«Smart» agriculture as a promising vector of development of the agro-industrial complex of mountain territories

Introduction. Most mountainous areas of Russia have an agricultural orientation and are characterized by the presence of complex development problems: low level of arable land use, low crop yields. Despite this, mountainous areas have significant resource potential for growing vegetables, grain and fruit crops. The use of modern digital technologies, explainable artificial intelligence in agriculture will help preserve ecosystems and efficiently use natural resources, increase the competitiveness of the agricultural sector, and create conditions for the economic and social revival of rural regions in mountainous areas. Research objective. To study the theoretical foundations and modern applied aspects of the use of digital technologies in agriculture in mountainous areas, and to propose a concept for integrating explainable artificial intelligence into digital agriculture to ensure sustainable development. Research methodology. The justification of proposals and recommendations was carried out using a logical analysis of issues and problems of implementing modern digital transformation technologies by agricultural enterprises; an illustrative method was used to clearly present a structural description of the integration of explainable artificial intelligence into digital agriculture in mountainous areas, emphasizing its impact on the transparency of the model and user trust. Research results. The article presents the results of a study on the application of digital technologies for the development of the agro-industrial complex of mountainous territories. The possibilities of smart farming, farmers’ attitudes towards new technologies, and existing barriers in mountainous territories are described. The study systematizes modern digital technologies in the agricultural sector according to certain criteria: space technologies, Internet technologies, information and communication and end-to-end technologies, sensors and detectors. Each individual block of digital technologies is analyzed in terms of the possibilities and advantages of practical use. The key role of explainable artificial intelligence in the formation of precision farming is determined. Discussion of results. The needs of small-scale mountain agriculture can be met using the so-called “appropriate technologies” or “intermediate technologies” approach, which is aimed at developing relatively simple and energy-efficient small-scale tools using materials that are readily available in their intended environment. It has been established that the application of technologies requires a “useroriented” and systematic approach that hybridizes practical and technical knowledge to solve user problems. When designing and implementing digital platform solutions in mountain agriculture, it is advisable to involve different actors: end users, machinery and equipment manufacturers, university research centers and other local stakeholders. Conclusion. The article presents the results of research on the application of digital technologies in mountain agriculture. A conceptual framework for integrating explainable artificial intelligence into digital mountain agriculture is proposed, which will serve as a practical guide for making informed decisions. The results of the study can be useful for researchers, practitioners, and educators in the field of smart agriculture.