Factors influencing greenhouse gas measurements in beef cattle: Understanding GreenFeed results.

The environmental impact of the livestock industry, particularly concerning greenhouse gas (GHG) emissions, has become a growing concern. Addressing this challenge requires accurate and efficient measurement methods for monitoring and mitigating gas emissions. One noteworthy method is the GreenFeed (GF), developed by C-Lock Inc., designed to measure methane (CH4 ) emissions and carbon dioxide (CO2 ) concentrations in ruminants through a real-time non-invasive monitoring device with reduced labor intensity and a high level of precision. The GF is the most used equipment to measure GHG in cattle; however, there is still considerable variability that is not explained due to the variation among animals. Thus, the objective of this work is to analyze other environmental factors influencing GF measurements in cattle to explain the variability observed. For this, a total of 127 yearling Angus steers were evaluated for GHG emissions through 6 GF units placed in 6 different pastures (n = 21 to 22 animals/pasture). Animals were evaluated from June to August (2023) at the South Dakota State University Cottonwood Field Station (Cottonwood, SD). The mean values of GHG evaluated were 174g CH4 /d and 5,885 g CO2 /d, showing a coefficient of variation (CV%) of 41% and 27%, respectively. To evaluate GHG variation, we used ANOVA type III (package car in R) for the following variables measured by the GF: temperature, wind speed, wind direction, variance influenced by the GF unit by itself, and animal factors as the number of visits and the duration per visit. Table 1 shows the percentage of variance explained by all these factors on the variation of CH4 and CO2 ; betweenanimal variation (13 and 15.5%), the GF unit (7.2 and 6.3%), duration of visits (2.7 and 2.8%), wind speed (1.7 and 1.3%), temperature (1.3 and 0.0%), wind direction (0.1 and 0.1%) and number of visits (0.3 and 0.0%). The residual error of the model represented 73.7% for CH4 and 73.9% for CO2, indicating the vast percentage of non-explained variance in these two gases, which, in this case, could be associated with different grazing systems or stocking density of animals in the different pastures. Results of this study demonstrate how other factors, non-related to the animal or the type of feed, may contribute to explaining the variation observed in CH4 and CO2 emissions. In future experiments, these factors should be considered to improve the accuracy of measurements and establish smaller differences between groups/individuals. [ABSTRACT FROM AUTHOR]