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Prediction of enteric methane emissions from lactating cows using methane to carbon dioxide ratio in the breath.

Tomoyuki SuzukiYuko KamiyaKohei OikawaItoko NonakaTakumi ShinkaiFuminori TeradaTaketo Obitsu
Published in: Animal science journal = Nihon chikusan Gakkaiho (2022)
The aim of this study was to develop prediction equations for methane (CH 4 ) emissions from lactating cows using the CH 4 /carbon dioxide (CO 2 ) ratio in the breath measured in the automatic milking system (AMS) and to evaluate the predicted values and factors affecting the CH 4 /CO 2 ratio. The model development was conducted using a dataset determined in respiration chambers or head boxes (n = 121). Then, gas measurements in the AMS as well as in the head box were carried out with six lactating cows fed one of three different levels of neutral detergent fiber (NDF) content, following a 3 × 3 Latin square experimental design. The obtained equation that is suitable for practical use on farms to predict CH 4 was CH 4 (L/day) = -507 + 0.536 live weight (kg) + 8.76 energy-corrected milk (kg/day) + 5,029 CH 4 /CO 2 (adjusted R 2  = 0.83; root mean square error = 40.8 L/day). Results showed that the predicted values correlated positively with the observed values, the determined CH 4 /CO 2 ratio increased with increasing dietary NDF content, and the detected eructation rate was in the normal range. On the other hand, the CH 4 /CO 2 ratio was affected by the time interval between measurement and last eating before the measurement.
Keyphrases
  • carbon dioxide
  • room temperature
  • heat stress
  • dairy cows
  • transcription factor
  • machine learning
  • optical coherence tomography
  • municipal solid waste