Invited review: Large-scale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions

[object Object]Efforts to reduce the carbon footprint of milk produc- tion through selection and management of low-emitting cows require accurate and large-scale measurements of methane (CH 4 ) emissions from individual cows. Several techniques have been developed to measure CH 4 in a re- search setting but most are not suitable for large-scale recording on farm. Several groups have explored prox- ies (i.e., indicators or indirect traits) for CH 4 ; ideally these should be accurate, inexpensive, and amenable to being recorded individually on a large scale. This review (1) systematically describes the biological basis of current potential CH 4 proxies for dairy cattle; (2) assesses the accuracy and predictive power of single proxies and determines the added value of combining proxies; (3) provides a critical evaluation of the relative merit of the main proxies in terms of their simplicity, cost, accuracy, invasiveness, and throughput; and (4) discusses their suitability as selection traits. The prox- ies range from simple and low-cost measurements such as body weight and high-throughput milk mid-infrared spectroscopy (MIR) to more challenging measures such as rumen morphology, rumen metabolites, or microbi- ome profiling. Proxies based on rumen samples are gen- erally poor to moderately accurate predictors of CH 4 , and are costly and difficult to measure routinely on- farm. Proxies related to body weight or milk yield and composition, on the other hand, are relatively simple, inexpensive, and high throughput, and are easier to implement in practice. In particular, milk MIR, along with covariates such as lactation stage, are a promising option for prediction of CH 4 emission in dairy cows. No single proxy was found to accurately predict CH 4 , and combinations of 2 or more proxies are likely to be a better solution. Combining proxies can increase the accuracy of predictions by 15 to 35%, mainly because different proxies describe independent sources of varia- tion in CH 4 and one proxy can correct for shortcomings in the other(s). The most important applications of CH 4 proxies are in dairy cattle management and breed- ing for lower environmental impact. When breeding for traits of lower environmental impact, single or multiple proxies can be used as indirect criteria for the breeding objective, but care should be taken to avoid unfavor- able correlated responses. Finally, although combina- tions of proxies appear to provide the most accurate estimates of CH 4 , the greatest limitation today is the lack of robustness in their general applicability. Future efforts should therefore be directed toward developing combinations of proxies that are robust and applicable across diverse production systems and environments.