Genetic Parameters of Different FTIR-Enabled Phenotyping Tools Derived from Milk Fatty Acid Profile for Reducing Enteric Methane Emissions in Dairy Cattle

SIMPLE SUMMARY: Enteric methane emission (EME) in dairy cows can feasibly be mitigated through genetic improvement at the population level. This work shows that several EME-related traits, directly and indirectly predicted from infrared spectra of milk, are heritable and are genetically correlated with those based on the fatty acid profile of milk. Genetic parameters were estimated using univariate and bivariate animal models. The results show that easy-to-measure values correlated to EME traits were identified and seem to have the potential to be exploited in breeding programs to improve the impact of dairy farming on climate change. ABSTRACT: This study aimed to infer the genetic parameters of five enteric methane emissions (EME) predicted from milk infrared spectra (13 models). The reference values were estimated from milk fatty acid profiles (chromatography), individual model-cheese, and daily milk yield of 1158 Brown Swiss cows (85 farms). Genetic parameters were estimated, under a Bayesian framework, for EME reference traits and their infrared predictions. Heritability of predicted EME traits were similar to EME reference values for methane yield (CH(4)/DM: 0.232–0.317) and methane intensity per kg of corrected milk (CH(4)/CM: 0.177–0.279), smaller per kg cheese solids (CH(4)/SO: 0.093–0.165), but greater per kg fresh cheese (CH(4)/CU: 0.203–0.267) and for methane production (dCH(4): 0.195–0.232). We found good additive genetic correlations between infrared-predicted methane intensities and the reference values (0.73 to 0.93), less favorable values for CH(4)/DM (0.45–0.60), and very variable for dCH(4) according to the prediction method (0.22 to 0.98). Easy-to-measure milk infrared-predicted EME traits, particularly CH(4)/CM, CH(4)/CU and dCH(4), could be considered in breeding programs aimed at the improvement of milk ecological footprint.