Milk Production Under Summertime Heat Stress In Different Cattle Breeds

An exposure to microclimatic conditions characterized by a combination of high temperature and air humidity may surpass an animal ability to maintain both normal thermoregulation and constant body temperature thus leading to an increase in body temperature that exceeds physiological limits. In addition to direct effects of heat stress on productivity, reproduction and health status of animals, global warming also affects animals indirectly through reduced soil fertility, water availability, crop yields, quality of plant nutrients and the circulation of pathogenic agents. The goal of the research was to study the effects of different fixed factors on the milk yield characteristics included in the analysis: MY – daytime milk yield (kg/day), MF - milk fat content (%) and MP - protein content (%). A total data set contained test-day information for the analysed traits during the summer period. The effects of breed, breeding area (district), order of lactation, phase of lactation, year of calving, season of calving, and month of control during the average daily temperature - humidity index (THI≥72) were studied. Manifestation and variability of the examined traits were determined using the PROC FREQ and PROC MEANS procedures, while the effect of individual factors on the examined traits was determined using the PROC GLM procedure of the SAS package. Cows had the highest daily milk yield when they calved during the spring season, in their third lactation and in the interval of the second phase (2-4 months) of lactation. Holstein cows achieved a higher milk yield than Red Holstein, Simmental and Brown Swiss cows. Milk yield per day decreased during the summer months from June to September. The fat content was the lowest in cows calved in the spring season, during the first lactation and the first phase of lactation (first 2 months) being lower during July, August and September compared to June. The protein content decreased during the summer from June to August. The model used along with a statistical analysis of the factors within the model showed a credible representation of the results obtained. A high statistical significance of the factors included in the model was determined (p<0.001).