Year: 2025
Type: article
Abstract: Optimizing genetic selection for the modern dairy herd is a key component for improving health and production and reducing environmental footprints.The objective of this retrospective study was to estimate the effects of genetic progress on environmental outcomes by using a comprehensive, whole-farm, process-based model, the Ruminant Farm System, which simulates individual animals and their unique daily events to model animal and herd production and environmental effects.In this study, the selection index used was Dairy Wellness Profit (DWP$).Data from 11 herds, for a total of 13,317 cows, were used to compare the best 25% of the animals within the herd with the worst 25% of the herd with respect to broader herd outcomes.Each of these herds was simulated 10 times over a 5-yr interval to estimate production and environmental outputs, including GHG emissions and manure nutrient excretion values and intensities.A regression analysis of the 220 enteric methane emission intensities on the average DWP$ of the herd estimated that enteric methane intensity decreased by 0.00017 kg CO 2 e/kg fat-and protein-corrected milk (FPCM) for each $1 increase in DWP$.For perspective, the average herd is making 84 DWP$ genetic progress per year (internal data).Given the average intensity value of 0.58 kg CO 2 e/kg FPCM, the lifetime enteric methane intensity of production would be expected to be 2.5% lower for each year's replacement heifers.Similar reductions were seen for the total farm footprint (sum of enteric, manure, and feed emissions) and manure nitrogen and phosphorus excretion intensities (0.00027 kg CO 2 e/kg FPCM, 0.000007 kg P/kg FPCM, and 0.0000005 kg P/ kg FPCM for every $1 increase in DWP$).The results represent the environmental effects of the differences in animal performance and herd structure associated with improved genetic merit for DWP$.The benefit of improving genetic selection within a herd using DWP$ along with proper management practices can reduce the environmental footprints of dairy cow herds.
Source: Journal of Dairy Science
Authors: D.J. Weigel, J. Adamchick, K.R. Briggs, B. Fessenden, E.A. Melchior, J.Q. Fouts, K. Reed, F. Di Croce
Language: English
Subfield: Genetics
Domain: Life Sciences
SDGs: Zero hunger, Climate action
Open Access status: gold
Estimated APC paid: $3,500
OpenAlex ID: W4409548808