Relationships between methane emission of Holstein Friesian dairy cows and fatty acids,volatile metabolites and non-volatile metabolites in milk

This study investigated the relationships between methane (CH₄) emission and fatty acids, volatile metabolites (V) and non-volatile metabolites (NV) in milk of dairy cows. Data from an experiment with 32 multiparous dairy cows and four diets were used. All diets had a roughage : concentrate ratio of 80 : 20 based on dry matter (DM). Roughage consisted of either 1000 g/kg DM grass silage (GS), 1000 g/kg DM maize silage (MS), or a mixture of both silages (667 g/kg DM GS and 333 g/kg DM MS; 333 g/kg DM GS and 677 g/kg DM MS). Methane emission was measured in climate respiration chambers and expressed as production (g/day), yield (g/kg dry matter intake; DMI) and intensity (g/kg fat- and protein-corrected milk; FPCM). Milk was sampled during the same days and analysed for fatty acids by gas chromatography, for V by gas chromatography–mass spectrometry, and for NV by nuclear magnetic resonance. Several models were obtained using a stepwise selection of (1) milk fatty acids (MFA), V or NV alone, and (2) the combination of MFA, V and NV, based on the minimum Akaike’s information criterion statistic. Dry matter intake was 16.8±1.23 kg/day, FPCM yield was 25.0±3.14 kg/day, CH₄ production was 406±37.0 g/day, CH₄ yield was 24.1±1.87 g/kg DMI and CH₄ intensity was 16.4±1.91 g/kg FPCM. The observed CH₄ emissions were compared with the CH₄ emissions predicted by the obtained models, based on concordance correlation coefficient (CCC) analysis. The best models with MFA alone predicted CH₄ production, yield and intensity with a CCC of 0.80, 0.71 and 0.69, respectively. The best models combining the three types of metabolites included MFA and NV for CH₄ production and CH₄ yield, whereas for CH₄ intensity MFA, NV and V were all included. These models predicted CH₄ production, yield and intensity better with a higher CCC of 0.92, 0.78 and 0.93, respectively, and with increased accuracy (C_b) and precision (r). The results indicate that MFA alone have moderate to good potential to estimate CH₄ emission, and furthermore that including V (CH₄ intensity only) and NV increases the CH₄ emission prediction potential. This holds particularly for the prediction model for CH₄ intensity.