Rumen volatile fatty acid prediction method, system, equipment and medium
A technology of volatile fatty acids and prediction methods, which is applied in health index calculation, medical informatics, informatics, etc., can solve the problems of lagging adjustment of feeding management measures, high test intensity, and high input of manpower and material resources, so as to avoid the risk of invalid tests, The effect of improving research efficiency
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[0054]Example 1
[0055]Literature search and data screening
[0056]The literature search uses databases such as China HowNet to screen relevant literature data for the past 10 years. The acceptance criteria are: the experimental animals are dairy cows, beef cattle, sheep and goats; the literature reports the composition and nutritional components of the diet (additives, RDS, peNDF, etc.); the experimental indicators are the rumen fermentation parameters (pH, TVFA content, molar ratio of VFA, propylene acetate Acid ratio). The RDS in the diet is based on the reported value in the literature. If the data is not reported in the article, use the CPM-Dairy software to estimate these parameters. A total of 55 articles and 78 sets of valid data were obtained.
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[0057]Example 2
[0058]Stepwise regression analysis modeling
[0059]Using stepwise regression analysis, stepwise regression calculations were performed on the 9 indicators of diet formula and animal information and the corresponding 10 rumen fermentation parameter indicators, and the equations and determination coefficients related to 10 rumen fermentation parameter indicators were obtained respectively (Table 1). R2max=0.50, which does not meet the modeling requirements.
[0060]Table 1 Coefficients of independent variables and coefficients of determination of the stepwise regression model
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[0062]Example 3
[0063]Partial Least Squares Regression Analysis Modeling
[0064]Partial least squares regression analysis was used to perform regression operations on the 9 indicators of diet formula and animal information and the corresponding 10 rumen fermentation parameter indicators, and the equations and determination coefficients related to the 10 rumen fermentation parameter indicators were obtained respectively (Table 2) , Where R2max=0.54, which does not meet the modeling requirements.
[0065]Table 2 Partial Least Squares Regression Model Independent Variable Coefficients and Coefficient of Determination
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