Comparative study of ANN and conventional methods in forecasting first lactation milk yield in Murrah buffalo

VIJAY KUMAR; A K CHAKRAVARTY; ANKIT MAGOTRA; C S PATIL; P R SHIVAHRE

doi:10.56093/ijans.v89i11.95887

Authors

VIJAY KUMAR Assistant Professor, Department of Animal Genetics and Breeding, Pt. Deen Dayal Upadhyaya Veterinary University, Mathura, Uttar Pradesh
A K CHAKRAVARTY Retired Principal Scientist, ICAR-National Dairy Research Institute, Karnal, Haryana 132 001 India
ANKIT MAGOTRA Assistant Professor, ICAR-National Dairy Research Institute, Karnal, Haryana 132 001 India
C S PATIL Assistant Professor, ICAR-National Dairy Research Institute, Karnal, Haryana 132 001 India
P R SHIVAHRE Assistant Professor, Animal Husbandry and Dairying, Udai Pratap College, Varanasi, Uttar Pradesh

https://doi.org/10.56093/ijans.v89i11.95887

Keywords:

AIC, ANN, BIC, FL305DMY, MLR, Test-day milk yield

Abstract

Present investigation was undertaken to predict first lactation 305-day milk yield (FL305DMY) using monthly test day milk records. Under this study, multiple linear regression (MLR) and artificial neural network (ANN) approach were used. Effectiveness of both methods was also compared for prediction of FL305DMY in Murrah buffalo. The data on 3336 monthly test day milk yields records of first lactation pertaining to 556 Murrah buffaloes maintained at National Dairy Research Institute, Karnal; Central Institute for research on buffalo; Guru Angad Dev Veterinary and Animal Sciences University (GADVASU), Ludhiana and Choudhary Charan Singh Haryana Agricultural University (CCSHAU), Hisar were used in this study. In MLR study, it was observed that model 14 having four independent variable, i.e. FSP, TD2, TD4 and TD6 fulfilled most criteria such as highest R2, lowest MSE, lowest RMSE, lowest CP, lowest MAE, lowest MAPE, and lowest U value. In the present investigation, the accuracy of prediction obtained from ANN was almost similar to MLR for prediction of FL305DMY using monthly test day milk records in Murrah buffalo. The best ANN algorithm achieved 76.8% accuracy of prediction for optimum model, whereas the MLR explained 76.9% of accuracy of prediction of FL305DMY in Murrah buffalo. MLR method is simple as compared to ANN, hence MLR method could be preferred.

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