Abstract

Heat stress is a major challenge for dairy herds and can lead to significant production reduction, mainly in tropical climate. Differences in decreased milk production in animals is associated with genetic variation. The overall goal was to investigate the effect of heat stress in milk yield of Girolando cattle in tropical climate and to identify the most appropriate statistical approach for evaluation and selection for heat tolerance in different breed compositions of Girolando. Therefore, to quantify heat stress effects on milk yield loss in Girolando cattle, random regression models were applied on test-day milk yield records (TDMY) and weather data. In addition, different statistical models were evaluated for estimating variance components and predicting breeding values for heat stress (HS). The data comprised 648,072 TDMY of 69,431 first-lactation Girolando cows of different breed compositions, and 21,147 genotyped animals, with daily temperature and humidity measurements from weather stations closest to the tested herds, between 2000 and 2020. We used daily mean values of temperature-humidity index (THI) for the day of test and the 3 previous days as the measure of HS. Heat stress thresholds estimated for the different breed compositions of Girolando in this study were THI 80 for 1/4H, 1/2H and 5/8H; THI 78 for 3/4H animals and THI 77 for 7/8H animals. Average milk production can decrease by up to 34% due to heat stress. Estimated average heritability for TDMY regressed to the THI was 0.21, while the heritability estimated for TDMY regressed to the DIM was 0.29. A correlation of 0.55 was observed between the GEBVs of HS tolerance and GEBV milk yield. The parameters estimated in this study indicate that genomic selection for heat tolerance in dairy cattle is a step towards ensuring valuable tropical production efficiency and improving animal welfare in the face of predicted increases in heat stress events and increase tropical production efficiency.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call