Accuracy of methane emissions predicted from milk mid-infrared spectra and measured by laser methane detectors in Brown Swiss dairy cows

Since heritability of CH₄ emissions in ruminants was demonstrated, various attempts to generate large individual animal CH₄ data sets have been initiated. Predicting individual CH₄ emissions based on equations using milk mid-infrared (MIR) spectra is currently considered promising as a low-cost proxy. However, the CH₄ emission predicted by MIR in individuals still has to be confirmed by measurements. In addition, it remains unclear how low CH₄ emitting cows differ in intake, digestion, and efficiency from high CH₄ emitters. In the current study, putatively low and putatively high CH₄ emitting Brown Swiss cows were selected from the entire Swiss herdbook population (176,611 cows), using an MIR-based prediction equation. Eventually, 15 low and 15 high CH₄ emitters from 29 different farms were chosen for a respiration chamber (RC) experiment in which all cows were fed the same forage-based diet. Several traits related to intake, digestion, and efficiency were quantified over 8 d, and CH₄ emission was measured in 4 open circuit RC. Daily CH₄ emissions were also estimated using data from 2 laser CH₄ detectors (LMD). The MIR-predicted CH₄ production (g/d) was quite constant in low and high emission categories, in individuals across sites (home farm, experimental station), and within equations (first available and refined versions). The variation of the MIR-predicted values was substantially lower using the refined equation. However, the predicted low and high emitting cows (n = 28) did not differ on average in daily CH₄ emissions measured either with RC or estimated using LMD, and no correlation was found between CH₄ predictions (MIR) and CH₄ emissions measured in RC. When individuals were recategorized based on CH₄ yield measured in RC, differences between categories of 10 low and 10 high CH₄ emitters were about 20%. Low CH₄ emitting cows had a higher feed intake, milk yield, and residual feed intake, but they differed only weakly in eating pattern and digesta mean retention times. Low CH₄ emitters were characterized by lower acetate and higher propionate proportions of total ruminal volatile fatty acids. We concluded that the current MIR-based CH₄ predictions are not accurate enough to be implemented in breeding programs for cows fed forage-based diets. In addition, low CH₄ emitting cows have to be characterized in more detail using mechanistic studies to clarify in more detail the properties that explain the functional differences found in comparison with other cows.