首页> 外文期刊>Indian Journal of Animal Research >Screening of animals for subclinical mastitis: A discriminate function analysis
【24h】

Screening of animals for subclinical mastitis: A discriminate function analysis

机译:亚临床乳腺炎的动物筛选:辨别函数分析

获取原文
获取原文并翻译 | 示例
           

摘要

The study was aimed to construct a discriminate model to differentiate health status of the udder in dairy lactating Holstein cows. Though SCC is a single most reliable indicator of mastitis, a fine demarcation line to differentiate the healthy and subclinical animals based on SCC, rarely exist. The model included contributory factors such as log_SCC, stage of lactation, rainy season, stall hygiene score, udder hygiene score and milking method constructed and was found to demonstrate 89.2 per cent accuracy with p<0.001 and the Holstein functions at group centroids are -0.982 and 1.209 respectively for normal and mastitis infected animals. The model will facilitate 92.3 per cent of the cases to correctly classify for non-mastitis normal animals and 85.3 per cent to predict correctly as mastitis.
机译:该研究旨在构建一个区分模型,以区分乳制乳酸荷斯坦奶牛的乳房的健康状况。 虽然SCC是乳腺炎最可靠的指标,但很少存在细微分界线,以区分基于SCC的健康和亚临床动物。 该模型包括Log_scc,哺乳期,雨季,摊位卫生评分,乳房卫生评分和挤奶方法等贡献因素,并发现了用P <0.001的精度证明了89.2%,并且组质心的Holstein功能是-0.982 和1.209分别用于正常和乳腺炎受感染的动物。 该模型将有助于92.3%的病例,正确分类为非乳腺炎正常动物,85.3%以预测为乳腺炎。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号