A practical future-scenarios selection tool to breed for heat tolerance in Australian dairy cattle

Climate change will have an impact on dairy cow performance. When heat stressed, animals consume less feed, followed by a decline in milk yield. Previously, we have found that there is genetic variation in this decline. Selection for increased milk production, a major breeding objective, is expected to reduce heat tolerance (HT), as these traits are genetically unfavourably correlated. We aimed to develop a future-scenarios selection tool to assist farmers in making selection decisions, that combines the current national dairy selection index, known as the balanced performance index (BPI), with a proposed HT genomic estimated breeding value (GEBV). Heat-tolerance GEBV was estimated for 12062 genotyped cows and 10981 bulls, using an established genomic-prediction equation. Publicly available future daily average temperature and humidity data were used to estimate mean daily temperature-humidity index for each dairy herd. An economic estimate of an individual cow's heat-tolerance breeding value (BV_HT) was calculated by multiplying head-tolerance GEBVs for milk, fat and protein by their respective economic values that are already used in the BPI. This was scaled for each region by multiplying BV_HT by the heat load, which is the temperature-humidity index units exceeding the threshold per year at a particular location. BV_HT were incorporated into the BPI as: BPI_HT = BPI + BV_HT; where BPI_HT is the augmented BPI' breeding value including HT. A web-based application was developed enabling farmers to predict the future heat load of a herd and take steps to aim at genetic improvement in future generations by selecting bulls and cows that rank high for the augmented BPI'.