Method for predicting dry matter digestion rate and metabolic energy of grass
A technology of dry matter and digestibility, which is applied in the direction of measuring devices, instruments, scientific instruments, etc., can solve problems such as prediction methods of digestibility and metabolic energy of different forages that have not been proposed, and achieve an optimized prediction model, simple and convenient operation, and high accuracy high effect
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Embodiment 1
[0027] Select 10 kinds of leguminous forages, and measure their crude protein CP (%), crude fat EE (%), neutral detergent fiber NDF (%), acid detergent fiber ADF (%), calcium Ca (%), phosphorus P ( %) content, total energy GE (MJ / kg) content. And use the same material to carry out animal digestion and metabolism test, measure its dry matter digestibility DMD (%) and metabolizable energy ME (MJ / kg). Through multiple linear regression analysis, the regression coefficient was obtained, so as to obtain the prediction equation of dry matter digestibility DMD and metabolizable energy ME (Table 1, Table 2).
[0028] Table 1 Regression analysis for prediction of dry matter digestibility based on nutrient composition (leguminous forages)
[0029]
[0030] Table 2 Predictive regression analysis of metabolizable energy based on nutrient components (legumes)
[0031]
[0032]
[0033] Among the 10 groups of data on the dry matter digestibility of leguminous forages, the relativ...
Embodiment 2
[0036] Select 10 kinds of gramineous forages, and measure their crude protein CP (%), crude fat EE (%), neutral detergent fiber NDF (%), acid detergent fiber ADF (%), calcium Ca (%), phosphorus P ( %) content, total energy GE (MJ / kg) content. And use the same material to carry out animal digestion and metabolism test, measure its dry matter digestibility DMD (%) and metabolizable energy ME (MJ / kg). Through multiple linear regression analysis, the regression coefficients were obtained, so as to obtain the prediction equations of dry matter digestibility DMD and metabolizable energy ME (Table 3, Table 4).
[0037] Table 3 Predictive regression analysis of dry matter digestibility based on nutrient composition (grasses)
[0038]
[0039] Table 4 Predictive regression analysis of metabolizable energy based on nutrient components (grasses)
[0040]
[0041]
[0042] Among the 10 groups of data on the dry matter digestibility of gramineous grasses, the relative error betw...
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