The aim of this study was to explore the possibility of assessing the health status of a cow’s udder using infrared thermography. We studied the effect of mastitis on cow milk yield, the effect of mastitis on udder surface skin temperature, and the dependence between severity of mastitis and udder temperature. We determined the presence of a significant relationship between the udder surface skin temperature and the milk yield of mastitis cows (Coefficient of determination = 0.886, linear Pearson correlation coefficient = −0.96), as well as the absence of a significant relationship between the udder surface skin temperature and the milk yield of healthy cows (Coefficient of determination = 0.029, linear Pearson correlation coefficient = 0.16). We substantiated the temperature ranges of the udder surface of healthy cows [32–35.9 °C] and mastitis [36.1–39 °C]. The obtained data made it possible to form an algorithm that allows a quick assessment of the herd for the presence of udder disease, using infrared images of the udder surface skin temperature.

Analytical and theoretical studies were conducted in working cattle facilities in order to identify infectious, parasitic, and nervous diseases in large horned cattle. Our analytical study was based on the analysis of available scientific research papers. The theoretical research was based on processing the measurement results with existing hardware and software. Both environmental and physiological parameters were obtained from five farms for at least 30 days. The studied cows were divided into two groups. One group consisted of 37 dairy cows of the Holstein breed aged 2–3 years having no clinical signs of disease. All cows in this group were fed the same diet, kept in the same conditions, and had the same lactation period (from 3 to 5 months). Their average weight was 517 (±2.03) kg. For inclusion into the second group, we selected 23 dairy cows with parameters similar to those of the cows in the first group but with some clinical signs of diseases such as encephalomyelitis, infectious enteritis, and hypodermatosis. The data obtained from the animals in the first group were considered as the parameters’ standardized boundary values for the estimation of a cow’s conditions, i.e., as the norm (the setpoint). As for the data obtained for the second group, they were considered to be deviations from the threshold values of the parameters (deviations from the setpoint, which required a pre-planned action). The analysis was carried out using the program code implemented in the software package “Matlab R2019b”. We analyzed the correlations between the cows’ rumen temperature and pH, their locomotive activity, and environmental parameters such as air temperature and relative humidity in the cowsheds. We then constructed graphs of inter-correlating functions. As a result of the study, for the first time, algorithms were compiled enabling the detection of infectious, parasitic, and nervous diseases.

The global recent development trend in dairy farming emphasizes the automation and robotization of milk production. The rapid development rate of dairy farming requires new technologies to increase the economic efficiency and improve production. The research goal was to increase the milk production efficiency by introducing the technology to automatically assess the fatness of a dairy herd in 0.25-point step on a 5-point scale. Experimental data were collected on the 3D ToF camera O3D 303 installed in a walk-through machine on robotic free-stall farms in the period from August 2020 to November 2022. The authors collected data on 182 animals and processed 546 images. All animals were between 450 and 700 kg in weight. Based on the regression analysis, they developed software to find and identify the main five regions of interest: the spinous processes of the lumbar spine and back; the transverse processes of the lumbar spine and the gluteal fossa area; the malar and sciatic tuberosities; the tail base; and the vulva and anus region. The adequacy of the proposed technology was verified by means of a parallel expert survey. The developed technology was tested on 3 farms with a total of 1810 cows and is helpful for the non-contact evaluation of the fatness of a dairy herd within the herd’s life cycle. The developed method can be used to evaluate the tail base area with 100% accuracy. The hungry hole can be determined with a 98.9% probability; the vulva and anus area—with a 95.10% probability. Protruding vertebrae—namely, spinous processes and transverse processes—were evaluated with a 52.20% and 51.10% probability. The system’s overall accuracy was assessed as 93.4%, which was a positive result. Animals in the condition of 2.5 to 3.5 at 5–6 months were considered healthy. The developed system makes it possible to divide the animals into three groups, confirming their physiological status: normal range body condition, exhaustion, and obesity. By means of a correlation dependence equal to R = 0.849 (Pearson method), the authors revealed that animals of the same breed and in the same lactation range have a linear dependence of weight-to-fatness score. They have developed an algorithm for automated assessment of the fatness of animals with further staging of their physiological state. The economic effect of implementing the proposed system has been demonstrated. The effect of increasing the production efficiency of a dairy farm by introducing the technology of automatic evaluation of the fatness of a dairy herd with a 0.25-point step on a 5-point scale had been achieved. The overall accuracy of the system was estimated at 93.4%.

Relevance. Increased values of temperature and relative humidity of the external environment lead to negative consequences for the animal body, forcing the thermoregulation processes to be turned on. These mechanisms allow the animal organism to adapt to new environmental conditions at the expense of productivity. In these cases heat stress is observed. It is established that its manifestation is observed after 17 hours and there is a possible decrease in productivity by 35–40%. To identify the effect of heat stress, accurate determination of temperature-humidity index (THI) is necessary.Methods. The materials and methods contain the most common formulas for determining the temperature and humidity index. The equipment and software package used for the research are presented.Results. A graph of the results of South Korean studies is presented to compare the effects of heat stress on productivity. The results and discussions display a modernized formula for determining the heat stress index and figures showing the level of heat stress at different temperature and relative humidity levels.