Abstract :
[en] Breeding needs tools to quantify at large scale greenhouse gases emissions in order to develop levers to reduce them. Milk mid-infrared (MIR) spectrum is a promising proxy to estimate daily methane (CH4) emissions of individual dairy cows. A model has been developed based on 1,089 reference measurements combining milk MIR spectra and CH4 records, collected using the SF6 tracer technique (n=513) and respiration chambers (n=576). These data came from 7 countries (BE, IRL, CH, UK, FR, DK and D) and from cows of 5 major breeds: Holstein (74%), Brown Swiss (13%), Jersey (3%), Red Holstein (3%) and Swedish Red Crossed (2.5%). Using a 5 groups cross-validation (CV), statistics reached an R2 of 0.64 with a SE of 61 g of CH4/day. A cow and country dependent external validation (CCDEV) has been performed: all the data from 20% of the cows per country are removed, calibration was then done on the 80% remaining cows from all countries and validated on the 20% removed. After 500 repetitions, the R2 and the RMSEP of CCDEV were 0.55±0.07 and 70±4.5 g of CH4/day respectively. To asses improving these results, parity, milk yield and breed information have been added individually and by combination to the MIR spectra. This led to 7 new calibration models. Statistics were improved with the parameters included, with an optimum found for the version combining milk MIR spectra, milk yield, parity and breed as predictors. The statistics reached a R2cv of 0.68, a SECV of 57 g of CH4/day, and R2 and RMSEP of CCDEV of 0.6±0.06 and 65±4.1 respectively. Including these routinely available cow parameters improves the model prediction performance. Practical applications are still required to observe and confirm the relevance of these new predictions.
