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奶牛乳房炎风险评估体系在中国荷斯坦牛群中的应用及优化 被引量:5

Application and Optimization of Dairy Cow Mastitis Risk Assessment System in Chinese Holstein
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摘要 为探究奶牛乳房炎风险评估体系的准确性和稳定性以及进一步的优化策略,本研究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),以与建模数据处于不同时间段的北京市6个牧场及浙江省1个牧场共73004头次泌乳牛的DHI信息作为验证数据,分别研究奶牛乳房炎风险评估体系在"多个牧场全年"、"多个牧场不同年份"及"同一牧场长时程"3种不同类型验证数据中的预测能力及优化应用策略。结果表明:CMLM在验证数据中仍然具备较高的区分度,其处理不同类型的中国北方牧场验证数据准确率和特异度较高,平均准确率为68.89%;同时CMLM在中国南方小群牧场的应用表现良好,平均准确率为77.64%;基于连续3个月预测结果可筛选出高患病风险奶牛,其下个月患临床乳房炎的概率高达99.11%,这种筛选策略为CMLM在中国荷斯坦牛群中应用的进一步优化提供了依据。综上,CMLM体系在中国荷斯坦牛群中的应用表现优异,具备全国推广的潜力。 The aim of this study is to explore the accuracy and stability of dairy cow mastitis risk assessment system and further optimization strategies.Based on Logistic regression model of dairy cow mastitis(Cow mastitis Logistic regression model,CMLM)that our group built.The DHI information of a total of 73004 lactating cows in six pastures in Beijing and one in Zhejiang was used as the validation data,which was collected in periods different from the training model.We studied the the prediction ability and optimization application strategy of risk assessment system for dairy cow mastitis in the following 3 different types of validation data,including multiple pastures during a year,multiple pastures during different years and one pasture during a long period.The results show that CMLM still has a good distinction in the validation data,the accuracy and specificity of validation data of different types of pastures in the north of China was higher,with an average accuracy of 68.89%.At the same time,the application of CMLM in small pastures in the south of China performed well,with an average accuracy of 77.64%.Cows with high risk of subclinical mastitis can be screened out based on the prediction results of three consecutive months and the probability of suffering from clinical mastitis in the next month is as high as 99.11%.This screening strategy provides a basis for further optimization of the application of CMLM in the Chinese Holstein herd.In conclusion,the application of CMLM system in Chinese Holstein performs well and has the potential for nationwide promotion and further optimization.
作者 李文龙 赵婷婷 达日格日乐 史良玉 郭刚 王雅春 肖炜 俞英 LI Wenlong;ZHAO Tingting;DA Rigerile;SHI Liangyu;Guo Gang;WANG Yachun;XIAO Wei;YU Ying(College of Animal Science and Technology,China Agricultural University,Beijing 100193,China;Beijing SunLonLivestock Development Co.,Ltd,Beijing 100076,China;Beijing Animal Husbandry Station,Beijing 100107,China)
出处 《中国畜牧杂志》 CAS 北大核心 2021年第10期65-72,共8页 Chinese Journal of Animal Science
基金 国家自然科学基金国际(地区)合作项目(31961143009) 北京首农畜牧发展有限公司自立科研课题申请书重点专项(SYZYZ20190003) 北京市奶牛产业创新团队(BAIC06) 北京市自然科学基金(6182021) 国家奶牛产业技术体系项目(CARS-36)。
关键词 乳房炎 风险评估 LOGISTIC回归模型 中国荷斯坦牛 DHI Mastitis Risk assessment Logistic regression model Chinese Holstein cattle DHI
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