使用生物识别分析估计克里奥尔山羊的体重
Fritz Trillo-Zárate1,2, Miguel Enrique Paredes-Chocce1, Jorge Salinas1
1Dirección de Servicios Estratégicos Agrarios, Instituto Nacional de Innovación Agraria (INIA), Lima, Perú.
Open veterinary journal
|November 7, 2025
概括
支持向量回归 (SVR) 准确地使用生物识别数据预测克里奥尔山羊的体重. 这有助于更好地管理牲畜,提高秘鲁农村地区的粮食安全.
科学领域:
- 动物科学动物科学
- 农业技术 农业技术
背景情况:
- 克里奥尔山羊养殖对于秘鲁农村的粮食安全至关重要,提供牛奶和肉.
- 准确估计体重 (BW) 对于在畜牧业中选择繁殖牲畜至关重要.
研究的目的:
- 为了比较使用克里奥尔山羊数据挖掘算法的体重预测模型.
- 根据生物识别测量评估不同算法的有效性.
主要方法:
- 利用了1075只1-4岁的雌性克里奥尔山羊的数据.
- 收集的生物识别测量包括胸部宽度,胸围,高度,部尺寸,身体长度和炮骨周围.
- 应用回归树 (CART),支持向量回归 (SVR) 和随机森林回归 (RFR) 算法.
主要成果:
- 支持向量回归 (SVR) 在预测克里奥尔山羊群体体重方面表现出卓越的表现.
- 在训练 (R2 = 0.765) 和测试 (R2 = 0.707) 期间证实了SVR模型的稳定性.
- 随机森林回归 (RFR) 与训练数据显示出更高的准确性 (R2 = 0.942).
结论:
- 开发的预测模型显示了使用生物识别数据准确预测体重的巨大潜力.
- 这些模型可以提高克里奥尔山羊的选择,养和卫生管理.
- 改进的管理实践有助于提高牲畜生产率和粮食安全.
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