Air Quality in San Diego County NACAA Fall Membership Meeting, 2007.
Shockey nacaa 2012
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Correlating nutritional values of grasses, legumes, and broadleaf weeds Shockey, W.L. 1 ; Rayburn, E.B. 2 ; Basden, T 3 ; Seymore, D.A. 4 ; Smith, B.D. 5 1 Extension Agent, West Virginia University, Kingwood, WV, 26537 2 Forage Extension Specialist, West Virginia University, Morgantown, WV, 26506 3 Nutrient Management Extension Specialist, West Virginia University, Morgantown, WV, 2650 4 Extension Agent, West Virginia University, Franklin, WV, 26807 5 Extension Agent, West Virginia University, Petersburg, WV, 26847 646 MATERIALS AND METHODS Sixteen pastures which were located on farms in several regions of WV were managed to measure effects of weather, fertilizer, and management strategies on a variety of parameters, including botanical composition of the swards. A series of samples was collected by clipping 1 foot square, randomly selected areas between May and November during a three-year period. After clipping, 40 samples were hand-separated according to botanical composition as grass (gra), legume (leg), and broadleaf weed (blw). Separated samples were sent to the analytical laboratories of Dairy One, Cornell, NY and analyzed for crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and total digestible nutrients (TDN) by Near Infrared Reflective (NIR) analysis. For each parameter, regressions between grasses and legumes and between grasses and broadleaf weeds were calculated by least squares regression techniques. RESULTS AND DISCUSSION Linear regressions between grass and legume or between grass and broadleaf weeds for each nutritional component are depicted in figures 1-4. Legumes contained higher concentrations of CP than both the grasses and broadleaf weeds (Figure 1). It was also noted that changes in the concentration of CP in the grasses were more closely related to changes in the broadleaf weeds compared to legumes. NDF was lower in both legumes and broadleaf weeds compared to grasses and were positively regressed (Figure 2). ADF levels were lower in legumes compared to grasses and broadleaf weeds (Figure 3). TDN was similar over the range measured among all the 3 classes of forage (Figure 4). This supports the concept of a similar energy value across all classes of forages with performance parameters being more closely related to intake than utilization. This observation is consistent with the results of Weiss, W.P. and Shockey, W.L. (1992. Orchardgrass can be a good forage for dairy cows. Hoard's Dairyman, 137(5) , p 204) who noted that the performance of lactating dairy cows was similar for cows consuming orchardgrass vs alfalfa because the NDF was more digestible in the grass compared to the legume. SUMMARY Linear regressions accounted for 33 to 66% of the variation (with a standard deviation about the regression of 2.7 to 5.3 units) in the nutritive components in legumes and broadleaf weeds by inputting the components in grass over the same range of re-growth. These results suggest implications for predicting animal performance based on the botanical components of pasture swards. A larger and more comprehensive database could improve the precision of regressions between botanical composition and animal performance and provide criteria for pasture managers to maximize forage utilization. ABSTRACT Most pastures contain grasses (gr), legumes (leg), and broadleaf weeds (blw). Each class of forage has unique nutritional characteristics both in terms of plant composition and animal utilization. In the Appalachian region, gr are the dominant forage species. The growth stage of most gr, which can give an indication of its nutritive value, is easily identified. Experiments were conducted to measure the correlation of nutritive components of gr compared to leg and blw at similar stages of re-growth. Sixteen pastures were sampled between May and November during a three-year period. After clipping, 40 samples were hand-separated according to botanical composition then analyzed for crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and total digestible nutrients (TDN). Correlations between gr and leg or between gr and blw for each parameter were CP leg = -0.09CP gr 2 + 3.31CP gr -6.88, R 2 = 0.52; CP blw = 1.10 CP gr + 0.19, R 2 = 0.66; NDF leg = 0.53NDF gr + 8.02, R 2 = 0.33; NDF blw = 0.67NDF gr + 2.83, R 2 = 0.33; ADF leg = 0.89ADF gr – 1.62, R 2 = 0.54; ADF blw = 0.75ADF gr + 7.16, R 2 = 0.52; TDN leg = 1.27TDN gr – 16.31, R 2 = 0.45; and TDN blw = 1.17TDN gr – 11.16, R 2 = 0.36. Thirty-three to 66% of the variation in the nutritive components in leg and blw was accounted for by measuring the measurements in gr at the same stage of re-growth. Results suggest implications for assessing the nutritive value of pasture swards by analysis of the gr only. INTRODUCTION Climatic conditions in West Virginia are good for forage growth, which can then be used as feed for ruminant livestock. Most pastures contain grasses, legumes, and broadleaf weeds as primary forage species. Each of these forage classes has unique nutritional characteristics both in terms of plant composition and animal utilization. In the Appalachian region of the United States grasses are the dominant forage species. The readily identifiable growth stage of grasses can give an indication of its nutritive value. To apply this principle to swards containing mixed classes of forage, experiments were conducted to measure the relationship between the nutritive components of grasses to legumes and broadleaf weeds at similar stages of re-growth. Development of a model that regresses nutritive components of different classes of forage at similar stages of re-growth for a given time and space may provide a way for ranchers and researchers to predict how the different classes of plants respond to the unique environmental conditions caused by their particular grazing management strategy. Figure 1 CP leg = 0.73CP gra + 11.40 R 2 = 0.44, SD reg = 2.8 CP blw = 1.10CP gra + 0.19 R 2 = 0.66, SD reg = 2.7 0 5 10 15 20 25 30 0 5 10 15 20 25 % CP, Leg or Blw % Crude Protein, Gra CP Leg Gra Blw Linear (Leg) Linear (Blw) Figure 2 NDF blw = 0.67NDF gra + 2.83 R 2 = 0.33, SD reg = 5.3 NDF leg = 0.53NDF gra + 8.02 R 2 = 0.33, SD reg = 4.2 0 10 20 30 40 50 60 70 30 40 50 60 70 % NDF, Leg or Blw % NDF, Gra NDF Leg Gra Blw Linear (Leg) Linear (Blw) Figure 3 ADF leg = 0.89ADF gra – 1.62 R 2 = 0.54, SD reg = 3.7 ADF blw = 0.75ADF gra + 7.16 R 2 = 0.52, SD reg = 3.3 0 5 10 15 20 25 30 35 40 45 10 20 30 40 50 % ADF, Leg or Blw % ADF, Gra ADF Leg Gra Blw Linear (Leg) Linear (Blw) Figure 4 TDN blw = 1.17TDN gra – 11.20 R 2 = 0.36, SD reg = 3.7 TDN leg = 1.20TDN gra – 12.50 R 2 = 0.45, SD reg = 3.2 40 45 50 55 60 65 70 75 55 60 65 70 % TDN, Leg or Blw % TDN, Gra TDN Leg Gra Blw Linear (Leg) Linear (Blw)
Transcript of Shockey nacaa 2012
Correlating nutritional values of grasses, legumes, and broadleaf weedsShockey, W.L.1; Rayburn, E.B.2; Basden, T3; Seymore, D.A.4; Smith, B.D.5
1Extension Agent, West Virginia University, Kingwood, WV, 265372Forage Extension Specialist, West Virginia University, Morgantown, WV, 26506
3Nutrient Management Extension Specialist, West Virginia University, Morgantown, WV, 26504Extension Agent, West Virginia University, Franklin, WV, 26807
5Extension Agent, West Virginia University, Petersburg, WV, 26847646
MATERIALS AND METHODS
Sixteen pastures which were located on farms in several regions of
WV were managed to measure effects of weather, fertilizer, and
management strategies on a variety of parameters, including
botanical composition of the swards. A series of samples was
collected by clipping 1 foot square, randomly selected areas
between May and November during a three-year period.
After clipping, 40 samples were hand-separated according to
botanical composition as grass (gra), legume (leg), and broadleaf
weed (blw). Separated samples were sent to the analytical
laboratories of Dairy One, Cornell, NY and analyzed for crude protein
(CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and
total digestible nutrients (TDN) by Near Infrared Reflective (NIR)
analysis.
For each parameter, regressions between grasses and legumes and
between grasses and broadleaf weeds were calculated by least
squares regression techniques.
RESULTS AND DISCUSSION
Linear regressions between grass and legume or between grass and broadleaf weeds for each nutritional component are depicted in figures 1-4.
Legumes contained higher concentrations of CP than both the grasses and broadleaf weeds (Figure 1). It was also noted that changes in the concentration of CP in the
grasses were more closely related to changes in the broadleaf weeds compared to legumes.
NDF was lower in both legumes and broadleaf weeds compared to grasses and were positively regressed (Figure 2). ADF levels were lower in legumes compared to grasses
and broadleaf weeds (Figure 3).
TDN was similar over the range measured among all the 3 classes of forage (Figure 4). This supports the concept of a similar energy value across all classes of forages with
performance parameters being more closely related to intake than utilization. This observation is consistent with the results of Weiss, W.P. and Shockey, W.L. (1992.
Orchardgrass can be a good forage for dairy cows. Hoard's Dairyman, 137(5) , p 204) who noted that the performance of lactating dairy cows was similar for cows
consuming orchardgrass vs alfalfa because the NDF was more digestible in the grass compared to the legume.
SUMMARY
Linear regressions accounted for 33 to 66% of the variation (with a standard
deviation about the regression of 2.7 to 5.3 units) in the nutritive components
in legumes and broadleaf weeds by inputting the components in grass over
the same range of re-growth. These results suggest implications for
predicting animal performance based on the botanical components of
pasture swards. A larger and more comprehensive database could improve
the precision of regressions between botanical composition and animal
performance and provide criteria for pasture managers to maximize forage
utilization.
ABSTRACT
Most pastures contain grasses (gr), legumes (leg), and
broadleaf weeds (blw). Each class of forage has unique
nutritional characteristics both in terms of plant
composition and animal utilization. In the Appalachian
region, gr are the dominant forage species. The growth
stage of most gr, which can give an indication of its
nutritive value, is easily identified. Experiments were
conducted to measure the correlation of nutritive
components of gr compared to leg and blw at similar
stages of re-growth. Sixteen pastures were sampled
between May and November during a three-year period.
After clipping, 40 samples were hand-separated
according to botanical composition then analyzed for
crude protein (CP), neutral detergent fiber (NDF), acid
detergent fiber (ADF), and total digestible nutrients
(TDN). Correlations between gr and leg or between gr
and blw for each parameter were
CPleg = -0.09CPgr2 + 3.31CPgr -6.88, R2 = 0.52;
CPblw = 1.10 CPgr + 0.19, R2 = 0.66;
NDFleg = 0.53NDFgr + 8.02, R2 = 0.33;
NDFblw = 0.67NDFgr + 2.83, R2 = 0.33;
ADFleg = 0.89ADFgr – 1.62, R2 = 0.54;
ADFblw = 0.75ADFgr + 7.16, R2 = 0.52;
TDNleg = 1.27TDNgr – 16.31, R2 = 0.45; and
TDNblw = 1.17TDNgr – 11.16, R2 = 0.36.
Thirty-three to 66% of the variation in the nutritive
components in leg and blw was accounted for by
measuring the measurements in gr at the same stage of
re-growth. Results suggest implications for assessing
the nutritive value of pasture swards by analysis of the
gr only.
INTRODUCTION
Climatic conditions in West Virginia are good for forage growth,
which can then be used as feed for ruminant livestock. Most
pastures contain grasses, legumes, and broadleaf weeds as primary
forage species. Each of these forage classes has unique nutritional
characteristics both in terms of plant composition and animal
utilization.
In the Appalachian region of the United States grasses are the
dominant forage species. The readily identifiable growth stage of
grasses can give an indication of its nutritive value. To apply this
principle to swards containing mixed classes of forage, experiments
were conducted to measure the relationship between the nutritive
components of grasses to legumes and broadleaf weeds at similar
stages of re-growth.
Development of a model that regresses nutritive components of
different classes of forage at similar stages of re-growth for a given
time and space may provide a way for ranchers and researchers to
predict how the different classes of plants respond to the unique
environmental conditions caused by their particular grazing
management strategy.Figure 1
CPleg = 0.73CPgra + 11.40R2 = 0.44, SDreg = 2.8
CPblw = 1.10CPgra + 0.19R2 = 0.66, SDreg = 2.7
0
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% C
P,
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g o
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% Crude Protein, Gra
CP
Leg
Gra
Blw
Linear (Leg)
Linear (Blw)
Figure 2
NDFblw = 0.67NDFgra + 2.83R2 = 0.33, SDreg = 5.3
NDFleg = 0.53NDFgra + 8.02R2 = 0.33, SDreg = 4.2
0
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% N
DF
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eg
or
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% NDF, Gra
NDF
Leg
Gra
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Linear (Leg)
Linear (Blw)
Figure 3
ADFleg = 0.89ADFgra – 1.62R2 = 0.54, SDreg = 3.7
ADFblw = 0.75ADFgra + 7.16R2 = 0.52, SDreg = 3.3
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% ADF, Gra
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Leg
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Linear (Leg)
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Figure 4
TDNblw = 1.17TDNgra – 11.20R2 = 0.36, SDreg = 3.7
TDNleg = 1.20TDNgra – 12.50R2 = 0.45, SDreg = 3.2
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% T
DN
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eg
or
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% TDN, Gra
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Linear (Leg)
Linear (Blw)
