Effect of animal and diet parameters on methane emissions for pasture-fed cattle

IF 1.4 4区 农林科学 Q2 Agricultural and Biological Sciences
Stefan Muetzel, Rina Hannaford, Arjan Jonker
{"title":"Effect of animal and diet parameters on methane emissions for pasture-fed cattle","authors":"Stefan Muetzel, Rina Hannaford, Arjan Jonker","doi":"10.1071/an23049","DOIUrl":null,"url":null,"abstract":"<strong> Context</strong><p>Estimates of enteric methane emissions for agricultural emissions trading schemes or national inventories can be a simple single emission factor, but the accuracy of the predictions may be affected by other diet- and animal-related parameters.</p><strong> Aims</strong><p>Determine the animal and dietary factors that affect methane yield (methane per unit of dry-matter intake) in pasture-fed cattle.</p><strong> Methods</strong><p>Methane emissions and dry-matter intake (DMI) of cattle of various ages and in different physiological stages that were fed different-quality fresh-cut pastures were quantified in respiration chambers. The animals used in the various trials were post-weaned calves, heifers and steers of various ages and some older lactating dairy cows. Diet quality of the pastures offered was determined using near-infrared spectroscopy. Mixed linear modelling was used to assess the impacts of animal and diet parameters on methane emissions.</p><strong> Key results</strong><p>Our results indicated that diet quality does not have a major effect on methane production. For individual composition parameters, the correlation (Pearson’s <i>r</i>) with methane production was less than 0.25. Only estimates of metabolisable energy (ME) content showed a higher correlation (<i>r</i> = 0.43). However, despite this correlation, ME, like the other diet composition variables, was not a useful parameter to predict daily methane production, as indicated by the Akaike’s information criterion (AICc). Including data on concentrate supplementation at a level of 30% of the DMI did not improve the prediction of methane production. The resulting model indicated that besides DMI, bodyweight, physiological state and sex significantly affected methane production. Methane production was mostly explained by DMI. This was illustrated by the observation that when methane production is expressed per kilogram DMI (methane yield, g kg<sup>−1</sup> DMI) none of the diet or animal related characteristics showed a significant correlation with methane yield. The model performed well, but needs to be validated with an independent dataset.</p><strong> Conclusions</strong><p>For ryegrass-based pasture dry-matter intake is the single most important factor that affects methane yield, while pasture composition has no effect and animal-related factors such as physiological stage and age only appear to modulate methane emissions.</p><strong> Implications</strong><p>Our findings have implications for methane accounting and national inventories in pastoral agricultural systems, which account for the majority of ruminant production systems.</p>","PeriodicalId":7895,"journal":{"name":"Animal Production Science","volume":"12 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Animal Production Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1071/an23049","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0

Abstract

Context

Estimates of enteric methane emissions for agricultural emissions trading schemes or national inventories can be a simple single emission factor, but the accuracy of the predictions may be affected by other diet- and animal-related parameters.

Aims

Determine the animal and dietary factors that affect methane yield (methane per unit of dry-matter intake) in pasture-fed cattle.

Methods

Methane emissions and dry-matter intake (DMI) of cattle of various ages and in different physiological stages that were fed different-quality fresh-cut pastures were quantified in respiration chambers. The animals used in the various trials were post-weaned calves, heifers and steers of various ages and some older lactating dairy cows. Diet quality of the pastures offered was determined using near-infrared spectroscopy. Mixed linear modelling was used to assess the impacts of animal and diet parameters on methane emissions.

Key results

Our results indicated that diet quality does not have a major effect on methane production. For individual composition parameters, the correlation (Pearson’s r) with methane production was less than 0.25. Only estimates of metabolisable energy (ME) content showed a higher correlation (r = 0.43). However, despite this correlation, ME, like the other diet composition variables, was not a useful parameter to predict daily methane production, as indicated by the Akaike’s information criterion (AICc). Including data on concentrate supplementation at a level of 30% of the DMI did not improve the prediction of methane production. The resulting model indicated that besides DMI, bodyweight, physiological state and sex significantly affected methane production. Methane production was mostly explained by DMI. This was illustrated by the observation that when methane production is expressed per kilogram DMI (methane yield, g kg−1 DMI) none of the diet or animal related characteristics showed a significant correlation with methane yield. The model performed well, but needs to be validated with an independent dataset.

Conclusions

For ryegrass-based pasture dry-matter intake is the single most important factor that affects methane yield, while pasture composition has no effect and animal-related factors such as physiological stage and age only appear to modulate methane emissions.

Implications

Our findings have implications for methane accounting and national inventories in pastoral agricultural systems, which account for the majority of ruminant production systems.

动物和日粮参数对牧草喂养牛甲烷排放的影响
背景用于农业排放交易计划或国家清单的肠道甲烷排放量估计可以是一个简单的单一排放因子,但预测的准确性可能会受到其他日粮和动物相关参数的影响。目的确定影响牧草喂养牛甲烷产量(单位干物质摄入量的甲烷)的动物和日粮因素。方法在呼吸室中对饲喂不同质量鲜切牧草的不同年龄和不同生理阶段的牛的甲烷排放量和干物质摄入量(DMI)进行量化。各种试验中使用的动物是断奶后的小牛、不同年龄的小母牛和小公牛以及一些年龄较大的泌乳奶牛。使用近红外光谱测定了所提供牧草的日粮质量。采用混合线性模型评估动物和日粮参数对甲烷排放的影响。主要结果我们的研究结果表明,日粮质量对甲烷产量的影响不大。单个成分参数与甲烷产量的相关性(Pearson's r)小于 0.25。只有代谢能(ME)含量的估计值显示出较高的相关性(r = 0.43)。然而,尽管存在这种相关性,但从 Akaike 信息标准(AICc)来看,ME 和其他日粮组成变量一样,并不是预测日甲烷产量的有用参数。将精料补充量(DMI 的 30%)纳入模型也不能提高甲烷产量的预测效果。由此得出的模型表明,除 DMI 外,体重、生理状态和性别对甲烷产量也有显著影响。甲烷产量主要由 DMI 解释。当甲烷产量以每公斤 DMI 表示时(甲烷产量,克/公斤-1 DMI),日粮或动物相关特征均未显示出与甲烷产量的显著相关性。该模型表现良好,但需要用独立数据集进行验证。结论对于以黑麦草为主的牧草来说,干物质摄入量是影响甲烷产量的最重要因素,而牧草成分没有影响,动物相关因素(如生理阶段和年龄)似乎只调节甲烷排放量。启示我们的发现对占反刍动物生产系统大多数的牧业系统的甲烷核算和国家清单具有启示意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Animal Production Science
Animal Production Science Agricultural and Biological Sciences-Food Science
CiteScore
3.00
自引率
7.10%
发文量
139
审稿时长
3-8 weeks
期刊介绍: Research papers in Animal Production Science focus on improving livestock and food production, and on the social and economic issues that influence primary producers. The journal (formerly known as Australian Journal of Experimental Agriculture) is predominantly concerned with domesticated animals (beef cattle, dairy cows, sheep, pigs, goats and poultry); however, contributions on horses and wild animals may be published where relevant. Animal Production Science is published with the endorsement of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) and the Australian Academy of Science.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信