Neural Network and Regression Based Model for Cows’ Milk Yield Prediction in Different Climatic Gradients
Bosede Oyegbile
Department of Animal Science, Ahmadu Bello University, Nigeria.
Oludayo Michael Akinsola *
Department of Theriogenology and Production, University of Jos, Nigeria.
Okeke Rufina Obioma
Department of Animal Science, Ahmadu Bello University, Nigeria.
Adekola Omololu Atanda
Department of Animal Science, Ahmadu Bello University, Nigeria.
Balami Samuel Paul
Department of Animal Science, Ahmadu Bello University, Nigeria.
Mary Foluke Oladipo
Department of Theriogenology and Production, University of Jos, Nigeria.
Zulfat Suleiman Abba
Department of Animal Science, University of Maiduguri, Borno State, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
The present study was designed to develop the prediction equations for 305 days fat corrected milk yield on the basis of part periods milk yield, milk component and conformation traits of multi-genotype cows. Artificial Neural Network model had the best prediction accuracy across varying environments, though Genetic Function Algorithm had the overall best adequacy for fat corrected milk yield predictions (FCM305d=1036.1-98.3RP+22FY+15.92UC-0.07RUH; Adj R2=0.997; RMSE=30.07; BIC=1997.28).
Keywords: Prediction, artificial neural network, genetic function algorithm, multi-genotype cows