区分分析作为一种工具,用于分类奶牛农场的农场干草
Aldo Dal Prà1,2, Riccardo Bozzi3, Silvia Parrini3
1Centro Ricerche Produzioni Animali-Soc. Cons. p. A., Reggio Emilia, Italy.
PloS one
|November 28, 2023
概括
区分分析成功地使用视觉检查和NIRS数据区分了花草类型. 这种方法有助于分类未知的干草样本,改善反动物料质量评估.
科学领域:
- 农业科学 农业科学
- 动物营养 动物营养
- 数据分析 数据分析
背景情况:
- 干草对于反动物的料至关重要,需要有效的质量评估方法.
- 目前的评估结合了视觉检查和近红外光谱学 (NIRS).
- 准确的干草分类对于优化动物营养和料管理至关重要.
研究的目的:
- 开发一种用于区分和分类干草类型的补充方法.
- 评估区分分析 (DAPC) 在干草分类中的有效性.
- 为了提高干草质量评估的准确性,超越传统的NIRS分析.
主要方法:
- 分析了来自意大利北部的1639个干草样本 (2016-2021年).
- 在基于视觉和NIRS数据的五种不同的花草类型上应用差别分析 (DAPC).
- 评估两个场景:完整的数据集培训和交叉验证分配概率.
主要成果:
- DAPC模型实现了66%的总体分配成功率.
- 纯 (PUA) 的成功率高达84%,料混合物 (FOM) 的成功率高达79%.
- 在交叉验证中,PUA,PRA和PEM显示了对特定群体的高度分配概率,表明了良好的差异化.
结论:
- 区分分析 (DAPC) 是区分干草类型的可行方法.
- 这种方法补充了NIRS分析,以改善干草质量评估.
- DAPC可以用来分类未知的干草样本,并可能评估其他质量因素.
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