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Updated: May 16, 2025

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基于料摄入量,体重,牛奶产量和组成的哺乳母牛的甲排放预测模型:基于可变甲转换因子的方法

Kohei Oikawa¹, Fuminori Terada², Mitsunori Kurihara³

¹Institute of Livestock and Grassland Science, NARO, Nasushiobara, Tochigi, Japan; Graduate School of Agricultural Science, Tohoku University, Sendai, Miyagi, Japan.

Journal of dairy science

|May 14, 2025

概括

这项研究开发了新的模型,使用可变CH4转换因子 (Ym) 方法预测甲 (CH4) 排放. 这些模型准确地预测了与牛奶生产水平无偏差的CH4排放量.

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:

对畜牧业的甲 (CH4) 排放的准确预测对于环境管理至关重要.
现有的CH4预测模型通常依赖于恒定的CH4转换因子 (Ym),这可能会引入偏差.
了解Ym和动物因素之间的关系是改善排放预测的关键.

研究的目的:

开发CH4排放预测模型,使用变量Ym的方法,将Ym与体重 (BW),牛奶产量 (MY) 和牛奶成分联系起来.
评估这些变量Ym模型的预测性能与常量Ym模型相比.
评估与牛奶生产水平相关的预测偏差.

主要方法:

开发了使用线性混合模型和通用线性混合模型的模型,使用266条记录的数据集.
纳入的变量如干物质摄入量 (DMI),总能量摄入量 (GEI),BW,MY,牛奶脂肪 (MFAT) 和牛奶蛋白 (MPROT).
通过k-fold交叉验证评估模型的准确性,精度和偏差.

主要成果:

性能最好的 Ym 模型的变量是:CH4 排放 (MJ/d) = exp(-2.74 + 0.000325 × BW - 0.00883 × MY + 0.116 × MFAT - 0.142 × MPROT) × GEI,其 R2 为 0.30.
在这项研究中开发的变量Ym模型没有显示与牛奶生产水平相关的显著偏差.
现有的基于Ym的模型对生产水平表现出了相当大的偏差.

结论:

基于变量Ym的模型提供了改进的CH4排放预测,特别是通过消除与牛奶生产水平相关的偏差.
虽然由BW,MY和牛奶成分解释的Ym的差异很小,但变量Ym的方法是有利的.
拟议的建模方法可以帮助在没有料数据的情况下开发国家特定的 Ym 模型.

关键词:

一般化的线性模型.在库存库存库存库存库存库存.模型开发模型的发展.在生产水平的生产水平上.

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