奶牛乳房炎风险评估体系在中国南北方奶牛场的验证及应用

doi:10.16431/j.cnki.1671-7236.2023.08.024

摘要/Abstract

摘要： 【目的】探究奶牛乳房炎风险评估体系在中国南北方奶牛场近年来实际应用的准确性和稳定性,观察该体系是否可以稳定应用于中国荷斯坦牛群奶牛乳房炎的预测。【方法】基于课题组已构建的奶牛乳房炎Logistic回归模型(cow mastitis logistic regression model,CMLM),在北京、河南、浙江6个荷斯坦牛场进行大规模横向、纵向数据验证,以北方地区5个荷斯坦牛场(覆盖北京、河南)以及南方地区1个荷斯坦牛场(浙江)共56 985头次泌乳牛的奶牛群体改良(dairy herd improvement,DHI)信息作为验证数据,验证奶牛乳房炎风险评估体系的预测能力;利用北方地区2016―2021年27万余条DHI测定记录,检验CMLM在整体不同时间段下的大规模纵向数据验证效果。【结果】CMLM在北京地区荷斯坦牛群的验证数据集中,平均准确率为71.85%,表现较优且稳定;在新加入的河南大群奶牛场的验证数据集中也有较好的实际应用表现,平均准确率为78.67%。CMLM在中国南方小群奶牛场长达180个月的验证数据集中应用表现稳定,平均准确率为77.63%。CMLM在不同时间阶段均具有较高的预测效力,模型的预测价值集中在0.70~0.90之间,可以认为该模型良好。【结论】CMLM体系在中国南北方荷斯坦牛群中应用表现优异,在大规模横向、纵向数据的验证中也有较高的预测效力,具有较高推广应用价值。

关键词: 中国荷斯坦牛; 乳房炎; 风险评估; Logistic回归模型; 模型验证

Abstract: 【Objective】 The aim of this study was to explore the accuracy and stability of dairy cow mastitis risk assessment system in pastures in North and South of China in recent years,and observe whether the system could be stably applied to predict mastitis of Chinese Holstein dairy.【Method】 Based on Logistic regression model of dairy cow mastitis (cow mastitis logistic regression model,CMLM) by the author’s research group had built,large scale horizontal and vertical data validation was conducted in 6 Holstein dairy farms in Beijing,Henan and Zhejiang.The dairy herd improvement (DHI) information of a total of 56 985 lactating dairy cows in 5 Holstein dairy farms in Northern region (Beijing and Henan) and 1 Holstein dairy farm in Southern region (Zhejiang) was used as the validation data.The prediction ability of risk assessment system for dairy cow mastitis was tested.More than 270 thousand DHI measurement records of pastures in Northern China from 2016 to 2021 were used to test the validation effect of CMLM on large scale vertical data in different time periods.【Result】 CMLM had a good accuracy in the validation data of pastures in Beijing,with an average accuracy of 71.85%.CMLM had a great actual application performance in the validation data of pastures in Henan which was new,with an average accuracy of 78.67%.CMLM had a stable actual application performance in the validation data of small-scale pasture in Southern region for 180 months,with an average accuracy of 77.63%.CMLM also had high predictive power at different time stages.The predictive value of the model was concentrated 0.70-0.90.It could be considered that CMLM was good.【Conclusion】 The CMLM system had excellent performance in the application of Holstein dairy herds in South and North of China,and had a high predictive effect in the verification of large scale horizontal and vertical data,which had a good promotion and application value.

Key words: Chinese Holstein dairy; mastitis; risk assessment; Logistic regression model; model validation

中图分类号:

S857.2⁺6

白云飞, 赵婷婷, 李文龙, 邢悦, 任小丽, 郭刚, 俞英. 奶牛乳房炎风险评估体系在中国南北方奶牛场的验证及应用[J]. 中国畜牧兽医, 2023, 50(8): 3267-3274.

BAI Yunfei, ZHAO Tingting, LI Wenlong, XING Yue, REN Xiaoli, GUO Gang, YU Ying. Verification and Application of Dairy Cow Mastitis Risk Assessment System in Pastures in North and South of China[J]. China Animal Husbandry and Veterinary Medicine, 2023, 50(8): 3267-3274.

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