2026-10-14T15:55:04Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33951361 2026-09-21T15:35:36Z category_30563 portal_1059 item_type_3 month_year_09_2026

Gas flux determination and prediction of methane emissions in yearling steers under grazing conditions Juan Vargas (330452) Eduardo Paula (20384676) Justin Derner (5013590) R. Mark Enns (6790082) Ines Mesa (25081888) Ashley Schilling-Hazlett (25081891) Mesa Kutz (25081894) Larry Kuehn (5337956) Melissa Johnston (17484567) John Ritten (25081897) Nathan Delay (25081900) Logan Thompson (2891930) Leticia Campos (25081903) Anna Shadbolt (25081906) Leonardo Sitorski (25081909) Edward Raynor (25081912) Pedro Carvalho (8173641) Kimberly Stackhouse-Lawson (25081915) Sara Place (25081918) Agricultural, veterinary and food sciences enteric methane gas flux Grazing improved pastures semiarid rangelands Bos taurus accuracy concordance correlation coefficient precision modeling Animal and dairy science <p>The use of an automated head chamber system (AHCS) for determining methane (CH₄) emissions in ruminants has increased in recent years; however, assessments of emissions from cattle in grazing systems remain limited, constrained by a lack of knowledge regarding the minimum number of AHC visits needed for gas flux measurements. Additionally, appropriate CH₄ determination allows for the evaluation of existing models for predicting CH₄ emissions from cattle under grazing conditions. This study aimed to determine the minimum number of AHCS visits to determine gas flux and to evaluate the sensitivity of retrieved equations for estimating enteric CH₄ emissions in yearling steers under grazing conditions. Individual gas flux from a total of 141 yearling cross-bred steers (398 ± 53.0 kg of body weight [BW]) that visited the AHCS at least 100 times under grazing was included in the analysis. Gas flux variables for each steer were estimated by increasing 5-visit intervals until the full 100-visit dataset was utilized. Residual variance, Pearson correlation, and Spearman rank correlation were calculated to determine the minimum number of AHCS visits to determine gas flux compared to the total 100-visit dataset. Then, 31 retrieved equations to estimate CH₄ production were evaluated according to the individual CH₄ emission from 154 yearling steers (394 ± 54.1 kg BW), using root mean square prediction error (RMSPE) and concordance correlation coefficient (CCC) analysis. Steers required at least 55 visits to ACHS to represent gas flux emissions under grazing conditions compared to the mean gas flux of 100 visits, resulting in Spearman and Pearson coefficient correlations greater than 0.95. In addition, four equations for predicting CH₄ emissions had excellent agreement (i.e., RMSPE ranged between 15.6 and 19.0 g/d and CCC ranged between 0.83 and 0.86) with individual CH₄ production, using the 55-visit average of CH₄ production. In the evaluated grazing environments, yearling steers required at least 55 visits to represent the gas flux, using the ACHS. In this analysis, four equations had excellent agreement between predicted and observed CH₄ emissions in the evaluated yearling steers under grazing conditions.</p> 2026-09-01T00:00:00Z Dataset Dataset 10.5061/dryad.dbrv15fg8 https://figshare.com/articles/dataset/Gas_flux_determination_and_prediction_of_methane_emissions_in_yearling_steers_under_grazing_conditions/33951361 CC0