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• W4306989185 abstract "Rumen methanogenesis results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits. Methane and carbon dioxide (CO2) data recorded via multiple GreenFeed Emission Monitoring (GEM), systems as well as feed intake, live weight, ultrasound scanning data, and slaughter data were available on 1,099 animals destined for beef production, of which 648 were steers, 361 were heifers, and 90 were bulls. Phenotypic relationships between GEM emission measurements with feed intake, weight traits, muscle ultrasound data, and carcass traits were estimated. Utilization of GEM systems, daily patterns of methane output, and repeatability of GEM system measurements across averaging periods were also assessed. Methane concentrations varied with visit number, duration, and time of day of visit to the GEM system. Mean CH4 and CO2 varied between sex, with mean CH4 of 256.1 g/day ± 64.23 for steers, 234.7 g/day ± 59.46 for heifers, and 156.9 g/day ± 55.98 for young bulls. A 10-d average period of GEM system measurements were required for steers and heifers to achieve a minimum repeatability of 0.60; however, higher levels of repeatability were observed in animals that attended the GEM system more frequently. In contrast, CO2 emissions reached repeatability estimates >0.6 for steers and heifers in all averaging periods greater than 2-d, suggesting that cattle have a moderately consistent CO2 emission pattern across time periods. Animals with heavier bodyweights were observed to have higher levels of CH4 (correlation = 0.30) and CO2 production (correlation = 0.61), and when assessing direct methane, higher levels of dry matter intake were associated with higher methane output (correlation = 0.31). Results suggest that reducing CH4 can have a negative impact on growth and body composition of cattle. Methane ratio traits, such as methane yield and intensity were also evaluated, and while easy to understand and compare across populations, ratio traits are undesirable in animal breeding, due to the unpredictable level of response. Methane adjusted for dry matter intake and liveweight (Residual CH4) should be considered as an alternative emission trait when selecting for reduced emissions within breeding goals.Methane production from cattle digestion results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits of economic importance. Methane and carbon dioxide emissions recorded using Greenfeed systems were available on a total of 1,099 animals. In addition, performance indicators such as feed intake, live weight, ultrasound scanning data, and slaughter data were also available on all animals. Phenotypic repeatability of CH4 ranged from 0.13 to 0.74, with a CH4 repeatability of >0.6 achieved by both heifers and steers in 10-d measuring period. Due to the high repeatability of CH4 measures, an accurate portrayal of CH4 production can be observed from a 10-d measuring period when measures are averaged. Methane emission data were positively correlated with traits of economic importance. Phenotypically, animals with heavier body weights and greater feed intake had higher emissions." @default.
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• W4306989185 date "2022-10-21" @default.
• W4306989185 modified "2023-09-27" @default.
• W4306989185 title "Phenotypic relationship and repeatability of methane emissions and performance traits in beef cattle using a GreenFeed system" @default.
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• W4306989185 doi "https://doi.org/10.1093/jas/skac349" @default.
• W4306989185 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36268991" @default.
• W4306989185 hasPublicationYear "2022" @default.
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