Currently, there is sanctions pressure on the economy from Western countries. One of the global issues requiring urgent solutions is the creation of conditions for sustainable economic growth in the agro-industrial complex of the republic. In the context of global digitalization, a particularly important issue is the need for staffing IT specialists in the agricultural sector. The authors in the article analyzed topical issues in the development of information systems, digital technologies, and issues of staffing IT-specialists in the agricultural sector. The effective use of these powerful development vectors will lead to economic growth, a comprehensive solution of social problems and stable economic and food security. To improve the economic efficiency of the agricultural sector, competent personnel are needed to develop and implement new digital technologies and their rational use, which can provide future breakthrough technological processes. Of particular importance in the article is the digitalization of agricultural production, given its diversified, complex and dynamic structure of the development taking into account their direct impact on the economic efficiency of the agro-industrial complex as a whole.
Despite the steady growth in agricultural milk production, its current volumes are still not enough to fully satisfy the country's needs. In 2021, only in 33 Russian regions did agricultural milk production exceed these regions' expenditures on household consumption and industrial consumption. In the same regions, dairy exports exceeded imports. One of the main reasons behind this situation is the lack of state regulation of the distribution of agricultural production across the regions. In 2021, Udmurtia ranked second after the Altai Region in terms of surplus milk and the dairy exports from the Udmurt Republic exceeded imports 4 times. Thus, by focusing on the development of its dairy industry, the Republic has managed to achieve a high level of self-sufficiency in milk production. In 2001, in view of the region's already existing specialization in dairy farming, dairy production was chosen as one of the key priorities for its development. In Udmurtia, the dairy industry provides employment opportunities and income not only for people in rural areas but also for those employed in the milk processing sector. It also serves as a source of revenue for governments of all levels. The region’s program aimed at stimulating the development of dairy farming emphasizes innovation, in particular the use of innovative biotechnologies that can help genetically improve the livestock and smart farming technologies in the sphere of fodder production, livestock feeding, keeping, and milking. All of the above has helped the Republic to achieve steady growth in the productivity of dairy cattle and in overall dairy production.
This article analyzes the development of dairy cattle breeding in a large subject of the Russian Federation, the Vologda region in the XXI century. The main indicators of milk productivity and production volumes were studied, statistical processing of digital arrays, including correlation analysis, was carried out. It is noted that in the Vologda Oblast, as well as in the North-Western Federal District and in the Russian Federation, milk production had a positive vector of intensification of many indicators, which was associated with regional favorable conditions for the development of the industry. Which include both autochthonous (forage base) and anthropogenic factors (zoned cattle breeds, breeding work, balanced feeding). Indicators of gross dairy production, milk yield of cows, the narrative of genetic and breeding potential indicate sufficiently high regional indicators of dairy cattle breeding. Currently, enterprises with herds of dairy cattle have been established here, which are not inferior in terms of milk yield to well-known European lines. An increase in the volume of dairy products has always been given great importance, but in modern economic and sanctions conditions, an increase in the productivity of the dairy herd is becoming particularly relevant. The analysis of the development and effectiveness of the dairy industry of the Vologda Oblast makes it obvious that the region is a possible platform for the implementation of innovative methods of feed production, breeding work, increasing the genetic potential of livestock in order to disseminate the results obtained in other regions of the country.
The analysis of the economic efficiency of production on potato crops based on the results of the conducted studies shows the advantage of using liquid organomineral fertilizers, since they give significant increases relative to the control variant for all varieties studied in the experiment. When cultivating the Goryanka variety, the use of liquid organomineral fertilizer as a leaf dressing allowed to obtain the maximum level of profitability – 160.8%, which exceeded the control by 31.0%. When growing the Kislovodsk variety, the use of liquid organomineral fertilizer as a leaf dressing Polydon Bio Profi allowed to obtain the highest economic results. Use of liquid organ mineral fertilizers as a leaf dressing allowed to increase the level of profitability – 104.2%, which is 24.6% higher than the value of the control variant. According to the Ossetian variety, the use of liquid organ mineral fertilizer as Polydon Bio Profi leaf dressing made it possible to ensure a level of profitability – 97.4%, which is 21.8% higher than the value of the control variant.
Adaptation of agro-food systems to adverse climate change is a complex problem, the decisions of which must be made at different levels of the hierarchy: from the commodity producer to the regional and federal regulators. The complex interdisciplinary nature of the problem requires a variety of tools to analyze the features of the interaction between the climatic, agroecological, and production and economic subsystems, taking into account adaptive response measures. An important role in finding a way out of this problematic situation is played by methods of economic and mathematical modeling, represented by models of varying complexity and structure. At the initial stage - exploratory analysis - the tasks of studying the responses of the agro-food system, represented in an extremely aggregated form by small-scale models, come to the fore. Thus, the fundamental connections and patterns of functioning of the agro-food system, described in terms of "gross agricultural output", "agro-ecological restrictions on production volumes", "level of technological development" are revealed to the researcher. The latter, considered as an object of regulation, is to some extent capable of solving the problem of adaptive control in response to unfavorable climatic dynamics. This ability depends both on the amount of investment by the agri-food system in technological development and human capital, and on the level of state support for these same areas.
The dynamic growth of agriculture for Russia in difficult geopolitical conditions is very relevant. In recent years, the volume of agricultural production in Russia has increased, and agriculture itself has become the driving force behind the country's economic development. However, the achieved growth in agriculture does not form the conditions for sustainable development of agriculture in the long term. Thus, there is a contradiction between the increase in agricultural production and the lack of conditions for expanded reproduction in the agricultural sector. This contradiction slows down the growth of agriculture and does not allow the full use of the agricultural potential of the country. We have formed an evidence base for such a contradiction. For this, the theory of parametric management and cognitive modeling technologies were used. We parameterized agriculture and built a fuzzy cognitive model to manage the growth of agriculture. The basis for building a fuzzy cognitive model was statistical data for the period 2000-2020 and correlation-regression analysis. A static and dynamic analysis of the fuzzy cognitive model was carried out. In the course of static analysis, a parametric imbalance in the system of managing agricultural growth was revealed. During the dynamic analysis of the model, scenarios for the development of agriculture were developed. These scenarios showed that agricultural management does not create the necessary potential for agricultural growth. We come to the conclusion that for the dynamic growth of agriculture, it is necessary to change approaches to agricultural management. Thus, the need for a new quality of agricultural growth in the country was substantiated.
The article is devoted to forecasting the gross harvest of grain and leguminous crops in the regions of high-risk agriculture based on the models of cyclical fluctuations. The models of the cyclical component were built on the basis of the correlation function, the autocorrelation function, as well as using spectral analysis. We analyzed the general characteristics of the time series from 1990 till 2021 of the gross harvest of grains and leguminous plants in the regions of the Far Eastern Federal District (FEFD). On the basis of the trend and cyclical component models the forecast of the gross harvest of grains and leguminous plants in four regions of the FEFD for the period of 2022-2024 was made. In regions with a strong dependence of agriculture on natural-climatic factors, it was proposed to forecast the gross harvest of grains and legumes in three stages: to identify the overall trend, then determine the cyclical component and only at the third stage proceed with the forecasting. The result obtained by the authors for the year 2022 was compared with the results of the gross harvest in the Republic of Buryatia on the basis of preliminary data from the Ministry of Agriculture of the Republic of Buryatia and was fully confirmed. The article proposes to use these models for further research in relation to individual types of crops, as well as taking into account the influence of various factors
The article provides a methodology for typing household plots using a special model of artificial neural network – self-organizing map (SOM). To reduce the number of features and visualize the results of typing, three multivariate means are calculated based on indicators of the state of infrastructure in rural areas and logistical support, indicators of the size of crop areas and the presence of livestock. In order to stabilize the dispersions of feature values and ensure better formation of clusters as typical groups of households, sharply different feature values are determined and excluded based on the interquartile range method. Approbation of the methodology was carried out according to the microdata of household plots of the Astrakhan region of the All-Russian Agricultural Census of 2016 (VSHP-2016): eight qualitatively different and internally homogeneous groups of households in terms of size and production direction were identified. The statistical significance of the influence of the used multivariate means on the formation of clusters has been established by analysis of variance. The article compares the results of applying the SOM model and the k-means method, formulates a number of advantages and disadvantages of each of the approaches. The use of the developed typology will allow developing and implementing a differentiated state policy aimed at the inclusive development of agriculture, targeted support for household plots.
Agriculture and its economic entities are currently evaluated primarily by the volume of products produced. Such an assessment is incomplete and significantly distorts the true value of large, medium and small agricultural producers. The multifunctionality of agriculture makes it necessary to take into account all external effects and public benefits emanating from the main organizational and legal forms of organization of agricultural production. The article reveals the fulfillment of agricultural missions by large agricultural production units and rural local economy. A formula for calculating the integrated efficiency in assessing categories of agricultural producers is proposed. The assessment of the activities of large agricultural organizations, agricultural holdings and subjects of the rural local economy should combine the calculation of public goods in value terms with the determination of the external effects they produce that cannot be measured by money.
It is important to reinforce the program-target approach used by the public authorities in the management of rural development with relevant monitoring and analysis methods. The article analyzes the first results of the implementation of the State Program of integrated development of rural territories by means of the author's methodology. Taking into account the achieved level and dynamics of target indicators, the best regional practices of integrated rural development are highlighted. The Stavropol Territory, the Orel Region and the Rostov Region were three times among the best regions. Twice – Krasnodar Territory, Lipetsk Region, Kabardino-Balkarian Republic, Bryansk Region, Republic of Adygea, Republic of Crimea. Analysis of the dynamics and structure of the integrated trend of integrated rural development shows that the main positive changes in the composition of the targets of the State Program occur with the proportion of comfortable housing. This is mainly due to the fact that there are significant opportunities for the growth of this indicator. Differentiation of regions by the level of provision of rural residents with comfortable housing is significantly higher than differentiation by other target indicators. The emerging increase in the share of comfortable housing in rural settlements is the main positive result of the first two years of the implementation of the State Program for the Integrated Development of Rural Areas. In turn, monitoring changes in the actual values of target indicators in the regions allows you to form an information base for activating the "stimulation" function. It is advisable to allocate annual grants to the subjects of the Russian Federation in two categories: 1) for the achieved level of integrated development of rural territories; 2) for the best dynamics of integrated development of rural territories.