COMBINED SYSTEM FOR THE PRODUCTION OF COMPLETE FEED BASED ON A BIOACTIVE MEDIUM USING ARTIFICIAL INTELLIGENCE
The relevance of this study is determined by the need to improve feed production efficiency under arid climatic conditions and limited natural resources, which is particularly important for livestock farming in the Republic of Kazakhstan. One of the most promising approaches to solving this problem is the implementation of automated hydroponic systems for producing complete green fodder, enabling year-round production of highly nutritious biomass with minimal water and land consumption. The aim of this study is to develop and scientifically substantiate a combined automated system for hydroponic complete feed production based on a sapropel-derived bioactive medium using artificial intelligence algorithms for predictive control of cultivation parameters. The study employed engineering design methods, mathematical modeling of ultraviolet water disinfection and lighting processes, and experimental evaluation of sapropel concentration effects on hydroponic green fodder productivity. A container-based automated production unit with a capacity of up to 500 kg/day was developed, equipped with an intelligent monitoring and control system for microclimate, lighting, irrigation, and nutrient medium parameters. It was established that the optimal sapropel concentration in the nutrient solution is 2.0 %, at which the maximum hydroponic biomass yield of 29.8 kg/m² is achieved, exceeding control values by 35.4 %. The optimal photosynthetic photon flux density was determined to be 300 μmol/m²·s. Implementation of predictive artificial intelligence algorithms reduced water consumption by 31.2 % and energy consumption by 28.7 %. The developed system reduces feed production costs by 30–40 % and can be recommended for industrial implementation in arid regions.