Exploring sustainability in dairy cattle breeding focusing on feed efficiency and methane emissions *

Reducing emissions is vital to improve sustainability, and industry leaders have set emission goals to reduce gross emissions, lower emissions intensity, or reach net zero. However, additional traits should also be measured and compared in terms of their impact on the broader definition of sustainability. In addition to environmental impact, a sustainable breeding objective must consider profit, animal welfare, farmer well-being, and social responsibility. Traits to be considered include direct emissions (e.g., nitrogen and methane), production efficiency (e.g., feed efficiency), health (e.g., calf and transition cow health), and welfare traits (e.g., polled). Many of these novel traits require labor- and cost-intensive phenotyping procedures. Consequently, this results in relatively modest data sets and estimated breeding values with limited reliability. Opportunities exist to overcome this limitation by developing cost-effective and easily quantifiable proxy traits and utilizing international collaboration to expand novel phenotype reference populations. Furthermore, noneconomic values can be estimated to quantify the impact of a trait on societal perspective (e.g., farmer preference) or environmental impact (methane emissions), and combined with economic weights to calculate aggregate weights for each trait. Although validation techniques are still uncertain, the United Nations Sustainable Development Goals may be applied to determine the improvement in sustainability due to genetic selection. This approach provides the flexibility to accommodate diverse sustainability perspectives, encompassing the disparities between developed and developing countries. Currently, the number and quality of relevant phenotypes are the main limiting factor. However, as confidence grows in the opportunity to improve sustainability through genetic selection, substantial new investment will be required in both refining phenotyping methodologies and conceptualizing novel breeding designs.