关键词: 奶牛, 中红外光谱, 甲烷排放, 预测模型

Abstract:

The emission of greenhouse gases not only leads to global warming and changes in the climate system but also may cause damage to the ozone layer, thereby exacerbating the greenhouse effect. Although the total emissions of methane gas are not as high as carbon dioxide gas, and its residence time in the atmosphere is relatively short, it possesses a higher global warming potential, making it a highly threatening greenhouse gas. Livestock farming is a major source of anthropogenic methane gas emissions, with the methane emissions from cows accounting for nearly one-fifth of the total proportion. Given this context, the measurement of individual cow methane emissions becomes crucial. Understanding the methane emissions produced by each cow can help identify cows with high emissions and implement more targeted measures to reduce emissions. Therefore, there is a need for convenient high-throughput technologies for measuring cow methane emissions. Traditional methane measurement techniques, such as respiration chambers and sulfur hexafluoride gas tracing technology, are time-consuming, labor-intensive, and costly, which hinders the monitoring of methane emissions on a large scale for individual cows. Using a combination of cow trait indicators to predict the methane emission characteristics of cows is a feasible alternative method. Numerous methane prediction equations based on factors, such as cow energy intake, dry matter intake, and daily feed composition, have been developed. However, these prediction factors are also challenging to collect on commercial farms, limiting the feasibility of these equations for large-scale applications. Considering that mid-infrared spectroscopic information of cow milk can be obtained in bulk and at low cost from routine cow production performance assessments, foreign researchers have been exploring the feasibility of predicting cow methane emissions based on mid-infrared spectroscopic information from cow milk over the past decade. It has been confirmed that using mid-infrared spectroscopy to predict cow methane emissions is feasible, biologically plausible, and moderately accurate. However, the researchers in this area have not yet begun in China. This paper elaborated on the current research status of predicting cow methane emissions using mid-infrared spectroscopic information from cow milk and emphasized the key points and challenges that need to be addressed in future research. It summarized the different strategies adopted by various studies in terms of cow methane emission measurement indicators, methane phenotype observation value determination methods, mid-infrared spectroscopy data collection, modeling methods, and validation strategies, aiming to provide insights for Chinese researchers conducting related studies.

Key words: dairy cattle, mid infrared spectroscopy, methane emissions, prediction model