This experiment was conducted to study the effect of a prolonged hot period on the fatty acid (FA) composition in blood serum of dairy cows. Eighteen multiparous Holstein cows were randomly assigned to the hyperthermia group (HYP, n = 8) in August (summer season) and the control group (CON, n = 10) in October (autumn season). Blood from animals of the HYP group was collected in one heat wave, which was preceded by a long period of heat stress (HS, temperature-humidity index (THI ≥ 72)). Blood from cows of the CON group was collected under thermal comfort conditions (THI < 68). The spectrum of free fatty acids (FFA) in the blood serum was analyzed by gas chromatography. The concentration of FFA increased, including saturated FAs and monounsaturated FAs, in the blood serum of cows under conditions of prolonged HS. This was associated with the mobilization of FA into the bloodstream from adipose tissue, as a consequence of negative energy balance. An increase in the ratio of n-6/n-3 polyunsaturated FAs may indicate biomembrane dysfunction and adversely affect dairy cows. This study showed that prolonged periods of heat can affect the FA composition of blood. How much this leads to changes in the FA composition of milk and the quality of food products remains to be seen in further research.

Finding livestock breeds that are resistant to high temperatures may be one of the strategies for mitigating the impact of global climate change on dairy farming. In this investigation, we studied the heat resistance of Holstein (HB) and Brown Swiss (BS) cows on two commercial dairy farms under the hot summer conditions of Ukraine. The physiological response of animals determined heat resistance by measuring rectal temperature (RT) and respiratory rate (RR) in the morning (from 4:00 to 6:00) in comfortable conditions and the afternoon (from 14:00 to 16:00), during heat load. The temperature-humidity index (THI) was used to characterize weather conditions and microclimate in naturally ventilated rooms (NVBs). BS cows were found to be heat resistant. The reaction of HB cows to the heat was manifested by higher growth of RT and RR, and they suffered significant losses in the daily milk yield per cow in the summer. Further research will need to elucidate the biological and genetic mechanisms of the identified breed differences in heat tolerance of dairy cows.

Global climate change is a challenge for dairy farming. In this regard, identifying reliable correlations between environmental parameters and animals’ physiological responses is a starting point for the mathematical modeling of their effects on the future welfare and milk production of cows. The aim of the study was to examine the relationship between environmental parameters and the milk production of cows in hot period. Archival data from the Ukrainian Hydrometeorological Center were used to study the state of insolation conditions (IC), wind direction (WD), wind strength (WS), air temperature (AT), and relative humidity (RH). The temperature–humidity index (THI) (Kibler, 1964) and temperature–humidity index in the hangar-type cowshed (THI_CHT) (Mylostyvyi et al., 2019) served as integral indicators of the state of the cowshed’s microclimate. The daily milk yield (DMY), yield of milk fat (MF) and milk protein (MP), and percentage of milk fat (PMF) and protein (PMP) were taken into account by the DairyComp 305 herd management system (VAS, USA). Statistical data processing was performed using the mathematical functions of Microsoft Excel (Microsoft Inc.) and Statistica 10 (StatSoft Inc.). There was a weak correlation between IC and DMY at r = −0.2, between RH and DMY at r = +0.4, and between RH and MF at r = +0.2. Between DMY, MF, MP, and WS made up r = –0.2 to 0.4. Between DMY, MF, MP, and AT made up r = −0.2 to 0.5 (p < 0.05). The effects of weather factors on animal productivity will be the subject of further research.

The increasing variability of weather conditions associated with global climate change is becoming a major problem for dairy farming. The present article provided the results of studies on the relationship between the milk production of Holstein cows and environmental parameters during the warm season. The study investigated whether the relationship between weather conditions (air temperature, relative humidity, wind direction, wind strength, and insolation) and daily milk yield, as well as its components (milk fat yield and milk protein), depended on the conditions comfortable for the cows. The temperature-humidity index was calculated based on air temperature and relative humidity data, which were recorded by the nearest weather station to the farm, which is subordinate to the Ukrainian Hydrometeorological Center. It was found that the relationship between environmental parameters and milk yield was weak concerning the increase in proportion to the growth of heat load. However, the factorial analysis indicated that the total influence of weather factors on milk yield, milk fat, and protein yield was 42-46%. Moreover, weather conditions could significantly impact dairy productivity when cows are kept in naturally ventilated barns. This suggests further investigation of issues related to the microclimate improvement in cowsheds in hot seasons using sprinkler systems for cooling dairy cows.

Agriculture plays a vital role in food production, resource utilization, and employment but faces challenges from population growth, climate change, and food shortages. The development of information technology has significantly contributed to the industry's development, and modern technologies such as artificial intelligence, the Internet of Things, computer vision, and machine learning have revolutionized agricultural practices. The purpose of this review is to explore the adoption of digital technologies in agriculture, with a specific focus on their application in livestock breeding. Through the examination of current literature and the utilization of various research methods, this review contributes to the existing knowledge in the field. It is established that the latest information tools allow collecting, analysing data, automating tasks and supporting decision-making, which leads to increased agricultural efficiency, resource management and sustainable development. It has been proven that modern technologies play a crucial role in increasing agricultural production, improving the efficiency of livestock and crop production. These technologies include devices and sensors, data analytics and decision support systems, as well as systems for overall farm productivity assessment. Precision technologies in agriculture, thanks to automation, sensors and machine learning, allow farmers to monitor animal health, optimise feed consumption, detect diseases at early stages and increase overall productivity. IT solutions in agriculture facilitate data processing, visualisation and decision-making, leading to lower costs, greater efficiency and improved food security. The study provides practical insights for farmers and other agricultural stakeholders who can benefit from accurate information, real-time monitoring and automated processes through the integration of modern technologies, ultimately improving agricultural practices and sustainability