Determination of gas flux of growing steers under intensive grazing conditions.

IF 1.3 Q3 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Translational Animal Science Pub Date : 2024-08-06 eCollection Date: 2024-01-01 DOI:10.1093/tas/txae119
Juan de J Vargas, Pedro H V Carvalho, Edward J Raynor, Edilane C Martins, Willian A Souza, Anna M Shadbolt, Kimberly R Stackhouse-Lawson, Sara E Place
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引用次数: 0

Abstract

Ruminants produce one-third of the anthropogenic methane (CH 4 ) emissions worldwide, and 47% of the CH4 emissions result from ruminants under grazing conditions. However, there is limited information regarding the appropriate number of visits to accurately determine enteric CH4 emissions using the automated head-chamber system (AHCS) from growing beef cattle under intensive grazing conditions. Data from one experiment were analyzed to determine the number of visits to assess gas flux (CH4, carbon dioxide [CO 2 ], and oxygen [O 2 ]) from Angus-crossbreed steers grazing in a pivot-irrigated improved pasture. A total of 110 steers (324 ± 37.3 kg initial body weight) were selected and divided into two blocks. Steers were under intensive grazing management for 84 d. Depending on forage availability, steers were rotated at 2- to 4-d intervals. Pastures were predominately composed of cool-season forages. Two different databases using the same animals (n = 16) were defined to calculate the gas flux using the first 100 visits to an AHCS with 2 or more or 3 or more minutes of visitation length. The mean gas flux was estimated as the average for increasing (forward) or decreasing (reverse) the gas flux of 5-visit intervals starting with the first or the last 5 visits and increasing or decreasing until the full 100-visit dataset was utilized, respectively. Spearman and Pearson correlations were computed between the maximum visits and each shortened visit interval. Concurrently, the residual variance and the residual variance change were determined for each interval by fitting a mixed model. The minimum number of visits was defined when correlations with the total visits were greater than 0.95, and the residual variance was stabilized. The results indicated that the minimum number of visits needed to determine CH4 production varied between 45 and 70, while CO2 production and O2 consumption varied between 45 and 50 according to the visitation length. Additionally, steers that visited the AHCS for 2 or more minutes in visit duration required a greater number of visits than those that visited for 3 or more minutes. Thus, based on the average daily visitation in this experiment (1.4 visit/d), the assessment of CH4 emissions requires 32 d, while CO2 production and O2 consumption require between 32 and 36 d using 3 or more minutes of visit length from growing steers under intensive grazing conditions.

测定密集放牧条件下生长母牛的气体通量。
反刍动物产生的甲烷(CH4)排放量占全球人为甲烷排放量的三分之一,而 47% 的 CH4 排放量来自放牧条件下的反刍动物。然而,关于在密集放牧条件下使用自动头腔系统 (AHCS) 准确测定生长肉牛肠道 CH4 排放量的适当访问次数的信息却很有限。我们分析了一项实验的数据,以确定评估在枢轴灌溉改良牧场放牧的安格斯杂交母牛的气体通量(甲烷、二氧化碳 [CO 2 ]和氧气 [O 2 ])的访问次数。共挑选了 110 头母牛(初始体重为 324 ± 37.3 千克),并将其分成两个区块。根据牧草供应情况,每隔 2 到 4 天轮换一次。牧场主要由冷季牧草组成。使用相同的动物(n = 16)定义了两个不同的数据库,利用前 100 次访问 AHCS(访问时间为 2 分钟或 2 分钟以上或 3 分钟或 3 分钟以上)来计算气体通量。平均气体通量的估算是,从第一次或最后一次5次探访开始,分别增加(正向)或减少(反向)5次探访间隔的气体通量,然后增加或减少,直到使用完整的100次探访数据集。计算了最大访问量与每个缩短的访问间隔之间的斯皮尔曼和皮尔逊相关性。同时,通过拟合混合模型确定了每个区间的残差和残差变化。当与总就诊次数的相关性大于 0.95 且残差稳定时,就确定了最小就诊次数。结果表明,根据访问时间的长短,确定 CH4 产量所需的最小访问次数在 45 到 70 次之间变化,而 CO2 产量和 O2 消耗量在 45 到 50 次之间变化。此外,访问 AHCS 2 分钟或更长时间的骏马比访问 3 分钟或更长时间的骏马需要更多的访问次数。因此,根据本实验中的日平均访问量(1.4 次/天),评估密集放牧条件下生长母牛的甲烷排放量需要 32 天,而二氧化碳产生量和氧气消耗量则需要 32 到 36 天,访问时间为 3 分钟或更长。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Translational Animal Science
Translational Animal Science Veterinary-Veterinary (all)
CiteScore
2.80
自引率
15.40%
发文量
149
审稿时长
8 weeks
期刊介绍: Translational Animal Science (TAS) is the first open access-open review animal science journal, encompassing a broad scope of research topics in animal science. TAS focuses on translating basic science to innovation, and validation of these innovations by various segments of the allied animal industry. Readers of TAS will typically represent education, industry, and government, including research, teaching, administration, extension, management, quality assurance, product development, and technical services. Those interested in TAS typically include animal breeders, economists, embryologists, engineers, food scientists, geneticists, microbiologists, nutritionists, veterinarians, physiologists, processors, public health professionals, and others with an interest in animal production and applied aspects of animal sciences.
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