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开发用于约克郡野猪使用累积料摄入量的料转换比率预测模型
Hao Zhou1, Haoshi Cheng1, Yuyang Wang1
1College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou 450046, China.
Animals : an open access journal from MDPI
|February 26, 2025
概括
预测猪料转换率 (FCR) 现在更加有效. 一个新的模型准确地估计了累计食摄入量 (CFI),减少了猪业的劳动力和成本.
科学领域:
- 动物科学动物科学
- 农业工程 农业工程
背景情况:
- 料转换率 (FCR) 对猪生产率至关重要,但很难衡量.
- 需要有效的FCR估计,以减少猪业的成本和劳动力.
研究的目的:
- 开发累计食摄入量 (CFI) 的预测模型,以估计FCR.
- 为了提高猪FCR测量的效率.
主要方法:
- 利用了987只约克郡野猪使用自动养器的数据.
- 使用细分R包和贝叶斯脊回归 (BRR) 开发了CFI的预测模型.
主要成果:
- 确定FCR预测的最佳体重范围为80-110公斤.
- 在CFI预测中,BRR模型实现了80%的准确性.
- 来自预测的CFI的FCR显示与更正的FCR相似度为81.4%.
结论:
- 即使数据有限,BRR模型也显示出FCR的强大预测潜力.
- 这种方法可以大大降低猪业的生产成本和测量时间.
- 结果支持减少FCR特征的选择压力,有利于猪生产.
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