对印度牛的肠道甲排放的评估和预测模型的开发
S Alam1, E Schlecht2, C A Bateki2
1Animal Husbandry in the Tropics and Subtropics, University of Kassel and Georg-August-Universität Göttingen, 37213 Witzenhausen, Germany; Department of Dairy and Poultry Science, Hajee Mohammad Danesh Science and Technology University, Dinajpur-5200, Bangladesh.
Journal of dairy science
|January 25, 2026
概括
准确预测印度牛的肠道甲 (EntCH4) 排放对于减缓气候变化至关重要. 一种新的线性混合效应模型显著提高了印度乳牛和非乳牛的EntCH4预测准确度.
科学领域:
- 农业科学 农业科学
- 环境科学 环境科学
- 动物科学动物科学
背景情况:
- 印度的动物通过肠道甲 (EntCH4) 排放,对全球变暖做出了重大贡献.
- 准确的EntCH4排放估计对于评估减排策略至关重要,但在规模上直接测量是不切实际的.
- 现有的EntCH4预测模型通常对印度多样化的牛群体缺乏准确性.
研究的目的:
- 评估现有的EntCH4预测模型对印度牛的准确性.
- 开发一种新的,更准确的模型来预测印度奶牛和非奶牛的EntCH4排放.
主要方法:
- 通过使用独立的数据集,评估了六个现有的EntCH4预测模型 (IPCC_DMI,IPCC_GEI,Ribeiro_DMI,Ribeiro_GEI,Patra_DMI,Patra_GEI).
- 开发了一种使用线性混合效应框架的新型实证 EntCH4 预测模型.
- 使用相对预测误差 (RPE) 和平均偏差误差 (MBE) 评估模型准确性,RPE <20%被认为是可以接受的.
主要成果:
- 六个评估模型中没有一个准确预测了非奶牛的EntCH4排放 (RPE <20%).
- 在Ribeiro_DMI和Patra_DMI模型中,乳牛的RPE分别为22.6%和22.9%.
- 新开发的线性混合效应模型 (阿拉姆模型) 在乳牛和非乳牛中实现了9.48%的显著较低的RPE.
结论:
- 现有的EntCH4模型不足以预测印度非奶牛的排放.
- 新的线性混合效应模型为乳制品和非乳制品印度牛的EntCH4预测提供了卓越的准确性.
- 该模型为评估减缓策略和了解印度EntCH4排放提供了有价值的工具.
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