Prediction of first lactation 305-days lactation milk yield from peak yield and test day milk yields in crossbred cattle

NISHA SHARMA; RAMAN NARANG; POONAM RATWAN; NEERAJ KASHYAP; SONI KUMARI; SIMARJEET KAUR; VARINDER RAINA

doi:10.56093/ijans.v89i2.87340

Authors

NISHA SHARMA PhD Scholar, Animal Genetics and Breeding Division, ICAR-National Dairy Research Institute, Karnal, Haryana
RAMAN NARANG Associate Professor, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab 141 004 India
POONAM RATWAN Scientist, Department of Animal Genetics and Breeding, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar
NEERAJ KASHYAP Assistant Professor, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab 141 004 India
SONI KUMARI PhD Scholar, ICAR-Indian Veterinary Research Institute, Izatnagar, Uttar Pradesh.
SIMARJEET KAUR Assistant Animal Geneticist, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab 141 004 India
VARINDER RAINA PhD Scholar, Animal Genetics and Breeding Division, ICAR-National Dairy Research Institute, Karnal, Haryana

https://doi.org/10.56093/ijans.v89i2.87340

Keywords:

HF Ã— Sahiwal, Peak yield, Prediction of milk yield, Test day

Abstract

Lactation yield (LY) of dairy animals have high relationship with peak yield and test day milk yield. The present study was carried out for prediction of 305 days lactation yield based on peak yield and test day milk yield. Data on 384 first lactation test day milk yield records of crossbred cattle maintained at GADVASU dairy farm over a period of 25 years from 1991â€“2015 were utilized for the study. Test day milk records were taken at 30 days interval. The simple regression analysis using peak yield (PY) revealed that peak yield alone could predict the lactation yield with 47% accuracy. Prediction of LY based on TDY125, TDY155 and TDY185 would be quite useful and reliable with 66.8%, 70.4% and 75.1% accuracy, respectively. The multiple regression equation indicated that R2 values showed increasing trend when more number of test day milk yields were included in prediction. The best suggested equation was LY = -121.674 + 80.58 PY + 5.477 TDY155 + 14.097 TDY185 with 86.3% accuracy. Prediction equations derived through step-wise regression for predicting the 305-days milk yield from monthly test-day milk yields showed that the average error and residual mean sum of squares continuously declined in prediction of 305- days milk yield with the increase in number of variables up to six, however there was no use of increasing the variables beyond five. It was concluded that the third, sixth and ninth test-day milk yield should be pooled for prediction of the 305-days milk yield with accuracy of 91.94% in crossbred cattle.

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