Meta-analysis of calorimeter data to establish relationships between methane and carbon dioxide emissions or oxygen consumption for dairy cattle

Recent developments suggest the use of other gases such as carbon dioxide (CO2) to estimate methane (CH4) emissions from livestock, yet little information is available on the relationship between these two gases for a wide range of animals. A large respiration calorimeter dataset with dairy cattle (n = 987 from 30 experiments) was used to investigate relationships between CH4 and CO2 production and oxygen (O2) consumption and to assess whether the predictive power of these relationships could be improved by taking into account some dietary variables, including forage proportion, fibre and metabolisable energy concentrations. The animals were of various physiological states (young n = 60, dry cows n = 116 and lactating cows n = 811) and breeds (Holstein-Friesian cows n = 876, Jersey × Holstein-Friesian n = 47, Norwegian n = 50 and Norwegian × Holstein-Friesian n = 14). The animals were offered forage as a sole diet or a mixture of forage and concentrate (forage proportion ranging from 10 to 100%, dry matter basis). Data were analysed using a series of mixed models. There was a strong positive linear relationship between CH4 and CO2, and observations within an experiment were very predictable (adjusted R2 = 0.93). There was no effect of breed on the relationship between CH4 and CO2. Using O2 instead of CO2 to predict CH4 production also provided a very good fit to the observed empirical data, but the relationship was weaker (adjusted R2 = 0.86). The inclusion of dietary variables to the observed CO2 emissions, in particular forage proportion and fibre concentration, provided a marginal improvement to the prediction of CH4. The observed variability in the CH4:CO2 ratio could only marginally be explained by animal physiological state (lactating vs. dry cows and young cattle) and dietary variables, and thus most likely reflected individual animal differences. The CH4:CO2 ratio can therefore be particularly useful to identify low CH4 producing cows. These findings indicate that CO2 production data can be used to accurately predict CH4 emissions to generate large scale data for management and genetic evaluations for the dairy industry.