Based on GIS technologies, a decision support system (GIDSS) has been developed to remediate agricultural lands in the Bryansk region (Russia) contaminated by 137Cs after the accident at the Chernobyl nuclear power plant. GIDSS is a multilevel system consisting of basic, information and computational layers. GIDSS allows justifying a targeted approach for the remediation of agricultural lands belonging to agricultural enterprises for the production that meets the established radiological requirements for the content of radionuclides.

The article presents indicators of the agricultural industry management system: doing business in a digital and technological transformation from the perspective of an ontological approach. It is important to note that it is impossible to transform under the requirements of the modern world without the introduction of innovation. However, innovation is always marked by financial costs and loss of time, which reduces the innovative activity of organizations in the agricultural sector, and, therefore, determines the diagnosis of innovation and investment policy.

The article emphasizes that for the innovative development of the Russian agricultural industry and ensuring the national food security, it is necessary to create a research and development sector in the field of food production; reform the education system for the innovative development of the agricultural industry; re-equip the agricultural industry; build a system of agricultural advisory support for producers; create an intellectual property protection system; improve legal standards for regulating innovation, research and development; pay attention to the needs of agriculture and agro-

The task of creating a single supranational payment market is to ensure its maximum independence, which correlates with the tasks of the competitive leading economic development of countries - the transition to a digital technological structure. To increase the efficiency of the generation of payment innovations with their subsequent diffusion into the agricultural sector, to strengthen the economy’s resistance to risks, a transfer of innovative institutional, organizational and informational forms of activity is necessary.

In terms of macroeconomic and geopolitical instability, in order to increase the competitiveness of agro-food complex of the Russian Federation in world food markets, a scientifically based choice of institutional solutions is required to increase innovative activity in the agricultural sector and to ensure the transfer of technologies used in industries related to agriculture.

In recent years, the international status of agriculture in the BRICS countries—Brazil, Russia, India, China and South Africa—has been continuously improved. In 2018, the gross agricultural production of the BRICS countries accounted for more than 50% of the world’s total. Further strengthening the developing cooperation of the BRICS countries is of great significance for ensuring global food security.

The level of developed countries in the conditions of global competition and open economy in terms of well-being and efficiency cannot be reached, unless the advanced development of the sectors of the economy that determine its specialization in the world economic system is ensured. This will make it possible to actualize national competitive advantages to their maximum.

In this paper, introduction presents the problem statement. The second chapter gives a brief description of the Smart Farming system. The third chapter provides an overview of ontologies. The fourth chapter describes implementation of the knowledge base in the Smart Farming system. The fifth chapter presents the main functions of the ontology editor for working with the knowledge base. Conclusions and prospects of further development of knowledge base in crop production are also given

This research examines the transformation of the agro-climatic conditions of the Altai region as a result of climate change. The climate of the Altai region in Russia is sharply continental and characterized by dry air and significant weather variability, both in individual seasons and years. The current study is determined by the lack of detailed area-related analytical generalizations for the territory of the Altai region over the past 30 years.