7-Title: Identifying best predictive model for weekly test day milk yield using lactation curve models in Murrah buffaloes
Authors: Sumit Kumar, Vijay Kumar and AK Chakravarty
Source: Ruminant Science (2014)-3(2):163-169
How to cite this manuscript: Kumar Sumit, Kumar Vijay and Chakravarty AK (2014). Identifying best predictive model for weekly test day milk yield using lactation curve models in Murrah buffaloes. Ruminant Science 3(2):163-169.
The adjusted weekly test day milk yields were used to develop three parameters models i.e. Inverse quadratic polynomial function (IQPF), exponential function (EF), mixed log function ( MLF) and the five parameters model polynomial regression function (PRF) by estimating lactation curve parameters for first three and pooled lactations up to second and third parity. Out of four models, the best model was identified for predicting weekly test day milk yield of different lactations on the basis of accuracy of prediction (R2) and the root mean sum of square (RMSE). Among the 3-parameters lactation curve models MLF was found best for predicting weekly test day milk yield (WTDMY) (R2=99.48to 99.73%) in different lactations. The 5-parameters model i.e. PRF was the best model for predicting WTDMY with the predicted error for unadjusted and adjusted WTDMY was 30, 70, 180, 80 gm in first three and pooled lactation. PRF could be used for predicting WTDMY of Murrah buffaloes both in organized herd and under field conditions. The combination of second, fourth & fifth; third, fourth & fifth and second, third & fifth MTDMY were found best for prediction of first, second and third TLMY (R2=60.19, 58.19 and 60.28 per cent) with the corresponding error ranged from 13.71 per cent.
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