Feed costs represent a significant component of milk production expenses, making up a share of 50% or more of the total cost. The optimization of feed costs is important to achieve financial stability, competitiveness, and sustainability in dairy farming. Optimizing dairy rations not only improves economic efficiency but also plays a significant role in reducing the environmental impact of dairy farming. On the other hand, dairy rations need to meet the specific nutritional requirements of cattle to ensure their health, well-being, and maximum milk production. The formulation of an optimal dairy ration is not an easy task for farmers due to the many challenges they face in this process. This study presents an intuitive web-based tool called OPTIMILK that is used for the optimization of dairy rations using the Simplex method of linear programming. This tool enables farmers to efficiently find a least-cost ration considering the nutritional needs of dairy cows, feed availability and costs, and the nutritional composition of feed. The tool was created for a dairy farmers’ association in Bosnia and Herzegovina and made available to its members for free. After almost four years of operation, the tool’s usage was evaluated by analyzing the collected data. The results show that after an initial period of low activity, there was evidence of an increase in the level of use, which implies the gradual adoption of the tool in dairy farming practice.

According to a report by the Food and Agriculture Organization of the United Nations, poultry meat is the leading contributor to global growth in total meat production. This growth is facilitated by the short production cycle of poultry, advancements in genetics, animal healthcare, feeding methods, breeding techniques, and improved environmental conditions, enabling producers to adapt quickly to market demands. Proper hatching practices are critical to maximizing the number of healthy chicks and minimizing their mortality rate. There are two primary methods of hatching: natural incubation, where hens incubate eggs by sitting on them, and artificial incubation, which uses incubators. In artificial incubation, monitoring and controlling key environmental factors, particularly temperature and humidity, are essential. Maintaining the incubator's temperature within an optimal range is crucial, with literature recommending a range of 37°C to 38°C and an ideal temperature of 37.8°C. This paper introduces a system for remotely monitoring and controlling temperature within an artificial incubator. The system integrates hardware and software based on the Internet of Things (IoT) framework. For this purpose, a proportional-integral-derivative (PID) controller is designed to maintain the desired temperature, with temperature data stored in a database and accessible online. The proposed system offers a cost-effective yet highly efficient solution, primarily designed for small-scale hatcheries. With modifications, it can be adapted for broader agricultural applications, including greenhouses, silos, and stables. By contributing to digital agriculture, the system supports sustainable farming practices, which are essential for the future of agriculture.