所有生产部门活动的温室气体排放目前是一个最重要的议题。畜牧业的主要贡献者是反刍动物,尤其是奶牛。这项研究旨在评估和比较21种预测肠道甲烷排放(EME)的公式,基于牛奶性状和脂肪酸谱,从通过文献综述检索的46个中选择。我们编制了详细脂肪酸谱的参考数据库,由GC测定,在4种不同的乳制品管理系统下,来自85个牧群的992头泌乳奶牛。根据DIM对奶牛进行分类,奇偶校验顺序,乳品系统。该数据库是我们使用选定方程估计EME的基础。估计的EME性状为甲烷产量(20.63±2.26g/kg的MI,7个方程),甲烷强度(16.05±2.76克/千克校正牛奶,4个方程),和日甲烷产量(385.4±68.2g/d,10个方程)。甲烷产量也通过将每日校正的牛奶产量乘以甲烷强度(416.6±134.7g/d,4方程)。我们还测试了DIM的效果,奇偶校验,和乳制品系统(作为校正因子)的估计值。总的来说,我们观察到从不同方程获得的EME估计之间几乎没有一致性,除了从不同研究中心的一系列数据的荟萃分析中获得的数据。我们发现所有EME预测都受到统计模型中包含的变异源的高度影响:DIM显着影响了21个方程中的19个的结果,和奇偶校验顺序影响了13的结果。对于不同的方程,观察到不同的模式,其中只有一些符合基于奶牛生理的预期。最后,当将产奶量的测量值包括在公式中时,或者当根据每日产奶量和甲烷强度间接计算估计值时,可以获得每日甲烷产量的最佳预测.
Greenhouse gas emission from the activities of all productive sectors is currently a topic of foremost importance. The major contributors in the livestock sector are ruminants, especially dairy cows. This study aimed to evaluate and compare 21 equations for predicting enteric
methane emissions (EME) developed on the basis of milk traits and fatty acid profiles, which were selected from 46 retrieved through a literature
review. We compiled a reference database of the detailed fatty acid profiles, determined by GC, of 992 lactating cows from 85 herds under 4 different dairy management systems. The cows were classified according to DIM, parity order, and dairy system. This database was the basis on which we estimated EME using the selected equations. The EME traits estimated were
methane yield (20.63 ± 2.26 g/kg DMI, 7 equations),
methane intensity (16.05 ± 2.76 g/kg of corrected milk, 4 equations), and daily
methane production (385.4 ± 68.2 g/d, 10 equations). Methane production was also indirectly calculated by multiplying the daily corrected milk yield by the
methane intensity (416.6 ± 134.7 g/d, 4 equations). We also tested for the effects of DIM, parity, and dairy system (as a correction factor) on the estimates. In general, we observed little consistency among the EME estimates obtained from the different equations, with exception of those obtained from meta-analyses of a range of data from different research centers. We found all the EME predictions to be highly affected by the sources of variation included in the statistical model: DIM significantly affected the results of 19 of the 21 equations, and parity order influenced the results of 13. Different patterns were observed for different equations with only some of them in accordance with expectations based on the cow\'s physiology. Finally, the best predictions of daily methane production were obtained when a measure of milk yield was included in the equation or when the estimate was indirectly calculated from daily milk yield and methane intensity.