Sustainability & efficiency

Logistics and value of recording field data for an international genomic reference population to improve beef cow resource use efficiency

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Abstract

Beef producing nations are striving to meet the global challenge of growing protein demand while delivering climate targets. Genomic selection has been identified as a viable method to improve cattle efficiency, reducing energy loss including methane. Five nations have united and joined the Global methane Genetics initiative, to establish the required reference population. The objective of this study was to present a practical framework to evaluate potential recording strategies. The target animal for measurement is the mother cow as the cow-calf sector offers the largest opportunity for energy loss abatement via selection. The framework to evaluate potential recording technologies considers the expected accuracy of genomic prediction given a level of investment based on the assumption that lower cost measures will translate to more phenotyped animals. Four potential indicative technologies with different heritabilities (h2) and costs (USD/record) were considered including A: infield gas flux (h2=0.4, 594 USD), B: accumulation chamber (h2=0.2, 221 USD), C: infield sniffer (h2=0.1, 88 USD) and D: molecular phenotype (h2=0.05, 30 USD). In these scenarios, A and B have previously estimated heritabilities where those for C and D were hypothetical. The expected genomic prediction accuracy assumed a perfect correlation with the target phenotype and was calculated with established equations based on the effective number of chromosome segments (Me) in the Australian Angus population along with heritability and number of records considering a combined investment of 2,050,982 USD for a single breed's reference. The expected accuracy and number of records were respectively A: 0.51, 3453; B: 0.55, 9263; C: 0.57, 23,259 and D: 0.62, 68,366. Results show that less accurate and cheaper technology can result in more reliable genomic predictions as the lower cost per record enables more records for a given investment. To provide the same 0.51 accuracy as obtained from technology A, the heritability of B, C and D could be as low as 0.16, 0.07 and 0.03, respectively. This demonstrates that the heritability of these lower cost measurement technologies can be considerably lower to achieve similar outcomes in genomic prediction accuracy. The final decision on recording technology needs to consider factors beyond operating costs. Collecting the required large number of records requires deployment across many breeder herds, so therefore the technology must be robust (i.e., minimal down time) and readily deployable across a range of conditions. Also, the lower cost technologies will result in more animals being sampled, which presents logistical challenges but offers a broader reference population, and the potential to investigate genotype by environment interaction. The framework presented will prove important to evaluate emerging technologies to build a genomic reference that combines genomic prediction accuracy with other practical considerations.

Keywords: 2026

How to Cite:

Aldridge, M., Archer, J., Berry, D., Bilton, T., Bunning, H., Clark, S., Coffey, M., Evans, R., Garcia, A., Kelly, D., Lakamp, A., Matthews, K., Miller, S., Ramos, P., Retallick, K., Rowan, T. & Rowe, S., (2026) “Logistics and value of recording field data for an international genomic reference population to improve beef cow resource use efficiency”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2286284. doi: https://doi.org/10.31274/wcgalp.23905

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