摘要 : The scope of this study was to develop lifetime milk yield (LTMY) prediction equation using different economical traits. The traits used were first lactation length, first peak yield, first lactation total milk yield, and total of... 展开 The scope of this study was to develop lifetime milk yield (LTMY) prediction equation using different economical traits. The traits used were first lactation length, first peak yield, first lactation total milk yield, and total of three lactation milk yield of 1210 Holstein Friesian crossbred dairy cattle in India. Four variants of feed-forward back propagation algorithms were compared with the multiple linear regression model. The performance of Bayesian regularization (BR) algorithm was found to be better than the other algorithms for LTMY prediction. The BR neural network model was able to predict milk yield with 71.18% R-2. 收起