Animal Bioscience

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Exploring indicators of genetic selection using the sniffer method to reduce methane emissions from Holstein cows

  • Yoshinobu Uemoto (Graduate School of Agricultural Science, Tohoku University) ;
  • Tomohisa Tomaru (Gunma Prefectural Livestock Experiment Station) ;
  • Masahiro Masuda (Niikappu Station, National Livestock Breeding Center (NLBC)) ;
  • Kota Uchisawa (Niikappu Station, National Livestock Breeding Center (NLBC)) ;
  • Kenji Hashiba (Niikappu Station, National Livestock Breeding Center (NLBC)) ;
  • Yuki Nishikawa (Head office, National Livestock Breeding Center (NLBC)) ;
  • Kohei Suzuki (Head office, National Livestock Breeding Center (NLBC)) ;
  • Takatoshi Kojima (Head office, National Livestock Breeding Center (NLBC)) ;
  • Tomoyuki Suzuki (Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization (NARO)) ;
  • Fuminori Terada (Institute of Livestock and Grassland Science, NARO)
  • Received : 2023.03.31
  • Accepted : 2023.08.24
  • Published : 2024.02.01
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Abstract

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.

Keywords

Acknowledgement

This work was supported by the MAFF Commissioned project study on "Development of Technologies to Reduce Greenhouse Gas Emissions in the Livestock Sector" (Grant Number JPJ011299).

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