Comparative study of three prediction models in predicting the milk yields of Yunnan Holstein cows

ZHIYONG CAO; XIUJUAN YANG; XIZHANG XIZHANG; WEIHUANG WEIHUANG; LINLI TAO; BIN DENG; CHENCHEN CHENCHEN; ZHAOCHENG SUN

doi:10.56093/ijans.v90i7.106681

Authors

ZHIYONG CAO Yunnan Agricultural University, Kunming 650 201 China
XIUJUAN YANG Yunnan Agricultural University, Kunming 650 201 China
XIZHANG XIZHANG Yunnan Agricultural University, Kunming 650 201 China
WEIHUANG WEIHUANG Yunnan Agricultural University, Kunming 650 201 China
LINLI TAO Yunnan Agricultural University, Kunming 650 201 China
BIN DENG Yunnan Agricultural University, Kunming 650 201 China
CHENCHEN CHENCHEN Yunnan Agricultural University, Kunming 650 201 China
ZHAOCHENG SUN Yunnan Agricultural University, Kunming 650 201 China

https://doi.org/10.56093/ijans.v90i7.106681

Keywords:

BPNN model, Milk yield prediction, Quadrinomial model, Wood model

Abstract

The polynomial model and wood model have been extensively applied to predict the milk yield of cows, which aims to measure and partially explain the uncertainty under single factor condition. However, different sample data would affect the goodness of fit of the models. To investigate the milk yield regularities of the Chinese Holstein cows in Yunnan Standardized Pasture (YSP), data of cows with 1–3 parities using different observation periods were derived from the 401,497 records of 1,826 cows collected from YSP, and fitted in the BP neural network (BPNN) model, the Quadrinomial model and the Wood model. Prediction results of three models were compared. The results show that, for group data (mean), the Quadrinomial model was likely to over-fit under the single factor condition with small sample data, while the Wood model had a better goodness of fit; the BPNN model was more suitable for multi-factor and large sample data analysis.

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