Bayesian approach for evaluation of lactation curve in cross bred cattle based on monthly and bimonthly test day milk yield

Abstract

In eld progeny testing program milk recording at monthly or bimonthly intervals and prediction of rst lactation 305-day milk yield (FL305DMY) from these test day yields have been adapted as an alternative to daily milk recording. Wood's incomplete gamma function is the one of the commonly used nonlinear lactation curve model. In recent years Bayesian approach of tting nonlinear biological models is gaining attention among researchers. In this study Wood's incomplete gamma function was tted using Bayesian approach using monthly (MTDY) and bimonthly test day (BTDY) yields. The lactation curve parameters thus obtained were used for prediction of FL305DMY. E ciency of prediction based on monthly and bimonthly test day milk yield were compared using error of prediction. It was found to be 5.78% and 7.59% as root mean square error (RMSE) values based on MTDY and BTDY respectively .The Breeding values of 97 Karan Fries sires were estimated using BLUP-AM based on actual and predicted FL305DMY so obtained. The RMSE was calculated as the difference between estimated breeding values based on actual and predicted yield. It was found that RMSE value calculated based on MTDY showed only a marginal superiority of 0.79% over BTDY and showed high degree of correlation with actual yield. So, recording at bimonthly intervals could be an economical alternative without compromising the e ciency.