Studies on lactation curve models in murrah buffaloes at organized herd.
Loading...
Date
2020
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana
Abstract
In the present study, the data were collected on the production traits of Murrah buffaloes up to fourth parity for the period of 25 years (1991-2015) maintained at Directorate of Livestock Farm, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana. The data used in present studies pertained to 5,17,293 daily milk yield records pertaining to 1524 lactations of 644 Murrah buffaloes sired by 213 bulls. The effect of non-genetic factors viz; period of calving, season of calving, age at first calving and parity on production traits were found significant and subsequently data were corrected to study the comparative fit of various lactation curve models to describe the shape of lactation curve and to develop a suitable lactation curve model for Murrah buffaloes. The period of calving showed highly significant effect (P<0.01) on 305-day milk yield, complete lactation milk yield, lactation length and peak yield. The season of calving had highly significant effect (P<0.01) on peak yield, lactation length and service period. The age at first calving had significant effect (P<0.05) only for peak yield. The parity had highly significant effect (P<0.01) on 305-day milk yield, complete lactation milk yield, lactation length and peak yield 305-day milk yield, complete lactation milk yield, lactation length and peak yield. The daily milk yields were used to develop the best lactation curve models for the lactation 305-day as well as 455-day milk yield in Murrah buffalo using four models viz. Gamma Function (GF), Exponential Function (EF), Polynomial Regression Function (PRF) and Mixed Log Function (MLF). The adjusted R2 values of Gamma Function (GF), Exponential Function (EF), Polynomial Regression Function (PRF) and Mixed Log Function (MLF) were 99.72%, 97.99%, 99.89% and 98.82%; whereas the average root mean squares error with these functions were 0.010%, 0.028%, 0.006% and 0.022%, respectively for 305-day milk yield and the adjusted R2 values of Gamma Function (GF), Exponential Function (EF), Polynomial Regression Function (PRF) and Mixed Log Function (MLF) were 98.10%, 96.80%, 99.50% and 99.10%; whereas the average root mean squares error with these functions were 0.041%, 0.053%, 0.020% and 0.028%, respectively for 455-day milk yield. Thus, the best fit model was Polynomial Regression Function, which was better than other functions for prediction of lactation in Murrah buffaloes for 305-day milk yield as well as 455-day milk yield, because PRF had higher R2 value and lower RMSE value for both 305-day milk yield as well as 455-day milk yield. The new developed model resembled Polynomial Regression Function for 305-day milk yield except that it incorporates a new variable into the equation as square root of the day of lactation and it showed better fit than all four earlier models considered in the study for 455-day milk yield, as it had 1.5% higher (99.65%) Adj. R2 and lower (0.017%) RMSE value by 0.003% to Polynomial Regression Function. The modelling of lactation curve can be used for early selection/culling of animals.