Exploring indicators of genetic selection using the sniffer method to reduce methane emissions from Holstein cows.

OBJECTIVE: This study aimed to evaluate whether the methane (CH4) to carbon dioxide (CO2) ratio (CH4/CO2) and methane-related traits obtained by the sniffer method can be used as indicators for genetic selection of Holstein cows with lower CH4 emissions. METHODS: The sniffer method was used to simultaneously measure the concentrations of CH4 and CO2 during milking in each milking box of the automatic milking system to obtain CH4/CO2. Methane-related traits, which included CH4 emissions, CH4 per energy-corrected milk, methane conversion factor (MCF), and residual CH4, were calculated. First, we investigated the impact of the model with and without body weight (BW) on the lactation stage and parity for predicting methane-related traits using a first on-farm dataset (Farm 1; 400 records for 74 Holstein cows). Second, we estimated the genetic parameters for CH4/CO2 and methane-related traits using a second on-farm dataset (Farm 2; 520 records for 182 Holstein cows). Third, we compared the repeatability and environmental effects on these traits in both farm datasets. RESULTS: The data from Farm 1 revealed that MCF can be reliably evaluated during the lactation stage and parity, even when BW is excluded from the model. Farm 2 data revealed low heritability and moderate repeatability for CH4/CO2 (0.12 and 0.46, respectively) and MCF (0.13 and 0.38, respectively). In addition, the estimated genetic correlation of milk yield with CH4/CO2 was low (0.07) and that with MCF was moderate (-0.53). The on-farm data indicated that CH4/CO2 and MCF could be evaluated consistently during the lactation stage and parity with moderate repeatability on both farms. CONCLUSION: This study demonstrated the on-farm applicability of the sniffer method for selecting cows with low CH4 emissions.

Rumen microbial composition associated with the non-glucogenic to glucogenic short-chain fatty acids ratio in Holstein cows.

This study aimed to determine the physiological features and rumen microbial composition associated with the non-glucogenic-to-glucogenic short-chain fatty acids ratio (NGR). Holstein cows were housed in a free-stall barn with an automatic milking system and fed a partially mixed ration. Physiological and microbial analyses were performed on 66 datasets collected from 66 cows (50-250 days in milk). NGR was positively correlated with ruminal pH, relative abundances of protozoa and fungi, methane conversion factor, methane intensity, plasma lipids, parity, and milk fat, and negatively correlated with total short-chain fatty acids. To highlight the differences in bacterial and archaeal compositions between NGRs, low-NGR cows (N = 22) were compared with medium-NGR (N = 22) and high-NGR (N = 22) cows. The low-NGR group was characterized by a lower abundance of Methanobrevibacter and a higher abundance of operational taxonomic units belonging to the lactate-producing, such as Intestinibaculum, Kandleria, and Dialister, and the succinate-producing Prevotella. Our findings indicate that NGR affects the methane conversion factor, methane intensity, and blood and milk compositions. Low NGR is associated with a higher abundance of lactate- and succinate-producing bacteria and lower abundances of protozoa, fungi, and Methanobrevibacter.