Genetic evaluation of heat tolerance in Holsteins using test-day production records and NASA POWER weather data

Heat stress is a prominent issue in livestock production, even for intensively housed dairy herds in Canada. Production records and meteorological data can be combined to assess heat tolerance in dairy cattle. The overall aim of this study was to evaluate the possibility of genetic evaluation for heat tolerance in Canadian dairy cattle. The 2 specific objectives were (1) to estimate the genetic parameters for milk, fat, and protein yield for Holsteins while accounting for high environmental heat loads, and (2) to determine if a genotype-by-environment interaction causes reranking of top-ranked sires between environments with low and high heat loads. A repeatability test-day model with a heat stress function was used to evaluate the genetic merit for milk, fat, and protein yield under heat stress and at thermal comfort for first parity in 5 regions in Canada. The heat stress function for each trait was defined using a specific temperature-humidity index (THI) threshold. The purpose of this function was to quantify the level of heat stress that was experienced by the dairy cattle. The estimated genetic correlation between the general additive genetic effect and the additive effect on the slope of the change in the trait phenotype for milk, fat, and protein yield ranged from -0.16 to -0.30, -0.20 to -0.44, and -0.28 to -0.42, respectively. These negative correlations imply that there is an antagonistic relationship between sensitivity to heat stress and level of production. The heritabilities for milk, fat, and protein yield at 15 units above the THI threshold ranged from 0.15 to 0.27, 0.11 to 0.15, and 0.11 to 0.15, respectively. Finally, the rank correlations between the breeding values from a repeatability model with no heat stress effect and the breeding values accounting for heat stress for the 100 top-ranked bulls indicated possible interaction between milk production traits and THI, resulting in substantial reranking of the top-ranked sires in Canada, especially for milk yield. This is the first study to implement weather data from the NASA POWER database in a genetic evaluation of heat tolerance in dairy cattle. The NASA POWER database is a novel alternative meteorological resource that is potentially more reliable and consistent and with broader coverage than weather station data increasing the number of animals that could be included in a heat stress evaluation.

Phenotypic analysis of heat stress in Holsteins using test-day production records and NASA POWER meteorological data

Weather station data and test-day production records can be combined to quantify the effects of heat stress on production traits in dairy cattle. However, meteorological data sets that are retrieved from ground-based weather stations can be limited by spatial and temporal data gaps. The National Aeronautics and Space Administration Prediction of Worldwide Energy Resources (NASA POWER) database provides meteorological data over regions where surface measurements are sparse or nonexistent. The first aim of this study was to determine whether NASA POWER data are a viable alternative resource of weather data for studying heat stress in Canadian Holsteins. The results showed that average, minima, and maxima ambient temperature and dewpoint temperature as well as 4 different types of temperature-humidity index (THI) values from NASA POWER were highly correlated to the corresponding values from weather stations (regression R² > 0.80). However, the NASA POWER values for the daily average, minima, and maxima wind speed and relative humidity were poorly correlated to the corresponding weather station values (regression R² = 0.10 to 0.49). The second aim of this study was to quantify the influence of heat stress on Canadian dairy cattle. This was achieved by determining the THI values at which milk, protein, and fat yield started to decline due to heat stress as well as the rates of decline in these traits after the respective thresholds, using segmented polynomial regression models. This was completed for both primiparous and multiparous cows from 5 regions in Canada (Ontario, Quebec, British Columbia, the Prairies, and the Atlantic Maritime). The results showed that all production traits were negatively affected by heat stress and that the patterns of responses for milk, fat, and protein yields to increasing THI differed from each other. We found 3 THI thresholds for milk yield, 1 for fat yield, and 2 for protein yield. All thresholds marked a change in rate of decrease in production yield per unit THI, except for the first milk yield threshold, which marked a greater rate of increase. The first thresholds for milk yield ranged between 47 and 50, the second thresholds ranged between 61 and 69, and the third thresholds ranged between 72 and 76 THI units. The single THI threshold for fat yield ranged between 48 and 55 THI units. Finally, the first and second thresholds ranged between 58 and 62 THI units and 72 and 73 THI units for protein yield, respectively.

PSIII-12 Genetic analysis of heat tolerance in Holsteins using test-day production records and satellite-based meteorological data

Heat stress in dairy cattle is an existing issue in temperate regions that can cause reduced milk production, impaired fertility, and mortality. Genetic selection for heat tolerance using test-day production records and weather station data is a potential mitigation strategy. However, weather stations can have temporal data gaps and a low spatial resolution, which reduces the number of herds that can be incorporated into an analysis. The objectives for this study include: (1) compare satellite-based meteorological data from the NASA POWER database to weather station records in Ontario and Quebec, (2) evaluate the effects of heat stress on Canadian Holsteins, and (3) assess breeding value estimates for heat tolerance in the same population. Daily estimates of ambient temperature, dewpoint temperature, relative humidity, and wind speed from 481 weather stations in Ontario and Quebec were compared to the parameters estimated by the NASA POWER project using an ordinary least squares regression. The coordinates of herds in Ontario and Quebec were estimated using their addresses and Google Maps Geocoding. The best weather data for each herd location will be incorporated into two random regression animal models to analyze three test-day production traits: milk, fat, and protein yield. The first model will be used to estimate general and specific additive genetic merits over the thermal gradient. The second model will estimate the traditional additive genetic merit. In conclusion, this study explores the use of satellite estimated meteorological parameters in addition to or alternatively to weather station data in heat tolerance studies, quantifies the sensitivity of Canadian dairy cattle to heat stress, and evaluates if genetic selection for increased heat tolerance in Canadian dairy herds is possible.