Explore the vast range of titles available.

The targeting and timeliness of financial and non-financial measures of state support for small and medium-sized enterprises in the field of agriculture within the framework of ongoing state support for entrepreneurship in the Russian Federation are currently crucial not only for a specific industry, but also for the national economy of the country as a whole, as they minimize the risks associated with the specifics of the activities of these enterprises, and make it possible to redistribute the resources released as a result of the support received to enhance the digitalization of business processes. The authors investigated the results of providing financial and non–financial support to SMEs in the Sverdlovsk region, including in the field of agriculture, received from the regional Development Institute of the Sverdlovsk region for the period from 2021 to 2023. The conclusions obtained by the authors showed the need to strengthen measures to support small and medium-sized enterprises in the field of agriculture by the state through regional development institutions, which will ensure the growth and scaling of their business and allow for a more comprehensive implementation of digitalization processes in business planning and operational management of enterprises.

The most remarkable technology brought to dairy farms by the digital transformation in agriculture is undoubtedly robotic milking systems (RMS). Knowing the economic impact of this technology is essential for farmers to adopt. For this purpose, in the study; a simulation model was created that gives possible economic analysis results as a result of the use of RMS by using the current economic analysis results of dairy farms. For the economic analysis of dairy farms, data obtained from face-to-face surveys from 148 dairy farms were used. Assumptions used in the simulation model for comparing RMS and conventional milking systems (CMS) were 8.66% increase in milk yield, 58.46% increase in investment costs, 36.66% increase in energy consumption, 1.33% increase in feed costs and 27.84% decrease in labor input. The economic analysis of the dairy farms was made again with these new input and output values obtained. While the simulation results show that the use of RMS is a preferable investment that increases profitability for 10-60 head and 121 + head groups; it shows that it will be an investment that negatively affects profitability for the 61-120 head group. The simulation model was used by taking the average values of the data belonging to the dairy farm groups. A dairy farmer considering an RMS investment can be able to obtain a result specific to his farm if he combines the simulation model with his own economic analysis results.

The underlying assumption of the study is that ERP systems can crucially facilitate information exchange; yet, the agricultural sector is slow in their adoption due to different reasons, including a shortage of skilled personnel as well as a lack of knowledge about ERP capabilities among top managers and key employees. The study intends to identify challenges and prospects for ERP implementation in agriculture. The applied methods include the analysis of WoS publications and questionnaire surveys of executives of 55 companies operating in the Middle Urals’ agricultural sector. ERP systems can be defined as comprehensive software solutions aimed to integrate business and management processes through a holistic approach and a single information system. According to expert estimates, in today’s Russia the projects related to the agro-industrial sector account for 1-2% to 10-15% of the projects from the leading ERP vendors, including 1C, Bars Group, and Navigator-Agro. ERP systems in agriculture help improve business performance, reduce and monitor costs. These systems are effective in decision-making and can serve as the basis for precision agriculture. The main barriers are poor personnel skills and competencies, shortage of funds for ERP adoption, poorly developed or absent infrastructure, difficulties of fitting and adapting of ERP systems to agricultural business. In addition, agricultural business owners show no confidence in high-tech solutions and poor knowledge of the above systems. Other problems include operation complexity and insufficient government support in ERP implementation. The results of the study can be used by government authorities in their programs for innovative development and technical upgrading of the agriculture industry.

In the context of a shortage of labor and objective patterns of the development of means of production in a number of sectors of agriculture, farmers are increasingly using robotics. Despite the presence of significant positive economic effects, the robotization of agriculture in Russia is carried out at a slow pace and is very uneven. This suggests that the robotization of agriculture is influenced by the socio-economic characteristics and characteristics of the regions. The methods are based on a systematic approach to research and an algebraic approach to modelling, which, in our opinion, is a system of several components. To build models, data on the introduction of robotics in Russian agriculture for 2006–2020 and the socio-economic characteristics of the regions during the period of the most intensive introduction of robots (2013–2017) were used. As a conclusion, it can be noted that the robotization of agriculture in the Russian Federation is at the implementation stage, which is confirmed by a significant spread in the correlation coefficient of robotization indicators and various socio-economic characteristics of the regions, including the share of organizations using the Internet, availability of road infrastructure, the share of the rural population in the regions and a number of other indicators. It is shown that, at this stage of the robotization of agriculture, the most important are the models of the management process, while the priority is the subjective component of decision-making about the introduction of robotics, both at the micro level and at the regional level. We have proposed models that reflect various aspects of the robotization process and three mathematical models for the implementation of the strategy are built, which form a model-triad. Three theorems on the existence of an optimal realization of the strategy are proved.

The paper analyses the prospects of applying artificial intelligence (AI) technologies in agriculture of Sverdlovsk oblast. This topic is currently relevant, as in the context of the rapid technological development and various innovations in the digital sphere; there is still considerable uncertainty about using AI in agricultural production. During the preparatory phase, an analysis of publications in the Web of Science (WoS) allowed to identify the nature and scope of the application of AI technologies in agriculture. Relying on a survey of managers from 55 agricultural organizations, the study determines the problems and prospects of using AI technologies in the regional agriculture. The respondents claim it is appropriate to use AI technologies for producing livestock products (26.0 %) and ensuring animal welfare (18.5 %). Considering the application of such technologies, the respondents expect an increase in production (23.2 %) and a decrease in costs (20.3 %). More than half of the respondents express their belief that AI technologists will significantly change agricultural production, reducing low-skilled labour employment while creating new jobs in the intellectual sphere. However, a positive perception of AI technologies may be the reason for somewhat unrealistic expectations from their use. A large part of the surveyed managers (65.5 %) presumes that these technologies will increase the production profitability, even though only 9.8 % of the respondents are currently using them. The application of AI technologies in the regional agriculture is limited due to their high cost and the lack of funds. In order to overcome these constraints, it is necessary to increase state support and train staff. AI technologies will enable forecast accuracy in various areas of agriculture that will attract additional investments in the regional agriculture. Executive authorities can use the research results for creating programs of digital agriculture development.

The paper analyses the prospects of applying artificia l intelligenc e (AI ) technologie s i n agricultur e o f Sverdlovs k oblast. This topic is currently relevant, as in the context of the rapid technological development and various innovations in the digital sphere; there is still considerable uncertainty about using AI in agricultural production. During the preparatory phase, an analysis of publications in the Web of Science (WoS) allowed to identify the nature and scope of the application of AI technologies in agriculture. Relying on a survey of managers from 55 agricultural organizations, the study determines the problems and prospects of using AI technologies in the regional agriculture. The respondents claim it is appropriate to use AI technologies for producing livestock products (26.0 %) and ensuring animal welfare (18.5 %). Considering the application of such technologies, the respondents expect an increase in production (23.2 %) and a decrease in costs (20.3 %). More than half of the respondents express their belief that AI technologists will significantly change agricultural production, reducing low-skilled labour employment while creating new jobs in the intellectual sphere. However, a positive perception of AI technologies may be the reason for somewhat unrealistic expectations from their use. A large part of the surveyed managers (65.5 %) presumes that these technologies will increase the production profitability, even though only 9.8% of the respondents are currently using them. The application of AI technologies in the regional agriculture is limited due to their high cost and the lack of funds. In order to overcome these constraints, it is necessary to increase state support and train staff. AI technologies will enable forecast accuracy in various areas of agriculture that will attract additional investments in the regional agriculture. Executive authorities can use the research results for creating programs of digital agriculture development.

At present, the entities of the agrarian sector are moving towards the digital, intellectual and robotic technologies or the robotization of the industry. Robotics is used in the various fields of the agrarian sector, the most widespread is the milking robotics. From 2006 to 2016, in the agricultural enterprises of the Russian Federation, 393 units of robotics were introduced. While in the Sverdlovsk region at the beginning of 2018, 37 units of this equipment have been used. We suggest to use the indicator of “density of agricultural robotization” to characterize the effectiveness of the transition to robotics. This indicator for Russia increased from 0.02 to 0.78 units, and for the Sverdlovsk region — from 0.3 to 3.17 for the periods under review. However, the slowdown and low values of the density of agricultural robotics make it necessary to develop appropriate measures. The article proposes a model of an organizational and economic mechanism for the transition to robotics. It includes target, investment, technical and technological as well as personnel sections. The initial data on the state of the introduction of robotics in agricultural organizations was provided by the ministries and departments, as well as statistical bodies. We determined scenarios of inertial, targeted and system development of robotics in agriculture depending on the level of state support. We have determined that the investments needed for the robotization of agricultural enterprises in the Sverdlovsk region are at the level of 472 million rubles. Moreover, we have formulated the tasks, recommendations and the expected result from the training of personnel capable to master robotics in the industry. The most important measure is the reduction in the cost of this equipment due to its domestic production. The results of the research can be used by the executive authorities in developing programmes for the innovative development and technical modernization of agriculture.

At present, the entities of the agrarian sector are moving towards the digital, intellectual and robotic technologies or the robotization of the industry. Robotics is used in the various fields of the agrarian sector, the most widespread is the milking robotics. From 2006 to 2016, in the agricultural enterprises of the Russian Federation, 393 units of robotics were introduced. While in the Sverdlovsk region at the beginning of 2018, 37 units of this equipment have been used. We suggest to use the indicator of “density of agricultural robotization” to characterize the effectiveness of the transition to robotics. This indicator for Russia increased from 0.02 to 0.78 units, and for the Sverdlovsk region — from 0.3 to 3.17 for the periods under review. However, the slowdown and low values of the density of agricultural robotics make it necessary to develop appropriate measures. The article proposes a model of an organizational and economic mechanism for the transition to robotics. It includes target, investment, technical and technological as well as personnel sections. The initial data on the state of the introduction of robotics in agricultural organizations was provided by the ministries and departments, as well as statistical bodies. We determined scenarios of inertial, targeted and system development of robotics in agriculture depending on the level of state support. We have determined that the investments needed for the robotization of agricultural enterprises in the Sverdlovsk region are at the level of 472 million rubles. Moreover, we have formulated the tasks, recommendations and the expected result from the training of personnel capable to master robotics in the industry. The most important measure is the reduction in the cost of this equipment due to its domestic production. The results of the research can be used by the executive authorities in developing programmes for the innovative development and technical modernization of agriculture.

This study focuses on the development of environmentally sustainable polypropylene (PP)-based composites with the potential for biodegradability by incorporating cellulose and the oligomeric siloxane ES-40. Targeting industrial applications such as fused deposition modeling (FDM) 3D printing, ES-40 was employed as a precursor for the in situ formation of silica particles via hydrolytic polycondensation (HPC). Two HPC approaches were investigated: a preliminary reaction in a mixture of cellulose, ethanol, and water, and a direct reaction within the molten PP matrix. The composites were thoroughly characterized using rotational rheometry, optical microscopy, differential scanning calorimetry, and dynamic mechanical analysis. Both methods resulted in composites with markedly reduced crystallinity and shrinkage compared to neat PP, with the lowest shrinkage observed in blends prepared directly in the extruder. The inclusion of cellulose not only enhances the environmental profile of these composites but also paves the way for the development of PP materials with improved biodegradability, highlighting the potential of this technique for fabricating more amorphous composites from crystalline or semi-crystalline polymers for enhancing the quality and dimensional stability of FDM-printed materials.

Most characterised metazoan mitochondrial genomes are compact and encode a small set of proteins that are essential for oxidative phosphorylation. However, in rare cases, invertebrate taxa have additional open reading frames (ORFs) in their mtDNA sequences. Here, we sequenced and analysed the mitochondrial genome of a polychaete worm, Polydora cf. ciliata, part of whose life cycle takes place in low-oxygen conditions. In the mitogenome, we found three 'ORFane' regions (1063, 427, and 519 bp) that have no resemblance to any standard metazoan mtDNA gene but lack stop codons in one of the reading frames. Similar regions are found in the mitochondrial genomes of three other Polydora species and Bocardiella hamata. All five species share the same gene order in their mitogenomes, which differ from that of other known spionidae mitogenomes. By analysing the ORFane sequences, we found that they are under negative selection pressure, contain conservative regions, and harbour predicted transmembrane domains.The codon adaptation indices (CAIs) of the ORFan genes were in the same range of values as the CAI of conventional protein-coding genes in corresponding mitochondrial genomes. Together, this suggests that ORFanes encode functional proteins. We speculate that the ORFanes originated from the conventional mitochondrial protein-coding genes which were duplicated when the Polydora/Bocardiella species complex separated from the rest of the Spionidae.Competing Interest StatementThe authors have declared no competing interest.