预测传统奶系统的农场的乳牛群的弹性
Roxann S C Rikkers1, Bart J Ducro1, Rianne van Binsbergen1
1Wageningen University & Research, Animal Breeding & Genomics, Wageningen, The Netherlands.
The Journal of dairy research
|September 11, 2023
概括
一种新的方法可以预测没有自动化奶制系统 (AMS) 的农场的奶牛群的弹性. 这种方法使用共同的农场数据来评估群体的健康和管理,改进性战略.
科学领域:
- 动物科学动物科学
- 乳制品管理 乳制品管理
- 兽医流行病学 兽医流行病学
背景情况:
- 估计群体的弹性对于奶牛场的可持续性至关重要.
- 现有的方法依赖于来自自动化奶制系统 (AMS) 的个别奶牛数据,但不包括传统奶制系统 (CMS) 的农场.
- 需要一种适用于CMS农场的弹性预测方法.
研究的目的:
- 开发和验证一种方法,以使用常规奶系统 (CMS) 农场常见的数据来预测牲畜的弹性.
- 确定关键的农场级指标,预测群体的弹性.
- 能够采取主动的管理决策,以提高奶牛群的弹性.
主要方法:
- 利用了来自585个荷兰AMS农场的数据,预先进行了群体弹性估计.
- 开发了一种5倍交叉验证的随机森林模型,使用通常在CMS农场上可用的群体性能数据.
- 将模型推导的弹性估计与基于AMS的估计进行比较.
主要成果:
- 通过使用CMS可用的数据,成功预测了69.9%的概率高于或低于平均群体弹性.
- 确定了乳皮酸性疾病的奶牛比例,体细胞数量增加和群体大小波动作为关键预测因素.
- 证明了群体管理影响了弹性.
结论:
- 通过使用常规奶制系统农场的易于获得的数据,可以有效地预测群体的弹性.
- 关键指标,如乳头酸性,体细胞计数和群体大小变异性,对于评估弹性至关重要.
- 这种预测能力使农民能够实施有针对性的管理变化,以提高整体群体的弹性.
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