillosum(L.) Borbás 7 2 23 10 237 1 2 1 — — — — 1
275 Vicia ervilia(L.) Willd. 37 — 49 — 186 — 1 — — 1 — — 1
271 Sesamum indicumL. — — 200 — 60 — 10 — — — — — 1
270 Panicum miliaceumL. 1 1 60 4 2 — — — 27 115 — 1 59
253 Lathyrus ciceraL. — — 2 — 248 — — — 3 — — — —
251 Allium sativumL. 8 — 127 5 17 — 1 — 10 61 1 1 20
235 Medicago rigidula(L.) All. — — 31 — 186 — — 1 — 4 — — 13
234 Cucurbita maximaDuchesne 4 — 53 6 27 — 51 — 4 63 1 — 25
230 Medicago minima(L.) L. 1 1 50 3 156 — — — — 17 — — 2
229 Lycopersicon sp. 1 — 75 — 3 — — — 66 39 — — 45
218 Origanum vulgareL. 139 — 3 46 1 — — — — 25 — 3 1
214 OrnithopuscompressusL. — — 5 — 209 — — — — — — — —
213 Solanum melongenaL. 9 — 37 — 24 — 27 — 14 72 — — 30
206 Petroselinum crispum(Mill.) Fuss 7 — 47 11 18 — 43 — 8 67 3 — 2
205 Prunus cerasusL. 2 — 12 13 7 — 5 — 2 142 4 — 18
204 Cannabis sativaL. 1 — 10 — — — — — 1 155 — 4 33
202 Medicago arabica(L.) Huds. — — 20 — 172 — — — — 1 — — 9
202 Sorghum bicolor(L.) Moench 18 — 114 8 13 — — — 1 41 — 3 4
Journal of Agricultural, Food and Environmental Sciences
UDC 633.11-184(497.2)
Original scientific paper
____________________________________________________________________________________________________
INVESTIGATION ON SOME MORPHOLOGICAL AND BIOLOGICAL
CHARACTERISTICS OF EINKORN WHEAT (T. MONOCOCCUM L.) DEPENDING
ON NITROGEN FERTILIZATION
H. Kirchev*, N. Semkova
Faculty of Agronomy, Agricultural University, Plovdiv, Bulgaria
*corresponding author: hristofor_kirchev@abv.bg
Abstract
The aim of this study is to investigate some quantitative and qualitative indicators of einkorn wheat
(T. monococcum L.). A three-year field experiment has been carried out at the experimental field of
Department of Crop Science in Agricultural University - Plovdiv. To compare the performance,
Sadovo1 common wheat (T. aestivum L.) is used as a standard. Both wheat species have been grown
on two nitrogen fertilization levels – 80 and 160 kg.ha-1 nitrogen. Phenological development of the
plants was recorded at the onset of the main phenophase. Inter-phase period has been calculated
(number of days). Grain yield (t ha-1) is accounted indirectly by ¼ m2 plot. The main structural
elements of plants have been established. It has been found that phenological development stage of
tillering occurs at the same time for both wheat species. Following the start of spring vegetation,
common wheat enters a phase earlier than the einkorn. Common wheat is a high-yielding einkorn, that
puts both proven wheat varieties in different groups. Einkorn has high tiller appearance but it has a
low productive tillering than common wheat. Einkorn form lower grain in the spike and lighter grain
per spike. Nitrogen fertilization significantly increased harvested grain in common wheat. In einkorn
it has no significant impact on yield.
Key words: einkorn, wheat, yield, nitrogen fertilization.
Introduction
The first cultivated wheat, einkorn (Triticum
monococcum L.) was domesticated during the
Pre-Pottery Neolithic period. It then spread to
the Balkans, and finally to Western and
Northern Europe (Desheva et al., 2014);
(Laghetti et al., 2009); (Mielke & Rodemann,
2007).
Growing of the einkorn has no significance in
modern agriculture due to its late ripeness and
low yields. At present, there is interest for
einkorn because of the nutritional qualities, its
adaptation to low-input agriculture and
resistance to diseases that it gives an
opportunity for organic farming (Konvalina et
al., 2009); (Konvalina et al., 2010); (Ruiz et
al., 2008). Compared to the common wheat,
often only 20% of the soft wheat yield are
achieved when cropping einkorn (without
husks). The einkorn flour distinguishes itself
by very high contents of proteins and glue.
The yellow pigmentation gives the bread and
cakes a pleasant looking color. Einkorn bread
and cakes have a taste of nut (Guzmán et al.,
2009; Hidalgo et al., 2009; Hidalgo et al.,
2014; Zaharieva & Monneveux, 2014).
Einkorn contains the highest levels of lutein
among wheat species. It is a specialty wheat
with high levels of carotenoids and other
phytonutrients, with emphasis on its potential
as a high-carotenoid wheat ingredient for use
in developing high-lutein whole grain baked
food products (Abdel-Aal & Hucl, 2014).
Material and methods
The aim of this study is to establish some
morphological and biological characteristics of
einkorn, compared with common wheat,
depending on the level of nitrogen
fertilization. For this purpose, a three-year
field experiment has been carried out at the
experimental field of Department of Crop
Science in Agricultural University – Plovdiv.
To compare the performance, Sadovo1
common wheat (T. aestivum L.) is used as a
standard. Both wheat species have been grown
on two nitrogen fertilization levels – 80 and
160 kg.ha-1 nitrogen. Phenological
70 H. Kirchev, N. Semkova
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
development of the plants was recorded at the
onset of the main phenophase. Inter-phase
period has been calculated (number of days).
Grain yield (t ha-1) is accounted indirectly by
¼ m2 plot. In einkorn, yield is assimilated to a
naked grain by correlating grain glumes by
medium samples of 20 g of harvested spikes.
The main structural elements of plants have
been established: Plant heigh, cm ;
Number of tillers per plant; Number of spikes
per plant; Productive tillers, %; Spike
length, cm; Numbers of spikelets per spike;
Numbers of grains per spike; Mass of grains
per spike, g and Mass of glumes per spike, g.
To establish a statistically significant influence
of the examined factors and differences
between the tested variants was used analysis
of variance.
Results and discussion
Phenological development of wheat species in
this study during the three years of the study
indicated as dates for the main phenological
phases (Table 1). The different dates of sowing
during the three years of the study are due to
rainfall conditions and the ability to perform
quality tillage and timely sowing. The sowing
during of three years has been done later than
the optimal period for the region (20 October).
This is the reason crops to spring up at
different times in each of the years, but both
types of wheat germinate at the same time
each year. Obviously germination depends on
the meteorological conditions, but not on the
genotype.
Late germination is the reason of entering the
crops the tillering phase in December. Even
though this phase of the development of winter
cereal crops is influenced mainly by
temperature conditions, einkorn enters the
tillering stage between 4 and 6 days later than
common wheat. The earliest tillering occurs
during the first harvest year - between
December 10 to 15, and later - during the third
year of the study - between 26 to 30
December.
Table 1. Phenological development.
Species Sowing Germination Tillering Stem
elongation
Spike
emergence
Maturity
2010
Wheat 28.10.2009 12.11.2009
10.12.2009 09.04.2010 28.04.2010 28.06.2010
Einkorn 15.12.2009 30.04.2010 15.05.2010 06.07.2010
2011
Wheat 04.11.2010 15.11.2010
14.12.2010 11.04.2011 02.05.2011 30.06.2011
Einkorn 20.12.2010 02.05.2011 17.05.2011 07.07.2011
2012
Wheat 01.11.2011 15.11.2011
26.12.2011 16.04.2012 05.05.2012 27.06.2012
Einkorn 30.12.2011 05.05.2012 20.05.2012 05.07.2012
The beginning of the durable spring vegetation
and the entering of the plants the phase of stem
elongation occurs at different times in each of
the species. In common wheat difference
between the year with the early and later
occurrence of the phase of stem elongation is 7
days (between 9 and 16 April), while einkorn
– five days (April 30 and May 5). Similar to
phase of stem elongation, the spike emergence
in the common wheat occurs earlier (between
April 28 and May 5) compared to einkorn,
wherein the spike emergence was recorded
between 15 to 20 May. The maturity occurs at
different times for both types of wheat. The
phase of full maturity in common wheat was
registered one week earlier compared to
einkorn.
In both species during the three years of study
differences in the dates of entering the main
phases of development of the crop are not
registered, depending on the level of nitrogen
fertilization, which gives grounds to consider
that nitrogen fertilization does not affect
phenological development of the wheat.
71 H. Kirchev, N. Semkova
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JAFES, Vol 69, (2016)
29
34
30
36
42
46
121
137
119
134
112
127
20
16
22
16
20
16
62
53
60
52
54
47
232
240
231
238
228
236
0 50 100 150 200 250 300 350 400 450 500
T. aestivum
T. monococcum
2010
T. aestivum
T. monococcum
2011
T. aestivum
T. monococcum
2012
sprung-tillering tillering-stem elongation
stem elongation-spike emergence spike emergence-maturity
total vegetation period
Number of days
Figure 1. Inter-phase periods, number of days.
Different dates of entering the main
phenophases of development are the reason of
different lengths of inter-phase periods in both
types of wheat (Fig. 1). Inter-phase period
germination – tillering in einkorn lasts
between 34-46 days and in common wheat is
shorter – between 29-42 days depending on
the year. During the three years of study the
period between tillering and stem elongation is
longer by 15 days average at einkorn to
common wheat. The period between phase of
stem elongation and spike emergence is
shorter in einkorn – 16 days during the three
harvest years, while in common wheat –
between 20-22 days. Even though maturity
occurs first in common wheat, interphase
period spike emergence – maturity is shorter in
einkorn – 47 days in year 2012 and 53 days in
the first year of study. Differences in the
duration of inter-phase periods in wheat
species are the reason of the different lengths
of vegetation from germination to maturity.
The vegetation period of common wheat is
between 228-232 days, while for the einkorn is
longer an average of 8 days – between 236-
240 days.
Table 2. Grain yield, t ha-1.
Species N rate,
kg ha-1
Years Average
2010 2011 2012
Triticum aestivum
L.
80 4.532** 4.128** 3.265** 3.975**
160 6.657*** 6.053*** 4.867*** 5.859***
Triticum
monococcum L.
80 1.532* 1.831* 1.062* 1.475*
160 1.862* 2.106* 1.302* 1.757*
LSD 5% 0.332 0.277 0.246 0.285
*Values with the different symbols are statistically proven.
Grain yield of the tested species of wheat
varies during three years of study, as in the
three harvest years common wheat variety
Sadovo1 significantly exceed the yields
obtained from einkorn (Table 2). Due to the
very large differences in yields between the
72 H. Kirchev, N. Semkova
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JAFES, Vol 69, (2016)
two species, the differences in the three years
are statistically proven. In common wheat
highest yields were obtained in the first
harvesting year – an average of 5.595 t ha-1 for
both fertilization rates, while einkorn yields
are highest in the second year of study – 1.969
t ha-1. The lowest yields in both species were
obtained during the third harvest year.
Nitrogen fertilization increases the yield in
both species, but during the three years of
study and average for the period at einkorn the
difference between the two levels of
fertilization are smaller than the least
significant difference (LSD). In common
wheat during the three studied years and
average for the three years higher fertilizer rate
of 160 kg ha-1 nitrogen proved increases grain
yield by an average of 1.884 t ha-1.
Table 3. Structural elements of the crop.
Species N rate,
kg ha-1
Plant
heigh, cm
Number of
tillers per plant
Number of
spikes per plant
Productive
tillers, %
T. aestivum L. 80 70.5* 2.8* 2.5* 89.3***
160 88.6** 3.2* 2.6* 81.2**
T.
monococcum
L.
80 103.4*** 3.8* 2.3* 60.5*
160 106.2*** 4.2* 2.5* 59.5*
LSD 5% 14.2 1.3 0.5 3.3
*Values with the different symbols are statistically proven.
The structural elements of the crop for the two
species of wheat enable them to be compared,
both in height and density (Table 3). Plant
height in both species is drastically different.
In einkorn the average height of the crop is
104.8 cm – proved higher by 25.2 cm the
formation of sowing Sadovo1 – 79.6 cm.
Similar to the results for yield, nitrogen
fertilization has no proven change in the height
of the plants in einkorn, while wheat variety
Sadovo1the higher fertilizer rate leads to
proven raising of the height of the crop to 18.1
cm. Overall species Triticum monococcum
formed higher stem than common wheat.
Crop density, determined by the number of
tillers per plant allows einkorn to be defined as
more strongly tillering species compared to
common wheat. For both species nitrogen
fertilization has no proven change in the
number of tillers per plant. Number of spikes
per plant is a factor determining how many of
formed tillers are productive. Even though
einkorn differs as dramatically strong tiller
species, spikes formed on one plant are almost
as many as on the common wheat. This puts
both species close to each other by this
indicator, since the difference does not exceed
the necessary least significant difference
(LSD), which indicates that it is not
statistically significant. This is the main reason
for the big difference, for productive tillering,
which is in favor of common wheat. Einkorn
has a low productive tillering for only about
60% of the generated tillers become
productive, while Sadovo1 variety, despite the
relatively small number of tillers per plant,
over 80% of them form spikes. Nitrogen
fertilization has no proven effect on productive
tillers on einkorn, while on common wheat it
increases productive tillers by 8.1%.
In addition to the structure of the crop, the
structural elements of the spike are essential
for the productive potential of wheat (Table
4). The length of the spike is higher in
common wheat in comparison with einkorn by
about 2 cm, so the difference of the spike in
common wheat in comparison with einkorn
may be considered to be statistically proven.
Nitrogen fertilization did not significantly
affect this feature in einkorn, while common
wheat higher nitrogen rates lead to the
formation of a longer spike. Although
common wheat formed a longer spike, the
number of spikelets per spike are on average 2
more in einkorn. In both wheat species
nitrogen fertilization had no proven effect. In
common wheat the number of grains per spike
varies proven under the influence of nitrogen
fertilization from 37.4 in fertilization with N80
to 39.6 in higher fertilization rates N160. As
einkorn forms only one grain in spikelet, the
number of grains per spike is equal to the
number of spikelets. The mass of grain per
spike in common wheat has been proven
heavier about 1 g than in einkorn. In einkorn
nitrogen fertilization had no proven effect on
73 H. Kirchev, N. Semkova
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JAFES, Vol 69, (2016)
this feature, while on common wheat
difference in the weight of the grain between
the two fertilization rates has been proven
statistically.
Table 4. Structural elements of the spike.
Species N rate,
kg ha-1
Spike
length, cm
Numbers of
spikelets per
spike
Numbers of
grains per
spike
Mass of grains
per spike, g
Mass of
glumes per
spike, g
T. aestivum L. 80 9.4** 20.7* 37.4** 1.45** 0.04*
160 10.5** 21.3* 39.6*** 1.87*** 0.05*
T. monococcum
L.
80 7.3* 23.3** 23.3* 0.79* 0.40**
160 7.6* 23.5** 23.5* 0.86* 0.42**
LSD 5% 1.2 1.8 2.0 0,19 0.08
*Values with the different symbols are statistically proven.
Typical of einkorn hulled wheat, with tough
glumes that tightly enclose the grains, causing
to form heavier glumes (0.41 g). In common
wheat weight of glumes is low, compared with
einkorn. Nitrogen fertilization did not
significantly affect this feature in both species
of wheat.
Conclusions
In einkorn, vegetation period is longer by an
average of 8 days, compared to the common
wheat. The reason for this is the late entry in
the main phenophases of development in
einkorn and different lengths of inter-phase
periods in both wheat species. Nitrogen
fertilization does not affect phenological
development of both types of wheat.
In common wheat grain yields are significantly
higher than einkorn. The main reasons for this
are that einkorn has higher tiller appearance
but it has a lower productive tillering than
common wheat. Einkorn forms lower grain in
the spike and lighter grain per spike.
Nitrogen fertilization significantly increased
harvested grain in common wheat. In einkorn
it has no significant impact on yield.
References
1. Abdel-Aal, E. M., Hucl, P. (2014).
Einkorn: a functional wheat for developing
high-lutein whole grain baked products. Cereal
Foods World, 59(1), 5-10.
2. Desheva, G., Valchinova, E., Kyosev,
B., Stoyanova, S. (2014). Grain physical
characteristics and bread-making quality of
alternative cereals towards common and
durum wheat. Emirates Journal Of Food And
Agriculture, 26(5), 418-424.
3. Guzmán, C., Caballero, L., Alvarez, J.
B. (2009). Variation in Spanish cultivated
einkorn wheat (Triticum monococcum L. ssp.
monococcum) as determined by morphological
traits and waxy proteins. Genetic Resources
And Crop Evolution, 56(5), 601-604.
4. Hidalgo, A., Brandolini, A., Ratti, S.
(2009). Influence of genetic and environmental
factors on selected nutritional traits of Triticum
monococcum. Journal Of Agricultural And
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5. Hidalgo, A., Brandolini, A. (2014).
Nutritional properties of einkorn wheat
(Triticum monococcum L.). Journal Of The
Science Of Food And Agriculture, 94(4), 601-
612.
6. Konvalina, P., Šrámek, J., Stehno, Z.,
Moudrý, J. J. (2009). Efficiency of alternative
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Z., Moudrý, J. (2010). Morphological and
biological characteristics of the land races of
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K., Pignone, D. (2009). On the trail of the last
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Deutschen Pflanzenschutzdienstes, 59(7), 162-
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677-706.
Journal of Agricultural, Food and Environmental Sciences
UDC 633.11-152.75(497.2)
Original scientific paper
____________________________________________________________________________________________________
POLYMORPHISM OF ENDOSPERM PROTEINS IN AMPHIDIPLOIDS
WITH THE G GENOME OF Triticum timopheevii (Zhuk.)
Doneva S.1*, Yordanova D.1, Daskalova N.2, Spetsov P.3
1Dobroudja Agricultural Institute – General Toshevo, Bulgaria
2Technical University, Department of Plant Growing - Varna, Bulgaria 3 Konstantin Preslavsky University of Shumen, College–Dobrich, Bulgaria
*e-mail: sonya_doneva@yahoo.com
Abstract
During evolution in Triticum the diversity of genes in T. aestivum L. was greatly reduced compared to
its ancestors. This tendency restricted further improvement of productivity and quality in common
wheat and narrowed the plant resistance to biotic and abiotic stresses. Wide hybridization resulted in
synthetic genotypes that offered opportunities for introduction of new genes for useful traits in
breeding. The objects of this study were two amphidiploids with G-genome inherited from tetraploid
wheat relative T. timopheevii (2n=28, GGAuAu). Glutenin and gliadin allelic composition of the
synthetic wheats H-68/44 and H-69/36 were analysed by SDS-PAGE and A-PAGE electrophoretic
methods. New allelic variants in Glu-G1 loci, which are not characteristics for the spectrum of T.
aestivum, were identified. In contrast to the high polymorphism of amphidiploids for high-molecular
weight proteins, variation in the low-molecular glutenins was much less. More gliadin alleles in
synthetic lines were found than in hexaploid wheat, due to the parent polymorphism. The results of
this survey showed that synthetics with T. timopheevii genome might serve as an important sources of
increased genetic variation for endosperm proteins in common wheat.
Keywords: synthetic wheats, T. timopheevii, glutenins, SDS-PAGE, gliadins, A-PAGE.
Introduction
Many cultivated and wild species from
Aegilops – Triticum group possessed various
and useful genes for wheat improvement
(Monneveux et al., 2000; Zaharieva et al.,
2003; Mujeeb-Kazi, 2005; Spetsov et al.
2006). Various synthetic and translocated
genotypes were developed from Triticum x
Aegilops crosses and used as bridges to
transfer different breeding traits to common
wheat (Jauhar and Peterson, 2006; Plamenov
and Spetsov, 2011).
Wheat grain quality depends on gluten, which
is the complex endosperm protein. It consists
of two prolamin groups–glutenins and
gliadins. Glutenins include high molecular and
low molecular proteins, shortly named as
HMW-GS and LMW-GS, respectively. HMW-
GS are coded by two genes (х- and у-), which
are localized in three loci (Glu-A1, Glu-B1,
Glu-D1) on the long arms of the
homoeologous group 1. LMW-GS are
classified in three groups (В, С и D) due to
their molecular weight and isoelectrical points
(Jackson et al., 1983). Genes, responsible for
them, are localized in the short arms of the
homoeologous group 1 (Glu-A3, Glu-B3 and
Glu-D3 loci). Gliadins are monomeric proteins
and electrophoretically separated in α-, β-, γ-,
ω- gliadins. Two of them (α- and β-) are coded
by Gli-2 loci in the short arms of
chromosomes 6А, 6В и 6D, and others (γ- and
ω-) by Gli-1 loci in the short arms of
chromosomes 1А, 1В and 1D (Masci et al.,
2002). There is a strong connection between
Glu-3 loci, responsible for LMW-GS and Gli-
1 loci, conducting the output of gliadins (Singh
and Shepherd, 1988).
Some investigations showed that the variation
of Glu-1, Glu-3 и Gli-1 loci in bread wheat
was limited (Gianibelli et al., 2001; Li et al.,
2007). Related species to wheat as Ae. tauschii
(Yan et al., 2003), T. turgidum (Li et al., 2006)
and T. monococcum (Ciaffi et al., 1998)
expressed a large diversity of glutenin and
76 Doneva S., Yordanova D., Daskalova N., Spetsov P
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JAFES, Vol 69, (2016)
gliadin alleles. New HMW-GS have been
detected in the A genome of diploid T. urartu
and some tetraploid species, which are
potential sources for genes in wheat
improvement.
T. timopheevi (GGAuAu) is a hulled tetraploid
wheat relative (Goncharov et al., 2009) and
still in seed production to some extent in the
Caucasus (Wan et al., 2002). Its genomes are
considered as homoeologous to wheat А- and
В- genomes (Brown-Guedira et al., 1997).
High protein content (19-22%), diversity in
HMW-GS and resistance to biotic stresses are
remarkable breeding traits for this tetraploid
species (Obukhova et al. 2009). Genes from
the G genome, responsible for endosperm
proteins, are probably similar to those,
governing the protein synthesis in hexaploid
wheat. Through SDS-PAGE и PCR methods
Li et al. (2002) found 8 allelic variants in Glu-
G1, suggesting T. timopheevi as a valuable
source for new glutenin genes in bread wheat
(Li et al., 2007). Two genes, belonging to А-
and G-genome, coding for х- and у- subunits,
were isolated (Wan et al., 2002). It is proved
that wheat lines with both types (х- and у-
subunits) in Glu-A1 are better in quality than
plants having only x-type subunit (Johansson
et al., 1993).
Despite that numerous researches has been
focused on seed proteins, T. timopheevi is
deeply involved in wheat improvement as a
resource of genes not only for grain quality,
but also for fungi resistance – leaf rust, stem
rust, powdery mildew and fusarium (McIntosh
et al., 2008; Lеonova et al., 2011).
Characterization of storage proteins (glutenins
and gliadins) in two amphidiploids possessing
the G-genome from Triticum timopheevii, is
the main purpose of this study. The two
synthetics differ with the second parent used in
the cross. Analysis of synthetic lines may
increase their role as important source of novel
protein genes for wheat breeding.
Materials and methods
Synthetic hexaploid wheat Н-68/44 was
obtained from the cross between Т.
timopheevii (GGAuAu) and Aegilops tauschii
(DD), and the second one, Н-69/36 - between
T. turanicum (BBAuAu) and T. timopheevii
(GGAuAu) (Table 1). Two bread wheat
varieties, Bezostaya 1 and Chinese Spring,
were used as standards in biochemiсаl
analyses.
Table 1. Breeding number and genome formulae of synthetic wheats
Breeding No C r o s s Genome formula1 (2n)
Н-69/36 T. turanicum x T. timopheevii BBАuАuGGАuАu
Н-68/44 T. timopheevii x Ae. tauschii GGАuАuDD 1, Genome formulae are according Goncharov et al. (2009).
Glutenins (HMW- and LMW-GS) were
extracted according to Singh et al. (1991).
Gliadins were first extracted in 70% ethanol
and protein fractions were separated by A-
PAGE using 8% polyacrylamide gel under
constant 10°С (Кhan et al., 1983). The
electrophoresis run on vertical apparatus in
two ways: а) classical one-dimensional 12%
polyacrylamide gel (Laemmli, 1970); б) one-
dimensional 10% polyacrylamide gel SDS –
PAGE with addition of 4М urea (Lafiandra et
al., 1993).
Arrangement and numbering of HMW-GS in
wheat was carried out according Payne and
Lawrence (1983). LMW-GS nomenclature in
wheat (Gupta and Shepherd, 1990) and
combined method for LMW-GS and gliadin
identification were adopted (Jackson et al.,
1996). Аlleles in Glu-D1 locus were described
according to William et al. (1993), while
subunits in Glu-G1 and Glu-А1 loci were
marked and compared to those expressed in
genomes of common wheat (Hu et al., 2012).
Results and discussion
Amphidiploid (AD) Н-68/44 expressed the
following HMW-GS subunits: 1Ах null in
Glu-A1, 1Gx and 1Gу in Glu-G1, and the
subunit pair 1Dx2 + 1Dy12.4 in Glu-D1 locus
(Fig. 1-2). Glutenins displayed in Glu-A1 and
Glu-G1 loci were inherited from the tetraploid
T. timopheevii, and those found in Glu-D1 –
from the diploid Ae. tauschii. These findings
were supported by studies of Wan et al.
(2002), Li et al. (2007) and Obukhova et al.
77 Doneva S., Yordanova D., Daskalova N., Spetsov P
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JAFES, Vol 69, (2016)
(2009) showing two HMW glutenin subunits
in the G-genome, х- and у- subunit. They have
lower electrophoretic mobility, but higher
molecular weight than 1Вх7 in Glu-В1 of
wheat varieties Bezostaya 1 and Chinese
spring. The classical Laemmli system (12%
SDS-PAGE) could not differentiate the
subunits, expressed in T. timopheevii, because
of their overlap. With the help of 10% SDS-
PAGE with 4М urea, they were divided and
identified (Тоdorov, 2006).
Synthetic H-69/36 exerted the following
HMW-GS: 1Ах 2* and 1Ау in Glu-A1, 1Вх7
in Glu-В1, and 1Gx in Glu-G1 (Fig. 3-4).
Аllele b, coding 1Ах 2* in Glu-A1, was
inherited from Т. turaniсum. Results of 12%
SDS-PAGE and 10% SDS-PAGE with 4М
urea showed the presence of only subunit x in
Glu-G1. The second fraction, differing in
molecular weight and electrophoretical
mobility among those of 1Ву9 and 1Dy10 in
Glu-1 of wheat checks Bezostaya 1 and
Chinese Spring, was identified as subunit 1Ay,
transferred to H-69/36 from the locus Glu-A1
of T. timopheevii. Our data are in conformity
with Hu et al. (2012) for similarity of 1Ay
with 1Вх7, 1Ву8, 1Dy10 and 1Dy12 in many
Triticum species, and its exhibition even
stronger than 1Dy12 in common wheat.
Fig. 1. 12% SDS-PAGE of HMW-GS: 1. Ае. tauschii,
2. Bezostaya 1; 3. AD Н-68/44; 4. Chinese Spring; 5.
Т. timopheevii.
Fig. 2. 10% SDS-PAGE of HMW-GS wth urea:
1. Ae. tauschii; 2. Bezostaya 1; 3. AD Н-68/44; 4.
Chinese Spring; 5. Т. timopheevii.
Fig. 3. 12% SDS-PAGE of HMW-GS: 1. T.
turanicum; 2. Bezostaya 1; 3. AD Н-69/36; 4.
Chinese Spring; 5. Т. timopheevii.
Fig. 4. 10% SDS-PAGE of HMW-GS wth urea: 1. T.
turanicum; 2. Bezostaya 1; 3. AD Н-69/36; 4. Chinese
Spring; 5. Т. timopheevii.
Synthetic H-68/44 expressed 12 fractions in
LMW-GS (5 major and 7 minor), against 11
glutenin subunits for AD H-69/36 (Fig. 5-6).
LMW-GS were identified in the В-zone,
probably inherited from T. timopheevii.
According to the nomenclature of Gupta and
Sheppherd (1990) for the low molecular
weight of glutenins in common wheat, the two
synthetics displayed a subunit in Glu-A3,
probably coded by c allele. Two subunits in
Glu-D3 of H-68/44, similar to the expression
of a allele in common wheat cv. Chinese
Spring, were also found. They might originate
from the diploid Ae. tauschii. The protein
composition of Glu-B3 in AD H-69/36 was
not identified.
78 Doneva S., Yordanova D., Daskalova N., Spetsov P
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JAFES, Vol 69, (2016)
Fig. 5. 12% SDS-PAGE of
LMW–GS in Glu-D3: 1.
Bezostaya 1; 2. AD H-68/44; 3.
Chinese Spring; 4. AD H-69/36;
arrows indicate Glu-D3 subunits
in H-68/44 on the a allele in
Chinese Spring; Bezostaya
1 has c allele in Glu-D3.
Fig. 6. 10% SDS-PAGE with
4М урея in Glu-A3: 1.
Bezostaya 1; 2. AD H-68/44; 3.
Chinese Spring; 4. AD H-69/36;
arrows indicate Glu-A3 subunits
on the level of c allele in
Bezostaya 1; Chinese Spring has
a allele in Glu-A3.
Fig. 7. А-PAGE in gliadins: 1.
Bezostaya 1; 2. AD H-68/44; 3.
AD H-69/36; arrows indicate Gli
subunits corresponded to w1 and
w2 from Bezostaya 1; γ 43.5 is
marked in H-69/36 and
Bezostaya1.
Each synthetic line was characterized by a
distinct spectrum of gliadins (Fig. 7). AD Н-
68/44 exerted 22 bands (eight are ω-, five-γ-,
six-β- and three-α-gliadins). Slow moving pair
of ω-fractions, characteristic for Gli-D1 of
wheat check Bezostaya 1 and for any
hexaploid wheat variety, was also identified.
Six ω-, six γ-, five β- and two α-gliadins were
visualized in synthetic H-69/36. The typical
ω1- and ω2- subunits for wheat cultivars were
not expressed in this synthetic. One γ-gliadin
43.5, coded by a gene in Gli-B1 locus, was
indicated. This subunit is characteristic for
common wheat, corresponding to good gluten
quality (Тоdorov, 2006).
Conclusions
1. Expression of subunit 1Gx at Glu-G1 in two
synthetic wheat lines involving the G genome
of Triticum timopheevii, was recorded.
2. Synthetic H-69/36 exerted 1Ау subunit,
coded by a gene in Glu-A1 locus. A gliadin for
good gluten quality (γ- 43.5) was only
registered in this amphidiploid. 3. Synthetic line Н-68/44 displayed HMW-GS
1Dx2 and 1Dy12.4 subunits and different
LMW-GS in B- and D-zones, which were
absent in check wheat cultivars Bezostaya 1
and Chinese Spring. Additionally, both
synthetics showed a lot of gliadin alleles and
could be of great interest as sources of genes
for improved grain quality in wheat.
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Journal of Agricultural, Food and Environmental Sciences
UDC 635.21-186(497.742)
Original scientific paper
____________________________________________________________________________________________________
THE INFLUENCE OF FOLIAR FERTILIZATION WITH ORGANIC FERTILIZERS
ON THE YIELD AND THE CHEMICAL CONTENT OF POTATOES GROWN IN
STRUMICA REGION
M. T. Stojanova1*, L. Karakashova1, H. Poposka2,
I. Ivanovski1, B. Knezevic3
1Faculty of agricultural sciences and food, University of Ss. Cyril and Methodius, Skopje,
Republic of Macedonia 2Institute of agriculture, University of Ss. Cyril and Methodius, Skopje, Republic of
Macedonia 3Faculty of agriculture, University of Prishtina, Prishtina, Republic of Kosovo
*corresponding author: marina_stojanova@yahoo.com
Abstract
The effect of foliar fertilization with organic fertilizers on the yield and the chemical content of
potatoes grown in Strumica region were studied, in the period from the year of 2011-2012. The
experiment was set in four variants and three repetitions. The variants in the experiment were: Control
(no-fertilizing variant); Humusil (organic matter 1.86%; organic carbon 1.08%; humin acids 0.14%; N
224 mg/L; P2O5 71 mg/L; K2O 1024 mg/L; CaO 180 mg/L); Humustim (organic matter 58.63 %; dry
matter 12.38 %; humin acids 20.40 %; fulvo acids 2.15%; N 3%; P2O5 1.02%; K2O 7.92%; Ca 3.70
%; Mg 1.03%); Ingrasamant foliar (N 0 %; P2O5 130 g/L; K2O 130 g/L; ME in helate form and plant
extracts 0.005 g/L). The experiment was arranged in 12 rows and in each variant and repetition was
involved 100 plants, total in all experiment were involved 1200 plants. The planting was made in
rows at a distance of 60 cm row by row and 20 cm in the rows. The row’s length was 20 m. Three
foliar treatments were applied with given above fertilizers at a concentration of 0.4%. The soil where
the experiment was carried had a good fertility with nitrogen, phosphorus and potassium. The foliar
fertilization had a positive influence on potatoes yield in all of the variants treated with different
organic fertilizers. The highest potatoes yield of 54.62 t ha-1 was established in variant 4. The foliar
fertilization had a positive influence on the chemical content of tubers potato, too. In three variants
treated with different fertilizers, higher content of all tested parameters was found, compared to the
control untreated variant. The highest average content of vitamin C (2.60 mg/100g), phosphorus (0.90
%), and potassium (1.30 %) was determined in the tubers potato in variant 3.
Key words: potatoes, foliar fertilization, yield.
Introduction
The main goal in the modern agriculture is to
obtained higher yields that are characterized
with good quality.
One of the most important agricultural
measures, which together with the others
should allow continuous, high and cost
effective production, is plant nutrition
(Vukadinović and Lonćarić, 1997).
For normal growing, bigger yield and getting
quality fruits is necessary normal regime of
plant nutrition. Regular nutrition means
availability of all macro and micro biogenic
elements in the right phenophases of the plant
development (Jekić, 1983, Horvat et al.,
2008). Each biogenic element has its specific
influence on the different plant parts. Plant
nutrition has an influence on numerous
physiological – biochemical processes, of
which depends growing, developing and
potato yield. Plants that are timely and regular
nourished, gets fruits with characteristic form,
color and size, with typically organoleptic
properties (Sarić et al., 1989; Šaćiragić and
Jekić, 1988). Because of different reasons,
often happens limiting of biogenic elements in
the root area. Intensive agriculture and use of
high productivity cultivars led to a continuous
decrease in soil micronutrient content (Ebert
2009, Kalinova et al., 2014). Using of foliar
82 M. T. Stojanova, L. Karakashova, H. Poposka, I. Ivanovski, B. Knezevic
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JAFES, Vol 69, (2016)
fertilizers in the crop cultures nutrition, has a
big influence for getting higher yields and
productions that are characterized with better
quality, too. Using of foliar fertilizers allows
directly supply of leafs, flowers and fruits with
biogenic elements in the most needed period.
Foliar fertilization is a widely used practice to
correct nutritional deficiencies in plants caused
by improper supply of nutrients to roots
(Poljak, et al 2005, Tomov et al., 2009). Foliar
spray with fertilizers is necessary to further
activity in the whole system of optimal
mineral nutrition of plants. Foliar spray
provides more economical water regime of
plants and allows overcoming the
physiological disturbances caused by adverse
soil conditions that hamper mobility and
absorption of nutrients (Kostadinov and
Kostadinova, 2014). Potato, as one-year
culture, has a big economic importance. The
most importance has in the human nutrition, as
raw material in the industry and in the
livestock nutrition. In the human nutrition has
a principle place because of its using for
preparing lot of foods.
Potato is irreplaceable for preparing diet food.
By industrial processing, potato can
dehydrates and in this form it is easier for
keeping and transporting. In the food industry
it is using for preparing flour, mashed, fries
etc. It is also used by many other industries for
getting alcohol, starch, glucose, doctrines, and
maltose. Potato is widely used in the
conservatory and pharmacy industry (Lazić,
1990).
In the livestock nutrition it has great
importance for dairy and fattening livestock.
Potato is an excellent pre-culture for all the
cultures, especially for the cereals. After
potato harvesting, soil stay clean and loose
(Maksimoviћ and Jain, 1996). This makes it
suitable for preparation and sowing of autumn
crops. Potato is root vegetable that is
characterized with big nutrition value. Potato
is one of the richest sources of starch, minerals
and fiber. It contains vitamins A, C and B6,
minerals such as: iron, manganese, copper and
potassium (Ðinović, 1989).
The aim of this exploration is to determine the
influence of foliar fertilization with liquid
organic fertilizers on the yield and the
chemical content of potatoes grown in
Strumica region.
Material and methods
In the Strumica region, in the vicinity of the
village Kuklis during the years of 2011 and
2012 was appointed field experiment in the
protected space of 96 m2.
Material of work was potato cultivar carrera.
This is early cultivar and its vegetation period
is 95-100 days. The tubers have right globular
oval form. The experiment was set in 12 rows.
The tests included 4 variants and 3 repetitions.
Seeding was obtained in raw spacing of other
60 cm and between plants 20 cm. The rows
had 20 m length. In each variant and repetition
were included in 100 plants and total for the
whole experiment had 1200 plants. The
experiment was set in terms of watering.
During the potato vegetation period were
applied all basic agricultural measures.
Variants in the experiment were:
1. Control (no-fertilizing);
2. Humusil;
3. Humustim;
4. Ingrasa mant.
Each variant was treated foliar with 0.4%
solution of the tasted fertilizers. The
application of fertilizers was done with hand
spray, by spraying the played leaves. The
treatments were made in the evening hours.
During the vegetation were conducted seven
foliar treatments.
Three types of fertilizers were used:
Humusil (organic matter 1.86%, organic
carbon 1.08%, humic acid 0.14%, N 224
mg /L, P2O5 71 mg /L, K2O 1024 mg /L,
CaO 180 mg /L);
Humustim (organic matter 58.63%, dry
matter 12.38%, humic acids 20.40%, fulvo
acids 2.15%, N 3%, P2O5 1.02%, K2O
7.92%, Ca 3.70%, Mg 1.03 %);
Ingrasa mant (N 0%, P2O5 130 g/L, K2O
130 g/L, ME in helate form, plant extracts
0.005 g/L).
The harvesting was carried out in the full
maturity of the potatoes separately by
variations and repetitions.
Before setting up the experiment soil samples
were taken for agrochemical and analyses
were performed on the following parameters:
pH value determined potentiometric with
pH meter (Bogdanović, et al., 1966);
Content of easy available nitrogen –
determined
by method of Tjurin and Kononova;
Content of easy available phosphorus –
determined by AL method and reading of
83 M. T. Stojanova, L. Karakashova, H. Poposka, I. Ivanovski, B. Knezevic
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JAFES, Vol 69, (2016)
spectrophotometer (Bogdanović et al.,
1966);
Content easy available potassium –
determined by AL method and reading of
spectrophotometer (Bogdanović et al.,
1966);
Content of carbonates –
determined with Schaiblerov Calcimeter
(Bogdanović et al., 1966).
In the tubers potato separately by variants the
following parameters were performed:
- Moisture content - determined by
calculation when from 100%, the
percentage of total dry matters is
deducted;
- Content of total dry matters - determined
by drying the material in dryer on
temperature of 105 °C;
- Content of organic matter - determined by
calculation when from 100% the
percentage of total ash will be deducted.
- Content of total ash - determined by
removing moisture from the prepared
material, drier on temperature of 105°C.
Then the rest was burned in electric oven
by gradually increasing the temperature to
550°C. The burning was done until ashes
became grey or white;
- Content of vitamin C - determined by
method of Thilmans, which is based on the
redox reaction between L-ascorbic acid
and organic color 2.6-
dichlorophenolindophenol;
- Content of nitrogen (N) - determined by
Kjeldhal method (Saric et al., 1989);
- Content of phosphorus (P2O5) -
determined using atomic emission
spectrometry with inductively coupled
plasma (ICP - AEC) (Saric et al., 1989);
- Content of potassium (K2O) - determined
by incineration of the material with
concentrated H2SO4 and plamenfotometar
(Saric et al., 1989);
- Content of proteins - determined with
calculation when the % N is multiplying
with coefficient 6.25.
- Content of iron (Fe) - determined using
atomic emission spectrometry with
inductively coupled plasma (ICP - AEC)
(Saric et al., 1989);
Results and discussion
For getting high and quality potato yields it is
necessary favorable soil and climatic
conditions. The best potato yields are getting
in deep sand and loose soil rich in readily
available nutrients.
The optimal soil pH value for potato is weakly
acidic from 6.0 till 6.5. Potato requires high
soil permeability because tubers are deformed
by compact soils. Potato requires good soil
drainage. Waterlogged soil leads to numerous
physiological changes in tuber that become
watery and difficult to store. For successful
cultivation of potatoes of great importance is
the presence of organic matter improves soil
structure and water capacity (Lazić et al.,
2001, Baniuniene and Zekaite, 2008).
In Table 1 are shown the results of the soil
agrochemical analysis before setting up the
experiment.
Table 1. Agrochemical soil analysis
No. Tag Deep
(cm)
pH Available forms (mg/100 g soil) CaCO3
(%) H2O KCl N P2O5 K2O
1 Potato I
part
0-20 7.35 6.75 8.30 20.70 25.20 /
2 20-40 7.40 6.70 8.10 21.30 24.80 /
Average 0-40 7.37 6.72 8.20 21.00 25.00 /
3 Potato II
part
0-20 7.43 6.80 8.15 22.00 22.80 /
4 20-40 7.40 6.85 8,10 20.30 25.70 /
Average 0-40 7.41 6.82 8.12 21.15 24.25 /
From the data in the table can be concluded
that soil in which the experiment was carried
out has neutral pH, and good fertility with the
available nitrogen, phosphorus and potassium.
There is no presence of carbonates.
In Table 2 are shown the results for obtained
yield in different varieties.
84 M. T. Stojanova, L. Karakashova, H. Poposka, I. Ivanovski, B. Knezevic
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JAFES, Vol 69, (2016)
Table 2. Average potato yield 2011/2012
Variant Total yield per
variant (kg)
Average per
plant (kg)
Yield (t ha-1)
1 114.90 0.383 47.87
2 121.50 0.405 50.62
3 126.90 0.423 52.87
4 131.10 0.437 54.62
LSD (0.05) = 2.403
LSD (0.01) = 3.497
Table 3. Average chemical content of tubers 2011/2012 (% of dry matter)
Parameter Variant
1 2 3 4
Hygroscopic water 75.20 76.35 76.50 75.10
Dry matter 24.80 23.65 23.50 24.90
Organic matter 96.30 96.25 96.00 95.90
Ash 3.70 3.75 4.00 4.10
Vitamin C mg/100g 2.40 2.52 2.60 2.48
N 0.97 0.99 1.10 1.15
P2O5 0.75 0.87 0.90 0.87
K2O 1.18 1.23 1.30 1.25
Fe 0.35 0.30 0.36 0.37
Proteins 6.09 6.22 6.90 9.42
From the obtained data can be concluded that
foliar fertilization with liquid organic
fertilizers had a positive influence on potato
yield achieved. In all of the variants with
different organic fertilizers was obtained
higher yield compared to control (no-
fertilizing) variant. Higher yield (54.62t ha-1)
was obtained in variant 4 where the treatments
were made with organic fertilizer Ingrasa mant
(N 0%, P2O5 130 g/L, K2O 130 g/L, ME in
helate form, plant extracts 0.005 g/L).
The lowest yield (47.87 t ha-1) was determined
in control (no-fertilizing) variant. The
differences in achieved potato yield between
separated variants were small. The positive
foliar influence of used organic fertilizers on
potato yield is due to their chemical
composition. The presence of micro elements
in the analyzed fertilizers has a great influence
on the regular growing, development and
potato yield (Gramatikov, 2005 Bansal and
Trehan 2011). This elements has an influence
on numerous physiological – biochemical
processes that has a vital importance on
culture vegetation cycle. Balanced nutrition
plays a significant role for increasing of crop
production and its quality and presents an
essential component of nutrient management
(Panayotova et al., 2014).
Obtained results in all of the variants with
different organic fertilizers are statistically
significant at LSD (0.05) level, but in the
variants 3 and 4 the statistically significance is
at LSD (0.01) level.
Foliar fertilization has a positive influence on
the content of all determined parameters in the
tubers (Table 3). In all of the variants treated
with different kinds of fertilizers, the analyzed
parameters have higher content compared to
the control one.
The highest average content of dry matters
(24.90%) and ash content (4.10%) was
determined in the tubers from variant 4. The
content of hygroscopic water is correlated with
the content of dry matters, and its value is the
highest in the variant 3 (76.50%). The content
of organic matter (96.30%) is the highest in
the control variant. The highest average
content of vitamin C (2.60 mg/100g),
phosphorus (0.90%) and potassium (1.30%)
was determined in the tubers from variant 3.
The highest average content of nitrogen
(1.15%), proteins (9.42%) and iron (0.37%)
was determined in the tubers from variant 4.
Conclusions
Based on the obtained results for the influence
of foliar fertilization with different liquid
organic fertilizers on potato yield, the
following conclusions can be made:
The soil where the experiment was carried
out had a good fertility with nitrogen,
phosphorus and potassium;
85 M. T. Stojanova, L. Karakashova, H. Poposka, I. Ivanovski, B. Knezevic
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
Foliar fertilizing had achieved positive
effects in all variants treated with different
organic fertilizers compared to control
one;
The highest yield, 54.62 t ha-1 of potato
was determined in variant 4 (Ingrasa mant
(N 0%, P2O5 130 g/L, K2O 130 g/L, ME in
helate form, plant extracts 0.005 g/L));
The results in all variant are statistically
significant at the level LSD (0.05), and the
results in variants 3 and 4 has statistical
significance on the level LSD (0.01);
The highest average content of vitamin C
(2.60 mg/100g), phosphorus (0.90%) and
potassium (1.30%) was determined in the
tubers from variant 3 (Humustim (organic
matter 58.63%, dry matter 12.38%, humic
acids 20.40%, fulvo acids 2.15%, N 3%,
P2O5 1.02%, K2O 7.92%, Ca 3.70%, Mg
1.03 %));
The highest average content of nitrogen
(1.15%), proteins (9.42%) and iron
(0.37%) was determined in the tubers from
variant 4 (Ingrasa mant (N 0%, P2O5 130
g/L, K2O 130 g/L, ME in helate form,
plant extracts 0.005 g/L)).
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Journal of Agricultural, Food and Environmental Sciences
UDC 633.1582.661.21]:631.589.2
Original scientific paper
____________________________________________________________________________________________________
THE EVALUATION OF GRAIN AND OIL PRODUCTION, SOME PHYSIOLOGICAL AND
MORPHOLOGICAL TRAITS OF AMARANTH ‘CV. KONIZ’ AS INFLUENCED BY THE
SALT STRESS IN HYDROPONIC CONDITIONS
M. Yarnia1*, M. B. K.Benam2, E. Farajzadeh3, V. Ahmadzadeh4 N. Nobari4
1Department of Agronomy and Plant Breeding, Tabriz Branch, Islamic Azad University, Tabriz, Iran 2East Azarbaıjan Agrıcultural and Natural Resources Research Center, Tabriz, Iran
3Malekan Branch, Islamic Azad University, Malekan, Iran 4Tabriz Branch, Islamic Azad University, Tabriz, Iran
*corresponding author: m.yarnia@yahoo.com
Abstract
The purpose of this study was investigation of salinity effect on some traits of Amaranth. A split plot
designed with three replications with two factors: 5 salinity levels (control, 75, 150, 225, 300 mM
NaCl) and applied time at 4 levels (plant establishment, branching, flowering, grain filling) in a
greenhouse under hydroponic system. Application of 300 mM salinity after plant establishment led to
death of amaranth. Salinity application after establishment decreased significantly plant height and
number of branches as 44.9 and 31.8, respectively. Production of grain weight was not affected by 75
mM salinity, but at higher salinity showed significantly decrease. The highest decrease in grain
weight obtained by applying 225 mM salt after the plant establishment and salinity at 300 mM after
branching as 86.6 and 71.3 percent respectively, resulting in a decrease in both 1000 kernel weight
and grain number, respectively. Salinity application increased H2O2, MDA and total phenolics
contents, severely. Most of characteristics hadnot affect by 75 mM NaCl, but other concentrations had
a negative effect on the growth and production of Amaranth and increasing salinity had more negative
impact. In this study, the most sensitive to salinity was after plant establishment and grain filling stage
was the most tolerant.
Key words: Amaranth, growth stage, salinity, yield.
Introduction
Amaranth belongs to genus Amaranthus. The
genus includes about 60 species of amaranth
that the majority of them are wild. Some of
them as edible crops and some of them are
used as ornamental crop (Borneo & Aguirre,
2008; Pospisil et al., 2006). Based on the soil
map published in recent years, the area of soils
with low to moderate salinity is 25.5 million
hectares and 8.5 million hectares of soils
tolerate high salinity (Almodares et al., 2008).
Salinity leads to serious changes in the
photosynthesis and photorespiration of plants
(Vega et al., 2006). High levels of sodium
reduce potassium adsorption and its
accumulation in the cytoplasm stopped the
activity of many enzymes (Jaleel et al., 2008),
because, potassium had import role in various
processes such as metabolism, growth and
adaptation to stresses. The salinity prevents
enzyme activity, cell division and
development, and causes disorganization of
the membrane and ion balance and eventually
led to the growth stop (Mahajan et al., 2008).
Salinity had a significant reduction in growth
and yield of Amaranthus family. Omami
(2005) and Omami et al., (2006) studied
salinity impact on Amaranth cultivars ( A.
tricolor ،Accession ’83 ،A. hypochondriacus
and A. cruentus showed that increasing salinity
in the soil leads to a significant reduction in
crop height, leaf area, specific leaf area, and
stomatal conductance rates. Dave and Patel
(2011) examined effect of salinity 2.7, 5.5, 8.5,
11.1 and 13.8 ds/m in A. lividus. The root and
shoot length, number of leaves, fresh and dry
weight of leaves, roots and stems showed a
significant decreased with increasing salinity
levels. In this study proline showed a
significant increase with increasing salinity,
while chlorophyll content reduced by salinity.
Salinity reduced number of hairy roots and
88 M. Yarnia, M. B. K.Benam, E. Farajzadeh, V. Ahmadzadeh.N. Nobari
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JAFES, Vol 69, (2016)
distal root growth and root cells were more
resistant to water penetration (Wang & Li,
2008). Malondialdehyde (MDA) a product of
lipild peroxidation, showed greater
accumulation in plants under stress condition.
Cell membrane stability has been widely used
to differentiate stress tolerant and susceptible
cultivars of some crops, and in some cases,
lower MDA content could be correlated with
stress tolerance (Wang et al., 2009). As salt
stress occur frequently and can affect most
habitats, plants have developed several
strategies to cope with these challenges. One
of the stress defense mechanisms is the
antioxidant defense system, which includes
antioxidant enzymes. antioxidant enzymes
converts H2O2 into water and oxygen (Gaber,
2010). Soil salinity is one of the most
important environmental and ecological
tensions in many parts of the world, nowadays
is one of the main reasons in reduction of
agricultural products. Grain amaranth is new
crop with high yield potential and good
nutrition can be a good substitute for salt-
sensitive crops in such areas. Growth study
reactions and seed production in saline
conditions and determining plant tolerance to
salinity and the sensitivity of the different
growth stages were important also.
Material and methods
The experiment was conducted in greenhouse
of Tabriz Branch, Islamic Azad University,
located at 15 km East of Tabriz in 2013. This
place located at 46, 17 E and 38, 5 N degrees
with 1360 meters altitude. Salinity factor
levels in 5 different levels (control, salinity
stress, 75, 150, 225 and 300 mM NaCl) and
applied stress time at 4 levels (plant
establishment, branching, flowering and grain
filling) under hydroponic system with
Hoagland solution arranged as split plot with
three replications in grain amaranth CV. Koniz
(Amaranthus hypochindriacus L.×
Amaranthus hybridus L.) as a new crop. 1100
g. perlite medium grain size was filled into
pots. Seeds randomly distributed on the
surface of the perlite. Nutrition of crops was
supplied by using nutrient solution after
emergence. Hoagland's A-Z solution is used to
provide macro and micro nutrients (Nenova,
2008). 2 weeks after emergence, seedlings
have been thinned to 5 plants per pot and in
third week after emergence were kept only 3
plants per pot. Every 4 days nutrient solution
(1/2 fold in the early period of growth) was
supplied to plants (Nenova, 2008). The amount
of used solution for treatment was determined
based on available water in each pot. For this
purpose, the weight of irrigated perlite
determined after 24 hours and the initial
weight of pearlite before irrigation was
fractioned. Then the amount of water turned to
volume. The resulted number is between 550
to 600 mL of water for each pot. Accordingly,
550 mL of each solution was used for the
treatments. No water leaching was permitted
from pots. After 30 days excess water used to
leaching pots. Hydrogen peroxide content in
amaranth leaves at grain filling stage were
determined according to Velikova et al.,
(2000). The level of lipid peroxidation
(Malondialdehyde: MDA) was determined in
terms of thiobarbituric acid-reactive
substances (TBARS) concentration as
described by Noreen and Ashraf (2009). After
harvest, characteristics such as plant height,
number of branches, seed weight and seed
weight per plant was measured. Grain oil
percentage were measured by micro-
souqksole. Before statistical analysis, the
normality test of data was performed. Data
analyzed using MSTATC software. Mean
comparisons done by Duncan's multiple range
test at the 5 percent level.
Results and discussion
Applying different levels of salinity different
growth stages and their interaction was
significant for all traits (Table 1).
Plant height: Salinity applying in the
beginning stages of branching, flowering and
grain filling had no significant effect on plant
height, but salinity levels affected plant height.
Salinity up to 150 mM did not affect on plant
height at establishment stage but increasing
significantly decreased plant height. Salinity
level at 225 mM, decreased plant height to 38
cm which was 44.9 percent lower than the
control treatments mean (Fig. 1). Omami
(2005) studied effect of salinity on some
varieties of grain amaranth (A. tricolor,
Accession '83, A. hypochondriacus and A.
cruentus) and announced that 200 mM salt
decreased A. hypochondriacus height at a rate
of 62% and A. cruentus by 59%. Apply 300
mM NaCl after establish stage led to plant
death. Simple linear regression equation
showed that for every unit increase in salinity
in the growth stage, plant height reduced 14.9
89 M. Yarnia, M. B. K.Benam, E. Farajzadeh, V. Ahmadzadeh.N. Nobari
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JAFES, Vol 69, (2016)
units. While the reduction in the branching and
grain filling was 4.6 and 2.6 units,
respectively, which may not provide a
significant effect (Fig. 1).
Branch number: Salinity at beginning of
branching, early flowering and grain filling
stages had not significant effect on number of
branches per Amaranth plant. In this study,
300 mM salt after plant establish had a
significant effect on number of branches (Fig.
2). The beginning and end of branching in
amarath depends on the type of crop and
environmental factors. In most crops
branching ends by beginning of flowering
(Beveridge et al., 2003).
1000 Kernel Weight: Salinity applying at 75,
150 and 225 mM in the establishment stage of
Amaranth reduced 10, 13.3 and 23.3 percent of
the 1000 kernel weight respectively (Fig. 3).
Stress at different growth stage had different
results. In this study, salinity applying 75 mM
in the beginning stages of branching and
flowering decreased 16.6 and 13.3 percent of
1000 kernel weight, respectively. Salinity
application at 150 mM at the beginning of
branching was not affected 1000 kernel weight
and 150 mM salt in the flowering stages,
increased 1000 kernel weight significantly.
This increase was due to a decrease in the
number of grain per plant (Fig. 4) which leads
to more assimilate for grain filling. In the
higher salinity of 150 mM was observed
significantly reduction in 1000 kernel weight.
Simple linear regression equations showed that
for every unit increase in salinity after the
establishment, 1000 kernel weight was
reduced 0.65 units. The reduction in the
branching and flowering stages was 0.22 and
0.08 unit respectively. Changes rate in salinity
levels after grain filling hadn't significant
differences. Thus, the delay in applying
salinity reduced the negative effects of salt
stress on 1000 kernel weight (Fig. 3).
Applying salinity stress in crop growth stage
reduced growth. Similar results have been
observed in other grain crops also (Omami,
2005). Research has shown that reproductive
organs of plants are more sensitive to
environmental stresses than grain filling period
(Gelalcha & Hanchinal, 2013). This
experiment showed a significant reduction in
seed weight also. Application 225 and 300
mM salinity at the branching reduced 20% and
36%, respectively and application 300 mM salt
in flowering stage decreased 1000 kernel
weight as 16.6%.
Seed number per plant: The maximum
number of grain per plant was 5524 in control.
Salinity of 75 mM had not effect on seed per
plant, however, higher salinity levels showed
significantly negative effect on seed per plant.
The decrease in seed per plant at salinity of
225 and 300 mM, was 38.5 and 56%,
respectively. Application of 150, 225 and 300
mM, in the beginning stages of branching
reduced 35.4, 38.5 and 35.5%, respectively,
the number of seed per plant. Application of
225 mM salinity after crop establishment
reduced 81.2% of seed number per plant.
Application of 150 mM salinity at crop
establishment reduced 50.2% seed number per
plant. So in three concentrations of 150, 225
and 300 mM, the maximum reduction in the
number of seed per plant was affected by
salinity imposed in the early stages of crop
growth (Figure 4). Salinity reduced number of
branches per plant and growth and
development such as reducing number of
florets and earliness flowering of plant
affected by salinity (Muuns & Tester, 2008).
Seed weight per plant: Maximum seed
weight was 15 g in control treatment. 75 mM
salinity had not effect on Amaranth seed
production, but on the other salinity levels
depending on the stage that salt stress was
applied, the weight of the produced seed
reduced. In all three levels of salinity, 150, 225
and 300 mM, the maximum reduction in yield
was in the stage of crop establishment. Seed
yield in both the 150 and 225 mM stress after
crop establishment stage was 6 and 2 g per
plant, respectively, which was 60 and 86.6%,
respectively, less than control. Stress at the
onset of branching in salinity levels of 150,
225 and 300 mM, a significant reduction in
seed weight was obtained. In the three
treatments, seed weight was 8.3, 7.3 and 4.7 g,
which 38, 46.6 and 71.3 % respectively, less
than control. With increasing salinity levels
seed yield of amaranth decreased (Fig. 5).
With increasing solute concentrations yield
decreased and even plant dies at high
concentrations. According to study, the low-
salt (75 mM) concentration had not affected
Amaranth seed yield, but higher salinity
concentration showed significant decreasing
yield. Application of 225 and 300 mM salt at
the beginning of flowering decreased 40 and
66.6% of the seed weight. Simple linear
90 M. Yarnia, M. B. K.Benam, E. Farajzadeh, V. Ahmadzadeh.N. Nobari
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
regression equations showed that for every
unit increase in salinity after crop
establishment, seed production reduced 47.3
units. The reduction in branching and
flowering stages were 1.9 and 1.7 units,
respectively. Changes observed in
morphological traits and yield components of
produced seed after seed filling stages were
not significant (Fig. 5).
Oil Production: As the stress is increased, oil
percentage decreases. In addition, the stress
application in the early stages of growth had a
greater impact on oil percentage. The highest
reduction in oil percentage was observed with
applying salinity stress in the establishment
stages. Applying salinity stress in the
establishment, branching, early flowering and
grain filling stages respectively led to 80, 62,
51 and 30% decrease in amaranth’s oil
percentage compared to control condition. The
study of linear regression equation showed that
for every unit increase in salinity after the
establishment ,branching, flowering and grain
filling stages, 3.76, 2.89, 2.12 and 1.41 unit of
oil percent were reduced. Thus, amaranth’s oil
production is more sensitive to salinity stress
compared to its other characteristics (Fig. 6).
H2O2, MDA and total phenolics contents: Salinity was increased MDA, the H2O2 and
total phenolics contents in amaranth leaves
(Table 2). The salinity levels of 75 mM had no
significant effect on H2O2 and MDA content in
amaranth leaves. However, enhancment of
salinity to 150, 225 and 300 mM significantly
increased H2O2 content as 35.9, 50.3 and
74.7%, respectively compared to non saline
conditions; these increase for MDA amount
were 62.9, 77.3 and 86.9 % respectively.
Result showed that total phenolics contents in
amaranth leaves significantly increased with
enhancment of salinity from non salinity
condition to 75, 150, 225 and 300 mM NaCl as
15.7, 24.2, 33.7 and 46.8% respectively (Table
2). The high increase content of H2O2 showed
that amarant in high salinity levels was
sensitive; on the other hand the high increase
content of MDA is Amaranth appropriate
response to salinity. MDA is the
decomposition product of polyunsaturated
fatty acids of membranes under stress. The rate
of lipid peroxidation level in terms of MDA
can therefore be used as an indication to
evaluate the tolerance of plants to oxidative
stress as well as sensitivity of plants to salt
stress. It is also known that the formation of
ROS enhances peroxidation at the cellular
level and that the rate of such enhancement
relates to plant species and the severity of
stress (Wang et al., 2009). Variation in MDA
contents were found in rice (Tijen & Ismail,
2005) and cotton (Meloni et al., 2003)
cultivars differing in salt tolerance. In
Amaranth leaves H2O2 remained changed due
to salt stress. While, in contrast, it is generally
known that salt stress enhances the production
of singlet oxygen, superoxide anion, H2O2 and
hydroxyl radical in plants. However,
regulation of these ROS depends on their rates
of generation, their rate of reaction with other
metabolites such as proteins, lipids and nucleic
acids, their rate of degradation and rate of their
neutralizing by enzymatic or non-enzymatic
antioxidants. Generally, the dismutation of two
superoxide anions, either enzymatically or
non-enzymatically, give rise to H2O2. H2O2 is
also produced from the β oxidation of fatty
acids and peroxisomal photorespiration
reactions (Noreen & Ashraf, 2009).
Conclusions
Seed yield reduction and its components
within components of Amaranth growth
indices affected by salinity were similar to
most crops. Based on these results, the grain
amaranth cultivar (cv. Koniz) growth factors
such as crop height, productive branches and
yield components such as number and grain
weight decreased with increasing salinity.
Highest and lowest significant reduction in
seed yield production was 86 % and 1000
kernel weight was 13 %. Salinity up to 75 mM
had not significant effect on most
morphological and physiological attributes.
According to not significant changes of
imposing salinity on different characteristics at
different stages of crop growth, it can be
concluded that grain Amaranth has a good
tolerance to the environmental stresses ranging
up to 75 mM NaCl extrusion. But with the
increasing salinity, significant negative effects
on the crop increased and in 300 mM salt plant
died in end of growth. Earlier salinity
imposing increased salinity effect on plant, but
extremely high salinity occurs at grain filling
stage had no effect on seed production. The
occurrence of moderate salinities (150 and 225
mM) in the later stages of the plant life in the
post-blooming stage did not cause a significant
loss, but, rising tension in early period was not
suitable for Amaranth. Grain Amaranth can
91 M. Yarnia, M. B. K.Benam, E. Farajzadeh, V. Ahmadzadeh.N. Nobari
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JAFES, Vol 69, (2016)
produce suitable seed production in areas with
low salinity and the most important limitation
was high salinity of the soil in these areas in
the entire developmental period.
Acknowledgements
We wish to thank the Tabriz Branch, Islamic
Azad University for financial support of this
project.
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Table 1. Analysis of variance of traits in Amaranth
SOV df Plantا
height
Branch
No MDA H2O2 Total phenol
salinity
levels 4 877.79** 4.23** 53.89** 21. 43 * 4.54 *
salinity
applying
time
3 3141.02** 8.84** 6.23 4.41 0. 65
salinity
level×time 12 492.09** 2.29** 0.87 2.34 0.22
error 40 70.35 0.45 18.57 3.84 0.88
CV (%) 13.17 16.23 13.68 13.83 7.04
and ** significant at 5% and 1% levels, respectivly
Table 1. Continue
SOV df 1000 kernel
weight
Seed No
per plant
Seed W
per plant Oil percentage
salinity levels 4 3.063** 15953857.1** 152.77** 163.88**
salinity applying time 3 2.475** 8674358.6** 99.66** 52.79**
salinity level×time 12 0.933** 3010661.5** 26.58** 4.35**
error 40 0.017 357547.5 3.5 0.516
CV (%) 4.76 17.01 18.37 5.43
and ** significant at 5% and 1% levels, respectivly
Table 2. Mean of H2O2, Total phenolics and MDA content as affected by NaCl levels
NaCl
(mmol)
H2O2
(µmol/g fw)
Total phenolics
( mg/g fw)
MDA
(nmol/g fw)
0 9.23 d 4.21 d 2.91 cd
75 10.33 dc 4.87 c 3.37 c
150 12.54 c 5.23 bc 4.74 b
225 13.87 b 5.63 b 5.16 ab
300 16.12 a 6.18 a 5.44 a
Treatments with the same letter(s) don’t have significant difference
d
c
bc
abcabcabcabc
abab
abc
ababab
abab
ab
ab
ab
aa
Stablishment: y = -14.901x + 87.237
R2 = 0.8395
Grain filling: y = -4.599x + 88.931
R2 = 0.8248
Flowering: y = 2.501x + 62.299
R2 = 0.6413
Branching: y = -2.599x + 74.999
R2 = 0.4822
0
10
20
30
40
50
60
70
80
90
Control(0) 75 150 225 300
NaCl (mMol)
Pla
nt
Heig
ht
(cm
)
Stablishment Branching Flowering Grain filling
Fig. 1. Comparison means of plant height affected
by salinity and applying time
aa
a a
b
aa
aa
a
a
a
a aa
aa a a a
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Control(0) 75 150 225 300
NaCl (mMol)
Bra
nc
h N
o.
Stablishment Branching Flowering Grain fi l l ing
Fig. 2. Comparison of number of branches
affected by salinity and apply time
93 M. Yarnia, M. B. K.Benam, E. Farajzadeh, V. Ahmadzadeh.N. Nobari
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
g
e
dcd
b
f
d
b
d
b
de
bc
a
d
bbc
b
bcbc
b
Flow ering: y = -0.0833x + 3.2363
R2 = 0.0901
Branching: y = -0.2201x + 3.3405
R2 = 0.4804
Grain f illing: y = -0.0233x + 3.0965
R2 = 0.3325
Stablishment: y = -0.65x + 4.0966
R2 = 0.702
0
0.5
1
1.5
2
2.5
3
3.5
4
Control(0) 75 150 225 300
NaCl (mMol)
1000 k
ern
el w
eig
ht
(g)
Stablishment Branching Flow ering Grain f illing
Fig. 3. Comparison of 1000 kernel weight under
influence of salinity and application times
g
fg
ef
aba-e
ef
dede
a-d
a-d
ef
decde
ab
ef
a-da-d
b-e
a-e
a
Grain filling: y = -111.6x + 4800.2
R2 = 0.0543
Flowering: y = -577.2x + 5161.4
R2 = 0.6731
Branching: y = -720.9x + 5718.5
R2 = 0.8909Stablishment: y = -1359.4x + 6686.4
R2 = 0.9131
-1000
0
1000
2000
3000
4000
5000
6000
Control(0) 75 150 225 300
NaCl (mMol)
Grain
per p
lan
t
Stablishment Branching Flowering Grain filling
Fig. 4. Comparison of number of seed per plant
under influence of salinity and application times
f
ef
c-f
abab
def
b-e
bcd
abc
ab
def
b-e
bcd
abab
ab
ab
bcda-d
a
Grain filling: y = -0.399x + 12.865
R2 = 0.0723
Flowering: y = -1.7003x + 13.902
R2 = 0.887
Branching: y = -1.9003x + 14.368
R2 = 0.9845
Stablishment: y = -3.467x + 16.735
R2 = 0.9042
-2
0
2
4
6
8
10
12
14
16
Control(0) 75 150 225 300
NaCl (mMol)
Gra
in w
eig
ht
(g/p
lant)
Stablishment Branching Flowering Grain filling
Fig. 5. Comparison of grain yield production in
crop affected by salinity and time application
p
n
lm
hij
cde
o
m
ijk
abcab
n
jk
ghiefg
ab
kl
fghdef
bcd
a
Stablishment: y = -3.7617x + 21.184
R2 = 0.909
Branching: y = -2.8954x + 21.737
R2 = 0.9617 Flowering: y = -2.121x + 19.997
R2 = 0.9468
Grain filling: y = -1.412x + 19.618
R2 = 0.9668
0
2
4
6
8
10
12
14
16
18
20
Control=0 75 150 225 300
NaCl (mmol)
Oil
percen
tag
e (
%)
Stablishment Branching Flowering Grain filling
Fig. 6. Comparison of oil percentage under
influence of salinity and application times
Journal of Agricultural, Food and Environmental Sciences
UDC 633.15-152.75:631.461(497.11)"2010"
Original scientific paper
____________________________________________________________________________________________________
YIELD RESPONSE OF FIVE MAIZE HYBRIDS TO INOCULATION WITH
RHIZOBACTERIA
N. Mrkovački 1*, D. Bjelić 1, D. Jošić 2, I. Đalović 1
1Institute of Field and Vegetable Crops, Novi Sad, Serbia
2Institute of Soil Science, Belgrade, Serbia
*corresponding author: nastasija.mrkovacki@nsseme.com
Abstract
The biofertilizers are found positive contribution to soil fertility, resulting in an increase in crop yield
without causing any environmental, water or soil pollution hazards. Nitrogen fixing and phosphorus
solubilizing bacteria play an important role in nitrogen mobilization and phosphorus solubilization for
the benefit of plant growth. A field experiment to study yield response of maize to inoculation with
rhizobacteria, was conducted during 2013 at experimental field of Institute of Field and Vegetable
Crops in Novi Sad. The maize hybrids (NS 3014, NS 4015, NS 5043, NS 6010 and NS 6030) were
used in the study. The field experiment was laid out in randomized complete block design with four
treatments (control and 3 inoculations) and four replications. Inoculation was done with Pseudomonas
PS2, Bacillus Q7 and their mixture with Azotobacter chroococcum (Q7 + PS2 + AC). Application
method was incorporation immidiately before planting with liquid culture of strains (1 l + 300 l H2O
ha-1). The results showed significant increase in maize yield with inoculation treatments. The best
effect on maize yield was achieved with mixture of strains (19.7%). Significantly higher yield was
obtained for hybrids NS6010 and NS 6030. The highest increase in yield of maize was achieved with
hybrid NS 6030 (32.2%). Statistically significant differences in comparison to the control were
obtained on treatments with Q7 and PS2 + Q7 + AC.
Key words: Azotobacter, Bacillus, Pseudomonas, yield.
Introduction
Maize is one of the most important cereal
crops in the world. In 2010, this crop was
grown in an area of nearly 162 million ha and
occupied second place in overall production
(http://faostat.fao.org). In Serbia, maize is
grown on about 1 200 000 ha and the total
grain production is between 4 and 7 million
tons per year. The grain yield of maize
dependson the genetic potential of a hybrid,
soil characteristics, agrotechnical measures
and climatic factors (Jocković et al., 2010;
Đalović, 2014).
Microbial inoculants are highly ranked among
promising alternatives for reducing global
fertilizer inputs into agroecosystems. Their use
has been steadily growing through the last
decade. some microbial inoculants are able to
improve nutrient availability and plant uptake
capability, thereby reducing nutrient inputs
and increasing the use efficiency of applied
chemical fertilizers. Single or mixed inoculant
formulations containing plant growth
promoting bacteria (PGPB) stimulate plant
growth by diverse mechanisms, which include
biological nitrogen fixation, synthesis of
hormones and a variety of other molecules,
phosphate solubilization and biological control
of pathogens.
Maize (Zea mays L.) is widely used for human
and animal food and is a staple in many
95 N. Mrkovački, D. Bjelić, D. Jošić, I. Đalović
____________________________________________________________________________________________________
JAFES, Vol 70, (2016)
developing world communities where small
increases in productivity without increasing
production costs represent significant gains in
food security. Thus, new technologies
promoting the effectiveness of bioinoculants
based on endophythyc diazotrophic microbes
(such as plant growth promoting bacteria
(PGPB) are of compelling social
environmental reelvance).
Significant increases in growth and yield of
agronomical important crops in response to
inoculation with PGPR have been reported by
Asghar et al. (2002), Bashan et al. (2004) and
Biswas et al. (2000). Azospirillum,
Pseudomonas and Azotobacter strains could
affect seed germination and seedling growth
(Shaukat et al. 2006). Kloepper et al. (1992)
has been shown that wheat yield increased up
to 30% with Azotobacter inoculation and up to
43% with Bacillus inoculation. Strains of
Pseudomonas putida and Pseudomonas
fluorescens could increase root and shoot
elongation in canola (Glick et al. 1997) as well
as wheat and potato (De Freitas and Germida,
1992; Frommel et al., 1993). Thus it has been
shown that Azospirillum and Pseudomonas had
the potential for agricultural exploatation and
could use as natural fertilizers (Bashan et al.,
1989; Cakmakci et al., 2006).
The main objestive of this research was to
determine the effect og PGPR strains on yield
of five maize hybrids.
Material and methods
The trial was conducted at Rimski Sancevi
experimental field of Institute of Field and
Vegetable Crops in Novi Sad. The
experimental objects were five hybrids of
maize (NS 3014, NS 4015, NS 5043, NS 6010
and NS 6030) developed at Institute and three
treatments with microorganisms. Non
inoculated treatment was control. Inoculation
was done with Pseudomonas PS2, Bacillus Q7
and their mixture with Azotobacter
chroococcum (Q7 + PS2 + AC). Application
method was incorporation immediately before
planting with liquid culture of strains (1 l +
300 l H2O ha-1). The experimental design was
a randomized, complete block with four
replications. Data were analyzed by the
analysis of variance; LSD test were used to
separate treatment means when there was a
significant difference at the P<0.05 level. All
analyses were conducted using the statistical
software package STATISTICA 10.0 (StatSoft
Inc. USA) (Mead et al., 1996).
Results and discussion
The results showed significant increase in
maize yield with inoculation treatments (Table
1). The best effect of inoculation was achived
with mixture of strains (PS2 + Q7 + AC). The
highest yield was obtained with hybrids NS
6010 and NS 6030 on all examined treatments
in comparison with control. The highest
increase in yield of maize was achieved with
hybrid NS 6030 (32.2%). Statistically
significant differences in comparison to the
control were obtained on treatments with Q7
and PS2 + Q7 + AC.
96 N. Mrkovački, D. Bjelić, D. Jošić, I. Đalović
____________________________________________________________________________________________________
JAFES, Vol 70, (2016)
Table 1. Effect of inoculation with PGPR on maize yield
Treatment Hybrid Yield (t ha-1)
Control
NS 3014 6.23f
NS 4015 6.77ef
NS 5043 6.82ef
NS 6010 7.38cde
NS 6030 6.89def
Treatment 1: Pseudomonas PS2
NS 3014 6.32f
NS 4015 6.83ef
NS 5043 6.95def
NS 6010 7.56bcde
NS 6030 7.64bcde
Treatment 2: Bacillus Q7
NS 3014 6.98def
NS 4015 7.48cde
NS 5043 7.85bcd
NS 6010 8.19abc
NS 6030 8.29abc
Treatment 3: PS2 + Q7 + AC
Pseudomonas + Bacillus + Azotobacter
NS 3014 7.42cde
NS 4015 7.65bcde
NS 5043 8.13abc
NS 6010 8.49ab
NS 6030 9.11a Means with the same letter are not significantly different at the P = 0.05 level of significance
Co–inoculation (Azotobacter, Bacillus,
Pseudomonas) had an advantage compared to
single inoculation, which is similar in our
results, while in case of single strains, better
effects were achieved in Pseudomonas and
Azotobacter treatments (Jarak et al., 2012).
Hajnal-Jafari (2010) investigated the effect of
co–inoculation of NS 640 maize hybrid on the
grain yield and microbiological activity in the
rhizosphere. The results obtained over the
period of three years showed that the average
grain yield amounted to when microbial
inoculants were used, and that microbiological
variants had a significant effect on the total
number of microorganisms, number of
aminoheterotrophs, free nitrogen–fixing
bacteria and phosphorus–mobilizing bacteria.
Mixture of biofertilizers, biostimulants and
biopesticides (A. chroococcum, A. vinelandi,
A. lipoferum, B. megaterium and B. subtilis)
caused an increase in the yield of all three
investigated maize hybrids (Govedarica et al.,
2002). Results of Hamidi et al. (2009)
revealed that co–inoculation with PGPR (A.
chroococcum, A. lipoferum, A. brasilense and
P. fluorescens) had the highest promoting
effect on phenology and grain yield of maize
hybrids. The best results on dry matter
accumulation and yield of maize hybrids were
obtained by the plots which seeds were
inoculated with Azotobacter bacteria compared
with Azosprillium and Azotobacter +
Azosprillium priming (Sharifi et al., 2011).
Findings of Umesha et al. (2014) have clearly
showed that combined application of
Azotobacter chroococcum, Bacillus
megaterium and Pseudomonas fluorescens
along with recommended dose of NPK and
enriched compost has resulted in obtaining
highest plant growth, crop yield and dry matter
production of maize.
References
Asghar, H.N., Zahir, Z.A., Arshad, M., Khaliq,
A. (2002). Releationship between in vitro
production of auxins by rhizobacteria and their
growth promoting activities in Brassica juncea
L. Biol. Fert. Soils No. 35, pp. 231-237.
Bashan, Y., Holguin, G., de-Bashan, L.E.
(2004). Azospirillum-plant relationships:
physiological, molecular, agricultural, and
97 N. Mrkovački, D. Bjelić, D. Jošić, I. Đalović
____________________________________________________________________________________________________
JAFES, Vol 70, (2016)
environmental advances (1997-2003). Can. J.
Microbiol. No. 50, pp. 521-577.
Bashan, Y., Ream, Y., Levanony, H.L., Sade,
A. (1989). Non-specific response in plant
growth yields and root colonization of non-
cereal crop plants to inoculation
with Azospirillum brasilense cd. Can. J. Bot.
No. 67, pp. 1317-1324.
Biswas, J.C., Ladha J.K., Dazzo F.B. (2000).
Rhizobia inoculation improves nutrient uptake
and growth of lowland rice. Soil Sci. Soc. Am.
J. No. 64, pp.1644–1650.
Cakmakci, R., Donmez, F., Aydin, A., Sahin
F. (2006). Growth promotion of plants by
plant growth-promoting rhizobacteria under
greenhouse and two different field soil
conditions. Soil Biol. Biochem. No. 38, pp.
1482-1487.
De Freitas, J.R., Germida, J.J. (1992). Growth
promotion of winter wheat by fluorescent
pseudomonads under growth chamber
conditions. Soil Biol. Biochem. No. 24, pp.
1127-1135.
Đalović, I. (2014). More important
morphological traits and the content of mineral
elements in maize at the different levels of
fertilization. Ph.D. Thesis. Faculty of
Agriculture, University of Novi Sad.
Frommel, M.I., Nowak J., Lazarovits, G.
(1993). Treatment of potato tubers with a
growth promoting Pseudomonas sp.: Plant
growth responses and bacterium distribution in
the rhizosphere. Plant Soil No. 150, pp. 51-60.
Glick, B.R., Changping, L., Sibdas, G.,
Dumbroff, E.B. (1997). Early development of
canola seedlings in the presence of the plant
growth-promoting
rhizobacterium Pseudomonas putida GR12-2.
Soil Biol. Biochem. No. 29, pp.1233-1239.
Govedarica, M., Milosević, N., Jarak, M.,
Đuric, S., Jeličić, Z., Kuzevski, J., Đorđević,
S. 2002. Use of biofertilizers, biostimulators
and biopesticides in agriculture production.
Field Veg. Crop Res. No. 37, pp. 85-95.
Hajnal-Jafari, T. (2010). Effect of inoculation
on the yield and microbial activity in soil
under maize. PhD thesis. Faculty of
Agriculture, University of Novi Sad.
Hamidi, A., Chaokan, R., Asgharzadeh, A.,
Dehghaoshoar, M., Ghalavand A., Malakouti,
M.J. (2009). Effect of plant growth promoting
rhizobacteria (PGPR) on phenology of late
maturity maize (Zea mays L.) hybrids. Iranian
J. Crop Sci. No. 11, pp. 249–270.
Jarak, M., Mrkovački, N., Bjelić, D., Jošić, D.,
Hajnal-Jafari, T., Stamenov, D. (2012). Effects
of plant growth promoting rhizobacteria on
maize in greenhouse and field trial. Afr. J.
Microbiol. Res. No.6, pp. 5683–5690.
Jocković, Đ., Stojaković, M., Ivanović, M.,
Bekavac, G., Popov, R., Đalović, I. (2010).
NS maize hybrids – today and tomorrow. Field
Veg. Crop Res. No. 47, pp. 325–333.
Kloepper, J.W., Beauchamp, C.J. (1992). A
review of issues related to measuring
colonization of plant roots by bacteria. Can. J.
Microbiol. No. 38, pp. 1219-1232.
Mead, R., Curnow, N.R., Hasted, M.A. (1996).
Statistical methods in agriculturae and
experimental biology, Chapman and Hall,
London, pp. 415.
Sharifi, R.S., Khavazi, K., Gholipouri, A.
(2011). Effect of seed priming with plant
growth promoting Rhizobacteria (PGPR) on
dry matter accumulation and yield of
maize (Zea mays L.) hybrids. J. Food Agr.
Environ. No. 9, pp. 393–397.
Shaukat, K., Affrasayab, S., Hasnain, S.
(2006). Growth responses of Triticum
aestivum to plant growth promoting
rhizobacteria used as a biofertilizer. Res. J.
Microbiol. No. 1, pp. 330-338.
Umesha, S., Srikantaiah, M., Prasanna, K.S.,
Sreeramulu, K.R., Divya, M., Lakshmipathi,
R.N. (2014). Comparative effect of organics
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55-62.
http://faostat.fao.org
Journal of Agricultural, Food and Environmental Sciences
UDC 633.11-116.424(497.11)
Original scientific paper
__________________________________________________________________________________________
YIELD AND YIELD COMPONENTS ON SOME WHEAT VARIETIES GROWN IN
ALEKSINAC REGION
D. Cvetkovic1, D. Boshev2*, Z. Dimov2,
S. Ivanovska2, M. Jankulovska2
1Agricultural Pharmacy “Pchela Prom”, Aleksinac, R. of Serbia
2Faculty of Agricultural Sciences and Food, UKIM, Skopje, R. of Macedonia
*corresponding author: dbosev@yahoo.com
Abstract
Yield and yield components of 5 wheat varieties (Kruna, Toplica, Zvezdana, Etida, Angelina) in
Aleksinac region (Serbia) were analysed. The experiment was performed in randomized block design
in 3 replications on the experimental field in area of Aleksinac city. The results showed relatively high
yields in all varieties. The general average yield was 6140 kg ha-1. The highest average yield varied
from 6858 kg ha-1 in cultivar Zvezdana to 5050 kg ha-1 in Toplica. The cultivar Kruna showed lowest
number of productive stems per square meter – 572, and largest number in Zvezdana and Angelina,
with an average of 658 and 641, respectively. Average longest spike was found in variety Angelina
12.4 cm, and shortest in Toplica (9.8 cm). The average number of spikelets per spike for all cultivars
was 19.4. Cultivar Angelina showed biggest number (21.1), and Kruna smallest number (17.9). The
biggest number of grains per spike was obtained in cultivar Etida(54.8), and lowest in Zvezdana
(51.4). During the examination, the highest average value for hectoliter weight is obtained in variety
Zvezdana (78.3 kg hl-1), and lowest in Toplica (75.4 kg hl-1). From the data on yield and yield
components, it can be concluded that all tested varieties can be grown in the region of Aleksinac, with
preference to varieties Zvezdana and Etida.
Key words: wheat, yield, yield components.
Introduction
Wheat is grown on about 600000 ha in Serbia
(http://webrzs.stat.gov.rs/WebSite/repository/d
ocuments/). About 52 % of this area is on the
territory of Vojvodina, and 48 % in the other
regions of Serbia. Average yield at the State
level is around 3.4 t ha-1 (Malesevic et al.,
2011). In terms of assortment, most national
varieties are developedin the Institute of Field
and Vegetable Crops in Novi Sad and Institute
for cereals in Kragujevac, and the rest are
imported varieties.However, although there
are many varieties, in Serbia is noticeable
appearance of greater variation of the area
under wheat, tending to their slight decline last
years
(http://webrzs.stat.gov.rs/WebSite/repository/d
ocuments/). Introduction of new varieties in
production for all different microclimatic areas
is one of the measures that can achieve a stop
to this trend, because, achieving the genetic
potential for yield and quality largely depends
on environment conditions in micro areas
(Hristov et al., 2010). Proper classification of
level of microclimate conditions may be the
key factor, which will used maximum genetic
potential of variety in a separate area, and will
get stable yields and good quality.
Based on these findings, the aim of this study
was to investigate the potential of some new
national wheat varieties in the region of
Aleksinac. The goal was to investigate the
possibilities for breeding through field trials
and to obtain data on yield and quality. The
research is aimed at studying the productive
components for each genotype individually, as
well as the mutual comparison of the
genotypes tested in order to make
recommendations for growing varieties in
similar microclimate conditions.
Material and methods
Field trials were conducted during two years
(2009/10 and 2010/11), on the fields of JSC
"Selekcija" in Aleksinac - Serbia. Five
national soft wheat varieties such: Kruna and
Toplica developed in the Institute of cereals in
Kragujevac, and Zvezdana, Etida and
99 D. Cvetkovic, D. Boshev, Z. Dimov, S. Ivanovska, M. Jankulovska
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
Angelina from the Institute of Field and
Vegetable Crops in Novi Sad were used as
plant material.
Experiments were setup in a randomized block
system, in three replications of 5 m2, and the
planting is carried out with 550 seeds per m2.
The basic soil preparation was made with the
autumn plowing at a depth of 25 cm.Complex
fertilizer of 300 kg ha-1 of 15N2-15P2O5-
15K2O was applied before seeding and 150 kg
ha-1 of KAN (27 % N2) was used as top-
dressing fertilizer in both years. Inspring at the
end of the tillering stage, plants were treated
against weeds with herbicide Monosan Herba,
at a doseof 2 l ha-1. The plant-based
measurement of the number of productive
stems per m2, were made during the vegetation
season. During the research, also were
measured: length of spike, number of spikelets
per spike, number of grains per spike, grain
yield per hectare and hectoliter weight of
grain. The results of the test were statistically
processed by ANOVA method of analysis of
variance and compared with LSD test.
Results and discussion
Climatic and soil conditions
It is extremely important to know the climatic
conditions in a certain area as a essential factor
for successful production of certain wheat
varieties in a region (Vasilevski et al., 1992).
Each region is characterized by specific
conditions, which directly affect the yield and
quality of wheat (Hristov et al., 2011; Yanchev
et al., 2014).
Moderate continental climate dominates in the
area of Aleksinac. The springs are usually cold
and humid, summers are hot and dry, and
winters are often cold, with insufficient
quantities of snow.
According to the data on average monthly air
temperatures in the investigated years (Table
1), it may be noted that the warmest months
are July and August, with average
temperatures of 21.1 or 21.2 °C. The lowest
average monthly temperatures are registered in
January and February, with amount of 0.7 - 0.9
for the first, as well 1.1 °C for the second year.
The average annual temperature in the first
testing year was 10.6 °C and 11.7 °C in the
second year. Annual fluctuations in the
average monthly temperatures, suggest
existence of temperate continental climate in
the region.
Table 1. Average monthly and annual air temperatures (оС)
VIII IX X XI XII I II III IV V VI VII Av.
2009/10 21 16.8 11.2 6.9 1.5 0.7 0.9 4.7 10.4 14.8 18 20.8 10.6
2010/11 21.4 18 12.6 7.5 2.1 1.1 1.1 6.1 12 16 20.4 21.5 11.7
Average 21.2 17.4 11.9 7.2 1.8 0.9 1 5.4 11.2 15.4 19.2 21.1 11.1
Table 2. Monthly and annual amount of precipitation (mm)
VIII IX X XI XII I II III IV V VI VII Sum
2009/10 48 45 51 60 43 18 27 28 38 27 30 53 468
2010/11 36 39 57 54 58 41 52 49 56 61 55 47 605
Table 2 shows the values of precipitation per
month as well annual amount of rainfall.
According to the results of the first year,
highest amount of precipitation was recorded
in November (60 mm), and the lowest in
February and May (27 mm). In the second
year, the largest amount of rainfall was
registered in May (61 mm), and lowest in
August (36 mm). The total rainfall amount in
the second year is 605 mm which is higher
than the precipitation amount in the first year
(468 mm) for 137 mm. Also, it is noticeable
that, during the spring months (III, IV, V, and
VI) in the second year, there is more
precipitation in contrast to the first. Generally,
2010/11 has higher amounts of precipitation,
the schedule is good in both years of the
research, and there is a sufficient amount of
rainfalls in both years.
100 D. Cvetkovic, D. Boshev, Z. Dimov, S. Ivanovska, M. Jankulovska
____________________________________________________________________________________________________
JAFES, Vol 69, (2016)
Table 3. Mechanical compositionofthesoil (%)
Horizon Depth
(cm)
Skeleton
(<2)
Sand
(0,2 – 0,02)
Dust
(0,02 – 0,002)
Cley
(> 0,002)
I 0 – 30 9.5 31.6 35 23.9
Although wheat can be grown on different soil
types, she has positive reaction of rich soil
with good physical properties and pH of 6.8 to
7.2. The best soil types for wheat are humus,
alluvial and diluvia deposits (Filipovski,
1993). The soil where were placed
experimental plots, were alluvial sediments,
with first-class creditworthiness. The layout of
the mechanical structure to a depth of 30 cm is
equal, but below this depth, sharply growing
share of the soil skeleton (Table 3).
Grain yield
Wheat yield is quite variable and depends of
the capacity of the yield elements (Yanchev et
al., 2013). According to the analysis of
Jestorovic (1998), 97.9% of the total impact on
the yield belongs to external factors, while
only 2.1% of the genotype. Confirmation of
strong dependence of this property from
external influences, also attached Jevtic
(1992), which concluded that, the lack of
sufficient water in the period after the
fertilization of grains, results in reduced yield,
absolute and hectoliter mass of grain. Tsenov
et al., (2001) concluded that the yield and
quality of wheat depends on both the variety
and the agro-technique, which should be
correlated with climatic conditions. Hristov et
al,. (2012) examined 8 NS wheat varieties in
different agro-ecological conditions of
Vojvodina, in the period from 2005 to 2011.
They found that varieties Zvezdana and Etida
are characterized by high genetic potential for
yield than standard variety Pobeda, but yield
of these varieties is strongly influenced by
external conditions. On the other hand, the
variety Angelina showed slightly lower yield,
but higher yield stability.
Table 4. Grain yield (kgha-1)
Cultivar Year Average of cultivar
2009/10 2010/11
Kruna 5610 6100 5855
Toplica 4860 5240 5050
Zvezdana 6810 6907 6858
Etida 6650 6740 6695
Angelina 6187 6306 6246
Average of year 6023 6258 6140
Cultivar
LSD0,05 = 206
LSD0,01 = 282
Year
LSD0,05 = 130
LSD0,01 = 178
Interaction cultivar x year
LSD0,05 = 291
LSD0,01 = 399
All varieties exhibited relatively high yields
per hectare, regardless of the year (Table 4).
The general average yield was 6140 kg and the
average highest yield for both years had
variety Zvezdana (6858 kg) and lowest
Toplica (5050 kg). Variety Toplica had the
lowest yield in both years, in the first year it
was 4860 kg, and in the second 5240 kg. On
the other hand, the variety Zvezdana showed
the highest values in both years, which in 2010
stood at 6810 kg and in 2011, 6907 kg. Higher
amount of rain in the second year has
noticeably greater impact on some varieties.
Thus, varieties Zvezdana, Etida and Angelina,
exhibit no statistically significant differences.
Regarding this, it can be concluded that these
varieties are easily adaptable and have greater
tolerance to periods of less rainfall, unlike
varieties Kruna and Toplica. The data shows
strong and significant impact of the rainier
year on high statistical significant level at 99
%.
Analyzing the differences between varieties,
which includes the impact of the year, the
variety Zvezdana showed statistically
significant differences in yield on level of 99
% compared to Angelina, Toplica and Kruna,
while there are not significantly differences
from the variety Etida. Second positioned
variety in terms of yield, the variety Etida, also
shows statistically significant difference in the
yield level of 99 % significance compared to
101 D. Cvetkovic, D. Boshev, Z. Dimov, S. Ivanovska, M. Jankulovska
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JAFES, Vol 69, (2016)
Angelina, Toplica and Kruna. The yield of
Angelina showed differences at the level of 99
% significance compared to the yield of
Toplica, at level of 95 % compared to Kruna.
Kruna proved reliable statistical significant
difference at the level of 99 %, compared with
Toplica.
Number of productive stems
The number of productive stems is one of the
indicators of yield, because it is the number of
all stems with formed spike (Bokan and
Malesevic, 2004). In determination of the
optimal crop density, it is necessary to know
the potential of the variety for tillering and
accordingly to plant optimal agrotechnics
(Nedic, 1989). For high potential of wheat
varieties,t he number of productive stems
should be between 600 and 700 per m2, which
is accomplished by sowing 500-550 seeds per
m2 (Mastilovic, 1998).
Table 5. Number of productive stems (spikes per m2)
Cultivar Year Average of cultivar
2009/10 2010/11
Kruna 571 573 572
Toplica 612 600 606
Zvezdana 680 637 658
Etida 598 566 582
Angelina 609 674 641
Average of year 614 610 612
Cultivar
LSD0,05 = 23
LSD0,01 = 31
Year
LSD0,05 = 14
LSD0,01 = 20
Interaction cultivar x year
LSD0,05 = 32
LSD0,01 = 44
According to thedata, variety Kruna has
smallest amount of productive stems – 572,
and Angelina and Zvezdana higher, with an
average of 658 and 641, respectively. Yearly
average of all varieties showed that there were
not major differences, in both years
considering productive stems per m2 (Table 5).
Statistical analysis of interaction variety x
year,showed thegreatest coefficient of
differences, followed the differences between
the varieties and the impact of the year.
Spike length
The spike length varies depending of the
agrotechnique, rainfall in the region and
amounts of fertilizers, especially during the
formation of the spikes (tillering stage).
Roncevic (1998) studied the morphological
and productive characteristics of several
foreign varieties of wheat and received major
differences between varieties for this property.
Vasilevski (1980), in experiments with
different doses of fertilization, observed
differences in the length of the spikes for
certain varieties of winter wheat, regardless of
the method of fertilization, indicating that this
trait is inherited strictly under the same
growing conditions.
Table 6. Spike length (cm)
Cultivar Year Average of cultivar
2009/10 2010/11
Kruna 10.3 11 10.6
Toplica 10.1 9.5 9.8
Zvezdana 10.5 11.5 11
Etida 11.1 11.2 11.1
Angelina 11.9 12.9 12.4
Average of year 10.8 11.2 11
Cultivar
LSD0,05 = 0.5
LSD0,01 = 0.7
Year
LSD0,05 = 0.3
LSD0,01 = 0.4
Interaction cultivar x year
LSD0,05 = 0.7
LSD0,01 = 0.9
Average value of this feature was 11 cm
regardless of year and cultivar (Table 6). The
average of the first year was 10.8 cm, and the
second was higher by 0.4 cm, respectively
102 D. Cvetkovic, D. Boshev, Z. Dimov, S. Ivanovska, M. Jankulovska
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JAFES, Vol 69, (2016)
accounted for 11.2 cm. Statistical significance
compared to the year has been observed in all
cultivars, except for Etida, indicating that this
variety has good stability in terms of
cultivation. In individual analysis of the
varieties, the longest average length was
recorded for the variety Angelina (12.4 cm),
and the shortest in Toplica (9.8 cm). Angelina
showed statistically reliable differences at the
level of 99 % compared with other varieties in
both years. In the Etida variety, in the first
year is certainly received statistical deviation
level of 95 % compared with all other
varieties, while in the second year, only at
variety Toplica.
Number of spikelets per spike
The number of spikelets per spike is a direct
indicator of fertility of a particular variety, in
certain growing conditions. This component
depends on both the characteristics of the
variety and conditions of cultivation (Jevtic,
1986). According to Jestorovic (1998), the
number of spikelet in 83.5 % depends on the
influence of external factors, and in 16.5 % of
genotype variability. Vasilevski (1980)
concluded that the impact on the schedule of
precipitation is an important determinant of
the total amount of rainfall for the number of
spikelet per spike.
According to the results of our research, the
values correspond to previous studies (Table
7). The average number of spikelets per spike
for all varieties for both years was 19.4.
Angelina showed the highest (21.1) and Kruna
the lowest (17.9) value. Analyze of the impact
of interaction variety x year there are evident
statistical differences among all varieties
except between Zvezdana and Toplica. Among
the variety Kruna, the number was the lowest
in both years of the survey, while Angelina
and Etida had the highest number in the first
year (20.4) and Etida (21.8) in the second.
Differences due to the impact of the year as
well as the differences between varieties were
highly statistically significant at the level of 99
%.
Table 7. Number of spikelets per spike
Cultivar Year Average of cultivar
2009/10 2010/11
Kruna 17.3 18.4 17.9
Toplica 18.2 19.1 18.6
Zvezdana 18 19.6 18.8
Etida 20.4 20.9 20.6
Angelina 20.4 21.8 21.1
Average of year 18.9 20 19.4
Cultivar
LSD0,05 = 0.4
LSD0,01 = 0.5
Year
LSD0,05 = 0.2
LSD0,01 = 0.3
Interaction cultivar x year
LSD0,05 = 0.5
LSD0,01 = 0.7
Number of grains per spike
The number of wheat grains in the spike
largely depends on the genetic characteristics
of the variety, but also, extremely important
are climatic conditions during the formation of
spikelet.
Jestorovic (1998) finds that external factors
have affected 66.1 % of this capacity, and 33.9
% was due to the impact of genotype. In other
research, Vasilevski (1980) concluded that the
impact of the year on the average number of
grains is great. Nedic (1989) concluded no
influence of sowing density, to average
number of grains per spike varies in different
years of investigation.
104 D. Cvetkovic, D. Boshev, Z. Dimov, S. Ivanovska, M. Jankulovska
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JAFES, Vol 69, (2016)
Table 8. Number of grains per spike
Cultivar Year Average of cultivar
2009/10 2010/11
Kruna 50.6 56.1 53.3
Toplica 51.4 58.1 54.7
Zvezdana 48.5 54.4 51.4
Etida 59 50.7 54.8
Angelina 53.6 50 51.8
Average of year 52.6 53.9 53.2
Cultivar
LSD0,05 = 1.3
LSD0,01 = 1.7
Year
LSD0,05 = 0.8
LSD0,01 = 1.1
Interaction cultivar x year
LSD0,05 = 1.8
LSD0,01 = 2.4
The results in our research (Table 8), shows
that all varieties have well-developed spikes
with big number of grains per spike. The
highest average value for this property from
two years of research was obtained in cultivar
Etida (54.8), and lowest among the Zvezdana
(51.4). Seen by year, the lowest number of
grains in the first year of studies had variety
Zvezdana (48.5) and second year Angelina
(50). The largest number of grains in the first
year was found in variety Etida (59) and
second year in cultivar Toplica (58.1). A
comparison of average values for all varieties
of two years showed that in the second year,
varieties had larger number of grains in spike
(53.9) than in the first year (52.6). Statistically
significant differences in the number of grains
in spike exist between varieties and between
conditions of the year, which coincides with
previous similar studies.
Hectolitre grain weight
Hectolitre grain weight is one of the most
important parameters in assessing of milled
quality of the wheat. It is an indicator of two
thirds of the required qualitative-quantitative
properties of the grain, and parameter for
necessary capacity and equipment of storage
(Miric et al., 2007). In addition, hectoliter
grain weight is an indicator of biological
plasticity and adaptability of the variety in
different climate conditions, especially in high
temperatures and air drought. Mladenov and
Milosevic (2011) concluded that the
environmental conditions greatly affect
hectolitregrain weight. Mastilovic (1998),
determining the quality of wheat in Serbia
from 1995 to 1998, found differences of
hectoliter grain weight in the same variety in
different years.
In our investigations, hectolitre weight of grain
varied depending of the year and variety
(Table 9). Highest value is obtained in variety
Zvezdana (78.3 kg hl-1), and lowest in Toplica
(75.4 kg hl-1). The highest average weight in
the two years of the examination was obtained
in Zvezdana, which in 2010 amounted to 77.3
kg hl-1, and in 2011 to 79.3 kg hl-1. The
average for all varieties in the first year was
76.3 kg hl-1, in the second year 77.4 kg hl-1,
and the general average was 76.8 kg hl-1.
Table 9. Hectolitre grain weight (kg hl-1)
Cultivar Year Average of cultivar
2009/10 2010/11
Kruna 75.5 77.8 76.6
Toplica 76 74.9 75.4
Zvezdana 77.3 79.3 78.3
Etida 76.8 76.5 76.6
Angelina 76 78.4 77.2
Average of year 76.3 77.4 76.8
Cultivar
LSD0,05 = 1.5
LSD0,01 = 2
Year
LSD0,05 = 0.9
LSD0,01 = 1.3
Interaction cultivar x year
LSD0,05 = 2.1
LSD0,01 = 2.9
104 D. Cvetkovic, D. Boshev, Z. Dimov, S. Ivanovska, M. Jankulovska
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JAFES, Vol 69, (2016)
Conclusions
Based on the research results of five wheat
varieties in the region of Aleksinac we can
extract several conclusions.
Climate and soil conditions in the investigated
area are favorable for growing these varieties,
since without irrigation it was obtained
relatively high yields. Grain yield is the
highest among the variety Zvezdana, which
occurs as a result of the large number of grains
productive per unit area and number of grains
per spike. Variety Zvezdana has average yield
of 6858 kg ha-1. The variety Etida, also proved
very high yield, with an average of 6695 kg ha-
1. These results coincide with the results of
previous studies of these two varieties on the
territory of Vojvodina. The lowest average
yield was obtained in the variety Kruna, with
4902 kg ha-1. Number of productive stems is
confirmed as a cultivar trait. Highest number
was in the variety Zvezdana (658), and lowest
in Kruna (572). The longest spike is obtained
in Angelina (12.4 cm), and the shortest in
Toplica (9.8 cm). The highest number of
spikelet has Angelina (21.1) and lowest Kruna
(17.9), but the number of fertilized and shaped
grains showed the highest values among the
variety Etida (54.8), and lowest among
Zvezdana (51.4). Highest value for hectoliter
grain weight was obtained for varieties
Zvezdana (78.3 kg hl-1) and Angelina (77.2 kg
hl-1). As a final conclusion, it was found that,
although all tested varieties can be grown in
the region of Aleksinac, preference may be
given to varieties Zvezdana and Etida.
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