Optimising the proportion of selection candidates measured for feed intake for a beef cattle breeding objective that includes methane emissions

Abstract

Reducing daily methane production (DMP) via selection for lower estimated daily (pasture) feed intake (DFI) has the potential to be more cost effective than direct selection for DMP. Daily feed intake has a high heritability and high genetic correlation to DMP and has a potential lower cost of measurement. This study's main aim was to determine for a breeding nucleus the optimal proportion of randomly selected young male and female cattle in which to estimate DFI. This optimum proportion was determined by modeling the measurement costs and response to selection of Angus cattle on a (standard industry) Angus breeding index (ABI) augmented with DFI and DMP in a combined breeding objective (BO), but without DMP being measured. For the assumed herd structure and considering a 20 yr planning horizon, the highest net present value (NPV) occurred when 64% of males and no females were measured for DFI. The highest breakeven DFI test cost (A$41.51/head) and highest returns on investment (ROI) occurred when 36% of males and no females had DFI estimates. Higher ROI were achieved when all males had DFI estimates before any females had DFI estimates. There was a diminishing increase in rate of genetic gain when moving from 36% to 64% of males with DFI estimates, thus ROI decreased from 29.7% to 23.1%. When 36% of males had DFI estimates (and no females), herd DMP genetic gain was slightly positive as the DMP reduction per generation from male selection (-0.086) was more than offset by the DMP increase per generation from female selection (+0.110). The selection response for DMP only became negative when at least 40% of males had DFI estimates. Having 64% of males with DFI estimates resulted in a predicted genetic decrease in DMP (-0.018 kgCOe/head per yr), compared to an increase of 0.052 kgCOe/head per yr when no animals had DFI estimates. The optimum proportion of males with DFI estimates (36 to 64%) depends on the breeders attitude toward ROI and the value of genetic change for DMP. Sensitivity analysis showed that the economic value (EV), heritability and genetic variance of DFI had a higher impact on the NPV and ROI outcomes than parameters related to ABI and DMP, so future work should focus on obtaining robust estimates for DFI parameters. Higher EV for feed intake and DMP would result in higher percentages of animals being profitably measured for DFI, leading to larger reductions in DMP.