Sustainability & efficiency

Analysis of environmental factors influencing methane to carbon dioxide ratio and predicted methane emissions of Holstein cows in Japan by the sniffer method

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Abstract

Enteric methane in dairy cattle is gaining attention as a target for greenhouse gas reduction. Genetic improvement is an effective method to achieve methane reductions in dairy cattle, but it requires many data. The sniffer method collects cow's breath at milking robots or feed troughs and measures methane and carbon dioxide concentrations. Compared to other measurement methods, it is easy to deploy and excels for continuous data collection from many cows on farms. The aim of this study was to identify the environmental factors affecting the methane to carbon dioxide ratio (CH4:CO2) and predicted methane emissions (pCH4) using the sniffer method in Japanese Holsteins. Holstein milking cows from 14 farms in Japan were used from fiscal years 2022 to 2024. Methane and carbon dioxide concentration (ppm) in cow's breath were measured using the sniffer method, and the average of CH4:CO2 for experimental periods (7-10 days) was calculated. Body weight and milk yield were also measured for experimental periods, and averaged. Milk compositions were measured by Fourier transform infrared spectroscopy. pCH4 was predicted from body weight, milk yield, milk compositions and CH4:CO2 using the equation by Suzuki et al. (2021). After excluding records of measurement failure, 1,981 records from 798 cows were used for analysis. The mathematical model included herd-gas analyzer (22 levels), fiscal year (3 levels), month (6 levels: grouped every two months), parity (4 levels: first calving, second calving, third calving, fourth calving or more), and days in milk (DIM, 13 levels: ≤30 DIM, 31-360 DIM grouped in 30-day intervals, ≥361 DIM) as fixed effects, and individual cows as a random effect. Using the above model, analysis of variance was performed and least squares means (LSM) were calculated. The means and standard deviations of methane concentration, CH4:CO2, and pCH4 are 275±118 ppm, 0.0892±0.0145 ppm/ppm, and 582±117 L/day, respectively. Analysis of variance revealed significant effects for all factors on both CH4:CO2 and pCH4 (p 4:CO2 peaked in July-August (0.0936 ppm/ppm) and was lower in September-December (0.0828-0.0841 ppm/ppm). pCH4 peaked in May-June (641 L/day) and was also lower in September-December (566-567 L/day). The LSM for CH4:CO2 decreased from first parity (0.0897 ppm/ppm) to third parity (0.0872 ppm/ppm). The LSM for pCH4 tended to increase with parity. For the LSM by DIM, CH4:CO2 was low in early lactation (0.0843 ppm/ppm). After that, but no major trend was observed (0.0855-0.0910 ppm/ppm). pCH4 was also low during early lactation (589 L/day), increased thereafter (151-180 DIM: 620 L/day), and then gradually decrease (≥361 DIM: 586 L/day). In conclusion, this study clarified that herd-gas analyzer, fiscal year, month, parity, and DIM were the environmental factors affecting CH4:CO2 and pCH4 using the sniffer method.

Keywords: 2026

How to Cite:

Ito, F., Kobayashi, J., Kodama, T., Kotaki, Y., Nishiura, A., Obitsu, T., Oikawa, K., Saito, Y., Sasaki, O., Sasano, T., Suzuki, T., Tanabe, T., Tatebayashi, R., Tomaru, T., Yamada, M. & Yamashita, M., (2026) “Analysis of environmental factors influencing methane to carbon dioxide ratio and predicted methane emissions of Holstein cows in Japan by the sniffer method”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2287398. doi: https://doi.org/10.31274/wcgalp.24289

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