A data-driven approach to determine the minimum number of spot samples for estimating methane and carbon dioxide emissions from Austrian dairy cows on commercial farms using GreenFeed

Accurate estimation of methane (CH₄) and carbon dioxide (CO₂) emissions requires precise sampling methods due to the significant variability of these gases. This study, part of the project breed4green in Austria, investigated the variability of CH₄ and CO₂ and minimum number of spot samples required to accurately estimate CH₄ and CO₂ emissions from dairy cows on commercial farms. A total of 51,895 spot samples from 451 cows on 9 farms were analyzed, which were obtained using the GreenFeed system. Each farm participated in 2 GreenFeed measurement periods (Period 1 and 2), each lasting 6 wk and separated by 3 to 6 mo. A total of 298 cows, each with at least 70 spot samples in either Period 1 or Period 2, were analyzed to determine the minimum number of spot samples. Two methods were used. In the first, forward sampling, subsets of increasing spot samples (the first 1, 10, 20, 30, 40, 50, 60 and 70 measurements per cow) were compared with the complete set of available measurements for the cows. In the second method, random sampling, the same number of spot samples were selected randomly from all available visits for each cow and this procedure was repeated 100 times to account for sampling variability. The minimum number of spot samples required was determined when the Pearson correlation between the arithmetic mean of the subset and that of all available measurements reached a value of 0.90. Mean CH₄ and CO₂ emissions were 430 g/d and 13,309 g/d, respectively. The coefficient of variation (CV) for diurnal variability ranged from 4.6 to 12.0% for CH₄ and from 2.7 to 6.9% for CO₂, indicating low to moderate diurnal variability. Day-to-day variability was low, with CV between 3.7 and 8.7% for CH₄ and between 2.5 and 8.7% for CO₂. Substantial within-cow variation was observed for CH₄ (mean CV of 22.5%), while CO₂ was more stable (mean CV of 11.7%). When using forward sampling, at least 19 spot samples were required for accurate CH₄ estimates and only 13 for CO₂, with a mean of 6.5 and 4.3 d needed to obtain these measurements, respectively. When using random sampling, only 8 spot samples for CH₄ and 5 spot samples for CO₂ were sufficient to meet the accuracy criteria. For future analyses of this data set, we will rely on the results of forward sampling. Forward sampling is based on the actual sequence of visits made by each cow to the GreenFeed and therefore offers a more conservative and realistic approach compared with random sampling. Overall, the results highlight the dynamic nature of CH₄ emissions, which are influenced by factors such as feeding patterns and rumen fluctuations and suggest that more spot samples are needed for reliable estimates of CH₄ than for CO₂.