Sustainable development of the agricultural industry, in particular, the production of milk and feed for farm animals, requires accurate, fast, and non-invasive diagnostic tools. Currently, there is a rapid development of a number of analytical methods and approaches that meet these requirements. Infrared spectrometry in the near and mid-IR range is especially widespread. Progress has been made not only in the physical methods of carrying out measurements, but significant advances have also been achieved in the development of mathematical processing of the received signals. This review is devoted to the comparison of modern methods and devices used to control the quality of milk and feed for farm animals.

Feeding cattle on livestock farms is a labor-intensive operation that requires considerable capital investments to purchase equipment and cover labour costs. The global trends in developing technological equipment for feeding cattle include the robotization of various processes. The operation of feed pushing on the feeding table is an integral part of the feeding process, which has a significant impact on livestock productivity. This study concentrates on the simulation modeling of a feed pusher robot using Simulink tools in the Matlab environment to facilitate robot modernization or optimize the final cost for artificial testing of typical system elements and reduce production costs. Based on a simulation model, an experimental sample was designed with a controlled dispenser of feed additives, which can significantly facilitate the feeding process and optimize the dosing of concentrated additives.

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.

Practical experience demonstrates that the development of agriculture is following the path of automating and robotizing operational processes. The operation of feed pushing in the feeding alley is an integral part of the feeding process and significantly impacts dairy cattle productivity. The aim of this research is to develop an algorithm for automatic positioning and a mobile remote-control system for a wheeled robot on a dairy farm. The kinematic and dynamic motion characteristics of the wheeled robot were obtained using software that allows simulation of physical processes in an artificial environment. The mobile application was developed using Swift tools, with the preliminary visualization of interfaces and graphic design. The system uses technical vision based on RGB cameras and programmed color filters and is responsible for the automatic positioning of the feed-pusher robot. This system made it possible to eliminate the inductive sensors from the system and suspend the labor effort required for assembling the contour wire of the feed alley. By assessing the interaction between the mobile app and the feed pusher via the base station connected to the Internet and located on the farm, the efficiency and accuracy of the feedback was measured. Furthermore, remote changes in the operating regime of the robot (start date) were proven to be achievable, and the productiveness of the food supplement dispenser also became manageable.

The article examines existing methods for assessing the homogeneity of feed mixes in the feed industry and agriculture. As an alternative to existing approaches, the authors offer a low-cost online technology to assess the homogeneity of feed. The feedstuff under study includes feed mixes for cattle or compound feed consisting of naturally-grown feed (green mass of freshly cut grass, haylage, corn silage, etc.) and concentrated components (grain milling, sunflower, and soybean meal). The proposed method based on an RGB camera, a diode lamp, filters, and software is approved by a preliminary study of the physical properties of feed mix components by Specim IQ hyperspectral camera and revealing characteristics of light absorption of each type of components (concentrated/natural origin). The article presents a method of processing a feed mix image fixed by an RGB camera through light filters using Matlab Image Processing Toolbox tools, namely, a Color Thresholder app and Image Region Analyzer app.