Principal component regression analysis in lifetime milk yield prediction of crossbred cattle strain Vrindavani of North India

T A KHAN; A K S TOMAR; TRIVENI DUTT; BHARAT BHUSHAN

doi:10.56093/ijans.v83i12.35805

Authors

T A KHAN Senior Scientist, Indian Veterinary Research Institute, Izatnagar, Uttar Pradesh 243 122 India
A K S TOMAR Principal Scientist, Indian Veterinary Research Institute, Izatnagar, Uttar Pradesh 243 122 India
TRIVENI DUTT Jt. Director, Indian Veterinary Research Institute, Izatnagar, Uttar Pradesh 243 122 India
BHARAT BHUSHAN Indian Veterinary Research Institute, Izatnagar, Uttar Pradesh 243 122 India

https://doi.org/10.56093/ijans.v83i12.35805

Keywords:

Vrindavani cattle, Lifetime milk production, Part lactation, Principal component regression analysis

Abstract

The study aims to devise most appropriate prediction model for lifetime milk production of Vrindavani, a crossbred cattle strain developed and maintained at Institute, based on principal components formulated on initially expressed part lactation records as predictors. Principal components (PCs) were derived on a data set pertaining to 10-year period (1999–2009). Part lactation records of 100, 170 and 240 days of first and second lactations and their respective total milk yields were used. Using principal component regression analysis (PCRA), the principal components were used as predictors for predicting lifetime milk yield as total milk yield up to 4 lactations (LTMY4), and up to 5 lactations (LTMY5). Eight types of model were fitted to identify the best fitted model for both the traits (LTMY4 and LTMY5) with the first principal component (PC_1) as a predictor. The equation LTMY4=4410.305+0.596PC_1-1.171PC_3 and LTMY5 = 7987.560– 2.301PC_3 explained 54.46% and 39.74% variation in the estimated values. The curve estimation analysis showing the appropriateness of power function was the most appropriate model for both the lifetime traits. The model LTMY4=32.609 (PC_1)0.671 was found best fit and explained 53.50% variation in estimation. In the other lifetime trait, model LTMY5==103.769 (PC_1)0.566, explained 38.40% variation in estimated values. These prediction equations may be helpful in selection at an early stage of Vrindavani cattle based on early part lactation records.

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