The article examines the spatial features of localization and concentration of grain production in the border regions of the Russian Federation and the Republic of Belarus in the context of ensuring food security and sustainability of the integration space of the Union State. The relevance of the study is due to the increasing role of internal sources of development, the transformation of logistics chains and the increasing importance of food security as one of the key elements of the economic security of the state. The purpose of the study is to assess the degree of localization and concentration of grain production in the border regions of Russia and Belarus, as well as to determine their role in ensuring food security. The methodological basis of the work is based on the approaches of spatial economics, new economic geography and regional analysis. The localization coefficient (LQ) and the Herfindahl–Hirschman index (HHI) was used as tools. The analysis covers the dynamics of acreage, gross harvest of grain and leguminous crops, yields, as well as structural shifts in the agricultural sector. It is concluded that the "grain belt" of the Union State is formed not as a continuous space, but as a system of individual specialization nodes with varying degrees of involvement in the grain sector. The link between the localization of agricultural production and food security is manifested in the formation of support areas of production and the simultaneous reduction of risks due to moderate concentration. The results obtained confirm that the development of grain specialization in the border regions is determined by a combination of climatic, structural, logistical and cooperative factors and should be taken into account in the formation of agricultural and integration policies.
This article presents a comparative analysis of agricultural export risk insurance practices in the United States, China, Brazil, Germany, and South Africa. The objective of the study is to identify positive international practices applicable to improving the Russian agricultural export insurance system. The article presents the results of a study of data from authorized government agencies in these countries, national export credit agencies, and insurance companies, as well as statistical data from relevant UN organizations–the OECD, WTO, and FAO–for 2022–2025. It is established that the United States and China have the most developed agricultural export risk insurance systems. However, key shortcomings are identified: high budget expenditures in the United States, low coverage of insured areas in Brazil and South Africa, and the lack of specialized agricultural programs in Germany. The article concludes with recommendations for possible implementation in Russia: the implementation of a climate zoning system based on the Brazilian ZARC model, expansion of EXIAR's authority in agricultural export insurance, the creation of an agricultural insurance stabilization fund, and the integration of ESG environmental standards into the export insurance system.
The article presents a methodology for assessing the intensity of digitalization across various segments of the livestock industry by constructing digital profiles. For the period 2021–2024, the study identifies a stagnation in the number of organizations adopting digital technologies and specialized software, alongside a simultaneous increase in total ICT budgets. This trend indicates an intensification of digitalization among existing adopters rather than market expansion. The measurements obtained indicate a pyramidal structure of digitalization: precision livestock technologies and a class of operational efficiency software tools are in much less demand than infrastructure and basic tools. The study reveals heterogeneity in digital strategies: the pig farming sector implements a model with a pronounced shift towards outsourcing, likely due to the concentration of ICT functions within subsidiary holding companies; the poultry industry is undergoing a phase of large-scale technical re-equipment; meanwhile, the dairy farming, unlike the global trend, has not shown itself as a leader in digitalization and changes priorities every year. Budgetary pressure on organizations varies significantly by segment due to production concentration and digital investments are mostly in the hands of large players, creating a system risk of technological inequality. Pig farming is the absolute leader of digitalization in Russian livestock farming industry in terms of the potential used at all levels of the digital hierarchy, with poultry farming in second place and dairy cattle in third. Two system challenges were identified: critical underfunding of employee competence and a lack of attention to cybersecurity.
In today's environment, artificial intelligence (AI), a set of technologies that mimic individual aspects of human thinking and behavior, is evolving into a powerful tool for supporting corporate management decisions. It enables companies to assess not only their current status but also formulate long-term strategies based on predictive models. Using the example of Agrofirm Svoboda CJSC, we propose a comprehensive model for using AI to improve the validity of management decisions, forecast key financial indicators, manage risks, conduct strategic planning and scenario modeling, and generate reports, forecasts, and possible scenarios online, facilitating the work of specialists. Overall, this article examines the importance of AI in improving the efficiency of agricultural production and proposes promising areas for its development, combining the latest technologies with the current conditions and needs of agricultural producers. This will enable Agrofirm Svoboda CJSC to apply innovative management approaches, making the company a leader in its industry, and AI will become a key data provider for strategic decisions.
The article examines the impact of artificial intelligence technologies on the development of the agro-industrial complex of the Russian Federation and individual regions under the Strategy for the development of the agro-industrial and fishery complexes until 2030. Based on data from Rosstat, the Ministry of Agriculture of Russia, Rosselkhozbank, the Skolkovo Foundation and Agroexport for 2021–2025, the study analyses the dynamics of the share of agricultural organisations using artificial intelligence technologies, compares the sectoral structure of digitalisation costs, and identifies barriers and drivers of artificial intelligence diffusion at the regional level. Despite the growth of aggregate expenditures of agricultural organisations on digital technologies, the share of organisations using artificial intelligence has decreased from 3,1 % in 2021 to 1,9 % in 2024, while artificial-intelligence-based solutions are deployed in only 15 out of 72 regional public agro-industrial management units. The authors conclude that the introduction of artificial intelligence in the agro-industrial complex provides substantial growth potential for industry gross value added, provided that state support measures are differentiated by regional groups and a coherent digital infrastructure for sectoral management is developed.
Agricultural enterprises, like the entire agricultural sector of the country, are not without the influence of negative factors and risks that affect all areas of activity: from production issues to logistics and product processing. For more than a year, the authorities have been taking measures to reduce the impact of such risks and threats within the framework of state agrarian policy through the implementation of national projects and programs for the development of agriculture. However, it is quite difficult to assess the level and effectiveness of the measures and tools being taken. The reasons may be the specific features of agricultural production, as well as the rapidly changing conditions of agribusiness, as well as the trade and economic climate in the agri-food market. The purpose of the study is to propose methodological provisions for assessing the methods and tools of the risk management system used in practice for the development of the agro-sector within the framework of state agrarian policy in the context of the functioning of the agricultural production structure in modern economic conditions. The research was based on the application of a systematic approach, the main research methods were abstract-logical, monographic, morphological, institutional analysis and synthesis. The results of the conducted research allowed us to propose methodological provisions for assessing the level of risk management for the development of the agricultural structure of the Russian Federation, including a number of stages. Initially, it is necessary to determine the choice of the purpose and object of the assessment, which will indicate the range of tasks to be solved. Next, a system of evaluation criteria and indicators is defined, optimal assessment methods are selected, as well as the necessary information, statistical data and analysis of available information are collected to form conclusions about the results and effectiveness of the applied risk management methods. At the same time, it is necessary to take into account the influence of internal and external factors of the development of the object under study, which can determine the choice of evaluation criteria and methods when adjusting and changing the objectives of the assessment.
In the context of sanctions pressure and the need to ensure food sovereignty, technological modernization is becoming an imperative for the development of the agricultural sector of key regions, which include the Altai Territory. The purpose of the study is a comprehensive analysis of the effectiveness of the technological modernization of agriculture in the region and the identification of systemic restrictions that constrain this process. The methodological base includes a systematic approach, economic and statistical analysis, panel regression modeling and machine learning methods (Random Forest, XGBoost). The information base was compiled by data from Rosstat, the Ministry of Agriculture of the Altai Territory and the results of a sample survey of 50 agricultural organizations. The article diagnosed the critical state of resource potential: the level of depreciation of fixed assets (48%) exceeds the national average, and the structural imbalances of the fleet create a "bottleneck effect" with an annual damage of 3.5-5.2 billion rubles. Positive, but different-speed dynamics of efficiency was revealed, accompanied by an increase in technological inequality (the differentiation coefficient for digitalization between large and small farms reaches 13.0). Using econometric modeling, the "paradox of the Altai Territory" was proved - the dominant role of state support (β=0.41) and the level of wages (β=0.38) as key drivers of modernization in conditions of chronic underfunding. The presence of a synergistic effect between state support and digitalization has been established (interaction effect 0.31). The need for a transition to a differentiated organizational and economic mechanism that implements the principle of "support for the request of the cluster" is justified.
The prospects for the development of any industry are associated with an increase in economic efficiency. This is especially important for industries with natural limitations. Such activities include horticulture. An increase in the production of this industry is possible due to the involvement of new lands in the turnover, increasing the yield of agricultural crops, and optimizing the structure of the industry. This article presents the results of an assessment of the use of almost half of Russia's acreage (46% of this area is in 10 regions, on the example of which this study was conducted). The effectiveness of crop production was assessed based on the dynamics of the average five-year yields of the main types of crops. The analysis showed that in 2001-2024 the contribution of the 10 subjects with the largest sown area to the production of crop production increased, but remains significantly lower than their combined share in the area of crops - the total share of the regions of this group in the total Russian volume of crop production increased from 36% to 40%. At the same time, significant reserves remain for expanding production, both due to extensive and intensive factors. Experts and Rosstat data indicate a reduction in the area of crops in most regions. A significant decrease in the yield of grain and leguminous crops in 2001-2024 occurred in the Republic of Tatarstan, the Republic of Bashkortostan, and the Omsk region. Potato yields have also decreased in the Omsk region.Although the yields of other types of crops increased in 2001-2024, in most regions, which together account for almost half of the country's arable land, the yields of most types of crops are significantly lower than the national average. Increasing yields and optimizing the structure of the industry in regions with the largest sown area can ensure significant growth in crop production, which is important both for domestic consumption and for export purposes. The results obtained can be used by experts in the field of agronomy to assess the prospects for the development of crop production and optimize the structure of the industry in Russian regions.
The article is devoted to a quantitative assessment of the changes that have occurred over the past five years in the rating structure of Russia's largest landowners, as well as in the total amount of their land resources. The analysis of changes in the group of the largest owners of agricultural land over the past five years (2021-2025) has been carried out, trends in the formation of the composition of the rating participants, as well as some of its structural characteristics, have been identified. The trend towards a reduction in the number of companies newly included in the ranking of the largest landowners has been revealed. It has been established that every year it becomes more and more difficult for new companies to enter the rating, and the rating itself stabilizes in terms of the composition of participants. Based on the analysis of domestic and foreign publications, the factors contributing to the increased concentration of land and hindering this process have been identified. The analysis of changes within the rating caused by a relative shift in the positions of its participants, without taking into account the replenishment of the rating by new participants, is carried out. It is established that, despite the growth of the land bank of companies in the rating, its structure remains constant. Significant changes are taking place within the groups of rating participants. The greatest changes are noted in the middle part of the rating; there is a slight tendency to smooth out changes over the years in these groups.
The labor market in rural areas is changing under the influence of technological transformations taking place in the agricultural industry. As a result, the structure of the rural economy is changing: the share of the rural population engaged in agriculture is decreasing, and the share of those employed in non-agricultural activities is growing. In the rural labor market, an imbalance was noted due to the vocational and qualification mismatch between the demand for labor and its supply in the agricultural sector. In the presence of a shortage of personnel in the agro-industrial complex (AIC) of Russia, rural employment is declining. The study showed that the rural labor market in the regions of Russia is significantly differentiated by such indicators as: economic activity of the rural population, employment rate, unemployment rate, average wages in agriculture, etc. In a number of regions of the country, with high wages in agriculture, there is an acute shortage of personnel in the agro-industrial complex. This indicates that the key mechanism of market regulation of the labor market, the price of labor, does not always work. In problem regions, on the contrary, the rural labor market has a low level of employment, high unemployment and low wages in agriculture, which is associated with poor development of the rural economy and lack of competition among employers for labor. Significant regional differentiation of rural labor markets requires improving the mechanisms of their state regulation, taking into account the characteristics of individual regions. The work proposes key tools for the mechanism of state regulation of the provision of personnel for the agro-industrial complex, which will reduce the personnel need for qualified workers.