Determination of the Best Model to Predict Milk Dry Matter in High Milk Yielding Dairy Cattle

Abstract

This study was aimed to determinate the best model to predict milk dry matter in high milk yielding dairy cattle. Level of milk dry matter (MDM) (%) is of great importance. The material of this study consisted of 2208 milking records of dairy cattle yielding more than 40 l per day from Polish Holstein Friesian population. In this study to estimate the milk dry matter, regression of daily milk yield (MY) (l), milk urea (MU), milk protein (MP) (%) and milk fat (MF) (%) as explanatory variables were used. To estimate the best fitting, curve estimation was used. Estimation of the curves showed that milk urea was cubic, milk yield, milk protein and milk fat were quadratic. To avoid multicollinearity where VIF value greater than 10, stepwise variable selection procedure was used. After variable selection the regression equation was obtained as MDM=2.879+1.290*MF+2.395*MP-0.039*MF^2–0.225*MP^2 with 0.946 coefficient of determination. Our results showed that milk fat (%) and milk protein (%) can be used to estimate the milk dry matter (%) with a great achievement in high milk yielding dairy cattle.