Gears, which are subject to intense abrasive wear due to their operation in dusty environments due to insufficient sealing of internal cavities, limit the service life of gear drives and transmissions in agricultural machinery. The aim of this study was to investigate and analyze changes in engagement characteristics and their impact on the kinematics of heavily loaded gear drives in conditions of abrasive wear. The study was conducted using a casting method to record the relative positions of profiles. Simultaneously, strain gauge measurements were performed to determine the start and end of engagement of a pair of teeth and to establish the overlap coefficient. Rotation angles were recorded using optical dividing heads. Spur gears with modules m=2-5 mm were tested without shifting the original contour (heat treatment - normalization and bulk hardening HRC38-400; the number of gear teeth z1=12 -30, z2=22-90. Gear material - steel 40X, wheel - steel 45. It was found that during abrasive wear of highly loaded gears, the shape of the tooth profile changes mainly in the initial period of wear when its value is 5-8%. The amplitude of oscillations during wear increases, especially in the initial period. As wear increases, the increase in the amplitude of oscillations slows down and when the wear of gear teeth is over 12-16%, the amplitude stabilizes. The increase in amplitude of oscillations with an increase in modulus e increases. Oscillations during wear can reach a significant value: at wear of 16% or more with a small number of gear teeth, the increase in amplitude reached 130%. It was found that the engagement line of the gear becomes distorted with wear. The start and end points of engagement shift along the direction of rotation of the gears. The overlap ratio decreases with wear and, at wear levels exceeding 10-14%, stabilizes within the range of 1.03-1.1. A mathematical model of the gear ratio function depending on the degree of wear has been developed.
In the context of increased turbulence in the global economic system, issues related to the development of models assessing the impact of import vulnerability on the development prospects of regional and industrial complexes have become increasingly relevant. Despite the relatively high level of elaboration of this research question, it should be noted that further development of methodological approaches in this area is necessary. Greater attention is required to the development of such models, with a focus on the regional and industrial research levels. Furthermore, the increasing blockade of access to foreign markets for a number of countries necessitates the adaptation of methodological tools for studying import substitution factors and their inclusion in the design of industrial development models. Based on the factors examined, the study identified the sensitivity of agro-industrial sector of the Republic of Tatarstan to adjustments in critical imports used in the economic activities of agricultural enterprises in the region (the Republic of Tatarstan). Using multivariate analysis methods, the HS nomenclature group 8433 “Machines or mechanisms for harvesting or threshing agricultural crops, including balers, presses for packing straw or hay into bales; mowing machines or lawn mowers; machines for cleaning, sorting, or grading eggs or fruit” was assigned to this category. It was found that a 1% reduction in imports of the studied product nomenclature entails a 0.39% decrease in the volume of shipped goods of own production in the agro-industrial sector of the studied constituent entity of the Russian Federation. Elements of scientific novelty are expressed in the author’s approach to identifying critical imports for the regional agricultural sector and, based on this, developing a predictive model for the sector’s development, taking into account potential risks in the form of supply restrictions for critically important commodities.
Research to evaluate promising spring soft wheat lines was conducted in 2022-2025 in Kama zone of the Republic of Tatarstan on gray forest medium-loamy soil. The study objects were lines provided by Russian State Agrarian University – Timiryazev Agricultural Academy to Kazan State Agrarian University for environmental testing in middle Volga region. Based on the results of 2022-2024 years evaluation, two lines were retained for further use in breeding. This paper presents the economic and biological characteristics of the selected lines, which are promising for the conditions of the Republic of Tatarstan. The standard is Yoldyz variety, bred by Kazan Federal Research Center of the Russian Academy of Sciences. Field trials were conducted according to the State Variety Testing methodology (plot area 20 m2, 3 replicates, NPK background of 106 kg active ingredient/ha). Phenological observations and yield measurements were made, root rot and powdery mildew infestation, plant lodging and grain quality were coducted. In 2024, during the heading period, 90% of plants of standard Yoldyz variety were affected by root rot, with the disease development at the base of the stem and underground internode amounting to 7.36% on average. For Line 15 – 50% of plants were affected, with the disease development rate being 5.25%. In 2025 Line 10 had the lowest development (2.75%). These two lines also surpass the standard in terms of powdery mildew resistance. In 2025 powdery mildew affected up to 8.0% of the leaf surface in 100% of Line 10 plants, and up to 5.5% in 70% of Line 15 plants. Line 10 was the most productive over the years of testing (3.85 t/ha), exceeding the standard by 21.8%. The productivity is relatively stable over the years, decreasing less than other varieties in unfavorable years and the variety shows responsiveness to improving environmental conditions in favorable years. The grain is distinguished by increased protein content (14.9%), wet gluten (26.0%), with an average 1000-kernel weight of 39.3 g and a natural weight of 768 g/l. Line 10 is recommended as a source of valuable economic traits in breeding for the conditions of middle Volga region. The breeding value of Line 15 is due to increased immunity and the ability to form large grains in arid conditions.
Global production of essential oil crops is demonstrating stable growth, driven by increasing consumer demand for natural and organic products. In Russia, the cultivation of essential oil crops is an integral part of domestic agriculture, however, despite the historical significance and potential for development, Russia’s share of global production is only approximately 2-3%. Meanwhile, the country’s territory is suitable for growing approximately one-third of all essential oil crops worldwide. Since 2014 Russia has significantly increased the area under essential oil crop cultivation (from 38 000 to 107 000 hectares). This had a positive impact on the production of essential oil seeds (an increase from 36 000 to 115 000 tons) and the economic attractiveness of this industry. Sustainable development of the essential oil industry requires rational use of land resources, with particular attention to the integration of undeveloped and underutilized lands into agricultural production. Russia’s 43.3 million hectares of land, of which 31.8 million hectares (73.4%) are agricultural lands, are located in the mountainous and slope areas of the Republic of North Ossetia-Alania. The unique climate and soil conditions of the Republic of North Ossetia-Alania offer significant potential for essential oil crops cultivation. Essential oil plants such as basil, tarragon, thyme, lavender and other aromatic herbs are highly adaptable to arid soils unsuitable for traditional farming. Developing essential oil production based on rational land management in the Republic of North Ossetia-Alania will optimize agricultural land use, increase productivity, prevent soil degradation and enhance the environmental sustainability of agricultural landscapes. This will significantly strengthen the region’s agricultural potential, enhance its investment attractiveness and ensure the long-term sustainable development of the industry.
The study was conducted to assess the biochemical composition of 18 domestically bred potato varieties used in chip production in Western Siberia. The work was conducted from 2022 to 2024 in Novosibirsk region. Lady Kler variety, which is widely used in the chip industry, was selected as the standard. The soil of the experimental plot was medium-deep leached chernozem. The experiment was established and records were collected according to All-Russian Research Institute of Potato Crops (VNIIKh) methodology. Biochemical assessment of tubers was performed according to A.I. Ermakov’s method, the quality of the crispy potato slices was assessed visually using HunterLab scale. Meteorological conditions during the study years were significantly variable, with alternating periods of deficient and abundant moisture throughout the growing season. Average yields exceeding 29 t/ha were observed for Evpatiy (29.4 t/ha), Bashkirskiy (29.9 t/ha) and Argo (29.9 t/ha) varieties. Samorodok (Ka = 1.42), Shakh (Ka = 1.41) and Evpatiy (Ka = 1.17) varieties were distinguished based on the adaptability coefficient (Ka), which are characterized by high productivity and tolerance to regional conditions. The highest dry matter content was observed in Nadezhda (29.24%), Artur (28.29%) and Vychegorskiy (28.60%) varieties, while the highest starch content was found in Vychegorskiy (19.12%) and Artur (17.85%). The lowest reducing sugar content (0.22%), which ensures the light color of chips, was found in Evpatiy, Artur and Rozovyy Charodey varieties. Evpatiy, Artur and Nadezhda (9 points) were the leaders in terms of suitability for processing into chips. Evpatiy variety (dry matter 25.21%, sugars 0.22%, yield 29.4 t/ha) is the most promising alternative to Lady Kler. Arthur and Nadezhda varieties are also suitable for chip production, but their cultivation requires optimized agricultural practices to increase productivity.
Air pollution by industrial dust at agricultural enterprises has a multifaceted negative impact, posing a direct threat to personnel health, reducing the service life of equipment and increasing the risk of environmental emergencies. Existing cleaning methods, especially for particles smaller than 10 µm, are often ineffective or energy-intensive. The aim of this study is to provide a comprehensive theoretical justification and develop analytical models for evaluating the efficiency of a new gas-liquid vortex separation device with a tangential vane swirler, combining centrifugal and inertial cross-flow separation mechanisms. Based on an analysis of particle trajectories and mass transfer equations, analytical relationships were developed that allow us to predict the fractional separation efficiency depending on the gas (G) and irrigating liquid (L) flow rates. It was found that efficiency of centrifugal separation is critically dependent on the L/G ratio: increasing the liquid feed reduces flow swirl. Thus, for particles with a diameter of 10 µm, with an L/G ratio of 0.12, the efficiency reaches 80%, but drops to 18% at L/G = 0.47. At the same time, the efficiency of inertial sedimentation on liquid droplets depends on the liquid load, demonstrating a positive correlation with particle size. Increasing the liquid flow rate from 21 to 168 kg/h increases the efficiency of the inertial mechanism for 10 µm particles from 56% to 94%. Calculation of the overall separation efficiency confirms the high potential of the device for capturing a wide fractional composition of industrial dust. The developed models and obtained results provide the basis for designing highly efficient dust removal systems specifically tailored to the conditions of the agro-industrial complex, particularly for feed production and grain processing plants.
Development of microbiota management methods to optimize plant biological productivity is a promising area of modern agriculture. The aim of this study is to analyze changes in the number of various ecological and trophic groups of microorganisms in the rhizosphere and evaluate the productivity of winter triticale using microbial supplements. The study was conducted from 2021 to 2023 in Leningrad region on Bilinda winter triticale plants. The experimental scheme included the following options: no inoculation (control), Agrofil (Agrobacterium radiobacter, strain 10), Mizorin (Arthrobacter mysorens, strain 7), Flavobacterin (Flavobacterium sp., strain 30), Rizobact RZhF (Corynebacterium sp., strain PBT 7), MZhF (Enterobacter sp., strain PBT 3), FZhF (Pseudomonas sp., strain PBT 4), and N100. Seed inoculation was carried out on the day of sowing with a suspension based on preparations with a titer of 5×109 CFU/ml and a rate of 1 l per 1 ton of seeds. Soil samples were taken from the rhizosphere zone during tillering, booting and milky ripeness phases. The soil of experimental field was sod-podzolic medium loamy. Meteorological conditions during the study years varied in moisture and temperature, but were favorable for grain formation and maturation. The highest numbers of ammonifiers and actinomycetes were recorded with Flavobacterin and Rizobact FZhF brand, while cellulose-degrading microorganisms were active with Mizorin and Rizobact RZhF brand. High numbers of microscopic fungi were observed in the RZhF and MZhF Rizobact variants. The highest number of phosphate-mobilizing microorganisms was recorded with Rizobact FZhF. All treatments showed an increase in the total number of oligotrophs compared to the control. The highest number of spikelets, grains and their weight were observed in Mizorin treatment. The increase over the control was 9.8%, 27.3% and 33%, respectively.
The study and conservation of cotton genetic resources is crucial because the species and varietal diversity of collection accessions serves as the basis for the effective development of crop production. The aim of this study is to identify promising cotton samples with colored fiber by examining the collection material of N.I.Vavilov All-Russian Institute of Plant Genetic Resources. The study was conducted from 2019 to 2021 on an irrigated plot in Astrakhan region. Cotton samples, provided by N.I. Vavilov All-Russian Institute of Plant Genetic Resources were: 6C with light-brown fiber; 1C, 10C, 11/15 and 32/3 are green, C11-F is beige-green. The standard variety was Braun with cream-colored fiber. The soil of the experimental plot was light chestnut, heavy loamy, the humus content in 0-20 cm layer was 1.12%. The productivity of Braun standard variety varied over the years from 1.5 to 4.2 t/ha, 6C - from 1.6 to 3.2; 1C - from 1.3 to 2.7; 10C - from 0.5 to 2.9; C11-F - from 1.0 to 2.6; 11/15 - from 0.6 to 3.2 and 32/3 - from 0.7 to 2.0 t/ha. Braun variety, 10C and 11/15 samples were identified as the most flexible and simultaneously most stable across the years of study.
Research on precision farming technologies implementation at Stavropol State Agrarian University, conducted from 2012 to 2025, revealed high variability in the concentration of key nutrients within a single field. An analysis of scientific research revealed that there are no solutions for field-based fertilizer mixing using a specialized unit, equipped with three compartments for storing single-component mineral fertilizers with individual dispensers, ensuring precise dosing of each element with simultaneous application. The aim of this study is to develop an algorithmic model for an automated control system for simultaneous dosing of fertilizer mixture nutrients for pneumatic boom spreaders. Methodology included field experiments with automated sampling, NPK mapping in AGRO MAP and development of a dosing system for three fertilizers for a pneumatic unit. An algorithm with an error of Δ = 3–5% was developed. Simulation modeling was performed in Python (PID controller, Ziegler–Nichols method) for speeds of 5-25 km/h and densities of 900–1300 kg/m3 (225 calculations) with the construction of error maps. The modeling results showed that the system ensures that the actual flow rate returns to the set value within the permissible error (Δ = 3–5%) within no more than 3 seconds after the onset of a disturbance. Parametric modeling across a speed range of 5-25 km/h and bulk densities of 900-1300 kg/m3 confirmed the algorithm’s robustness: the average dosing error was 2.9%, the maximum was 4.7% and the 5% tolerance was less than 2%. Using a closed-loop system reduces the average dosing error from 15-20% (for traditional open-loop systems) to 3–5%, which meets agronomic requirements. The control system with developed algorithm enables verification and adjustment of both the total application rate and the application rate of each NPK component individually.
Production cost management in agricultural enterprises based on digital platforms is a set of measures aimed at improving agribusiness efficiency through the analysis of large volumes of data obtained using modern information collection and processing technologies. Modern agriculture faces numerous challenges, including declining yields, high production costs and inefficient use of resources. The authors propose a new classification of cost items adapted to the specific needs of agricultural enterprises, including detailed indicators of the stages of the process chain in crop and livestock production. This information is generated exclusively by digital methods and specialized programs, such as the Russian “Galaktika ERP” system. Use of digital platforms allows us to address these challenges by optimizing production processes, reducing costs and increasing the competitiveness of agricultural enterprises. The study is based on the analysis of data collected using sensors, satellite imagery, drones and automated production management systems. Key areas include: automated material resource accounting; monitoring crop and livestock conditions; forecasting fertilizer and plant protection product requirements; and optimization of logistics operations. Digital technologies reduce fuel, electricity and labor costs and minimize the risk of crop losses. The use of digital platforms contributes to a significant reduction in production costs, improved quality of agricultural products and increased profits for agricultural enterprises. The study confirms the effectiveness of implementing digital solutions in agriculture and emphasizes the need for further development of relevant technologies. Thus, cost management in production is becoming an important tool for sustainable agricultural development, contributing to solving global food problems and ensuring environmental sustainability.
Sustainable development of rural areas is constrained by an imbalance between the economic efficiency of agro-industrial complex and the population’s quality of life, which triggers depopulation even as production increases. This problem is particularly acute in regions with a sharply continental climate and traditional agricultural specialization. In the Republic of Buryatia, where livestock farming accounts for 75% of gross agricultural output and rural outmigration remains a persistent trend, a quantitative assessment of this imbalance and a typology of municipal districts were conducted. The study is based on the author’s Index of Agrarian-Social Imbalance (IASI), which aggregates indicators of agricultural productivity, natural and climatic conditions and quality of life (provision of social infrastructure, development of transport and digital communications, income level and employment diversification). Calculation of the index for rural municipalities of the region allowed us to distinguish three types of territories: 1) “Efficiency without prospects” (IASI> 1.2) - districts with high marketability of the agricultural sector and low quality of life, which correlates with maximum migration loss; 2) “Balanced but vulnerable development” (0.8 ≤ IASI ≤ 1.2) - territories with relative equilibrium, unstable to external shocks; 3) “Comfort without development” (IASI < 0.8) - characterized by a developed social sphere with a weak agricultural sector. Priority policy areas have been defined for each type: the first one - stimulation of processing industries and development of digital infrastructure; the second focuses on economic diversification and support for cooperation; the third focuses on tourism development and creation of conditions for remote employment. The results demonstrate the need for a targeted approach that considers not sectoral efficiency, but the balance of economic and social factors.
This article presents a method for remote monitoring and forecasting of strawberry (Fragaria × ananassa) yields based on unmanned aerial vehicles (UAVs), computer vision and deep learning technologies. Using morphological features of the crop, UAVs ensure high detection accuracy. The study was conducted using YOLO12 Extra Large convolutional neural network, trained using transfer learning on a specialized dataset of strawberry flower images (class “Flower”). The dataset was created by manual labeling in RectLabel and expanded to 1700 images (18 496 exemplars) using complex data augmentation. Initial data were collected using a DJI Mavic 3M UAV (RGB camera) at an altitude of 30-60 m. Image processing included the construction of a high-precision orthomosaic (resolution 0.570 mm/pixel) in Agisoft Metashape Pro. Orthomosaic was automatically divided into 200×200 pixel fragments for detection. Training YOLO12 model (hyperparameters: batch size = 8, learning rate = 0.001, epochs = 1500) achieved high metrics on the test set: precision 0.903, recall 0.812, Fmeasure 0.852, mAP50 0.888. Based on the developed method, specialized software with a graphical interface was created. It implements the full processing cycle: orthomosaic tiling, flower detection, merging detection results into a single orthomosaic, spatial analysis (construction of density heat maps, calculation of Moran’s index for clustering assessment, K-means cluster analysis, visualization of Voronoy diagrams), and yield forecasting using a formula that takes into account the number of recognized flowers, varietal conversion factors and average berry weight. The method enables automated flower counting over large areas, identification of zones of uneven productivity and yield forecasting in the early stages of vegetation, significantly reducing labor costs and providing a basis for making agricultural decisions.
Potato storage is a critical and labor-intensive operation, the effectiveness of which is determined by the design of machines used, as their proper functioning minimizes damage to the tubers. Therefore, a pressing issue is the justification of operating units design capable of minimizing dynamic loads on the product and ensuring uniform distribution. The aim of this study is to identify patterns for justifying the operating elements of an automated machine for stored potatoes. The research was conducted at Federal Scientific Center for VIM in 2024-2025 using SolidWorks and Excel. Research methods were based on a comprehensive theoretical approach combining mathematical statistics and the theory of random processes to describe the stochastic nature of changes in tuber heap density. The material transport process was modeled using a system of differential equations transformed into operator form to analyze the dynamic properties of the feeder as a nonlinear element with distributed delivery. A comparative analysis of three geometric shapes of the feeder working surface for their effect on tuber lifting speed was conducted: an Archimedes spiral, a logarithmic spiral and a hyperbolic spiral. The speed variation between studied surface types in the angle range of π/8–3π/8 is within 1–5%. It was found that with an increase in the rotation angle to π/2, only the surface constructed according to Archimedes spiral ensures a linear increase in lifting speed to a maximum value of 1.6 m/s, while the logarithmic and hyperbolic spirals provide an increase of only up to 1.0 m/s or a decrease in speed. The obtained patterns provide a scientific and technical basis for the design of automated potato loading machines for storage facilities, adapted for use on small farms with limited space. Using a feeder with a working surface designed according to an Archimedes spiral will improve productivity by increasing the feed rate, reducing damage to the product and ensuring a more uniform mound formation.
Central Black Earth region accounts for 16.3% of agricultural output, accounting for only 6.0% of agricultural land. According to Rosstat, Belgorod region alone produced 10.8% of the national livestock output in 2024. However, a negative trend of slowing agricultural production has emerged in this macroregion, despite the sector’s overall growth nationwide, necessitating the identification of the factors exerting the negative impact. The scientific novelty of this study lies in the discovery of new empirical data demonstrating a strong correlation between agricultural production growth rates in the studied regions and producer prices, as well as the identification of a moderate dependence on export volumes. It has been established that, despite the overall growth of the agro-industrial complex in the Russian Federation, a negative trend of production decline is observed in a number of entities of Central Black Earth region. The peculiarity of Central Black Earth region’s development is due to the fact that several of its constituent entities are border regions. In 2024, the growth rate of agricultural production in Central Black Earth region was 94.9%, while the national average was estimated at 106.7%. A significant impact of agricultural producer prices on the pace of industry development was revealed (the paired correlation coefficient was: Russian Federation - 0.86; Central Black Earth region - 0.67; Belgorod region - 0.70). No direct correlation was found between inflation processes and the pace of growth of the agro-industrial complex. The study found that agricultural exports demonstrate steady growth, reaching $45 billion in 2024. Moreover, the volume of imports and exports has an indirect effect on the development of agriculture. The practical significance of this work lies in the development of a set of measures to support agro-industrial complex, including financial and credit mechanisms and increasing the investment attractiveness of the industry in border areas.
Mathematical model of air-grain mixture movement in a pneumatic loading device, first proposed for use in grain seed treaters, has been developed. The modeling was performed for suspended grain seed movement. An equation for seed motion has been derived that allows for a theoretical description of the grain trajectory in a pneumatic seed tube. This equation will be used in the future to theoretically substantiate the design and technological parameters of a pneumatic seed tube, ensuring highquality seed movement with the required throughput and minimal energy consumption. New theoretical dependencies were obtained and parameters of air-grain mixture movement in the inclined pneumatic seed pipeline of the pneumatic loading device were determined. The studies were conducted for grain crop seeds with hovering speeds of 5-20 m/s at pneumatic seed tube inclination angles of 30-75° and diameters of 0.05-0.25 m. It was determined that for seeds with a low critical speed (5 m/s) at a pneumatic seed tube inclination angle of 30°, the minimum air speed should be 10.0 m/s, at 45° – 7.1 m/s, at 60°– 5.8 m/s, at 75° – 5.2 m/s, and for seeds with a maximum critical speed (20 m/s) at 30° – 40.0 m/s, at 45° – 28.3 m/s, at 60° – 23.1 m/s, at 75° – 20.8 m/s. It was found that for high-quality seed movement at a high critical speed (20 m/s), the air flow rate increases from 0.08 to 0.99 m3/s with a diameter increasing from 0.05 m to 0.25 m at a pneumatic seed tube inclination of 45°, from 0.06 to 0.86 m3/s at 60°, and from 0.05 to 0.76 m3/s at 75°. Theoretical results obtained will be used in the design of a pneumatic loading device for seed treaters.
The existing set of social, economic and political problems can only be resolved through long-term economic growth. One of the most important trends in economic development is increasing investment. Low level of technical equipment and depreciation of fixed assets are among the main problems in the development of agricultural sector. Therefore, a promising vector for the development of agricultural production is its intensification through the introduction of modern technologies and modernization of material and technical base. The depreciation degree of fixed assets in agriculture in Krasnodar Krai in 2024 was 50.6%, compared to 43.3% for all types of economic activity. Moreover, over a third of agricultural machinery is obsolete and requires replacement. This situation poses a complex challenge for government in developing and implementing incentives to mobilize investment resources for agricultural enterprises. Through the tax system, the state influences the amount of financial resources that organizations can direct toward developing and expanding their material and technical base, i.e., using them as capital investments in fixed assets. A variety of tax benefits, preferences and special tax regimes have little impact on increasing the investment activity of organizations, including those in the agricultural sector. Replacing the payment of several types of taxes with a single tax under special tax regimes effectively transfers some financial resources from the state to businesses without requiring investment in the development of material and technical bases. Further effective development of the material and technical base in regional agriculture is expected through active promotion of the benefits of using depreciation bonuses, investment tax deductions and special tax regimes that facilitate the formation of sources of capital investment.
Arable soils are one of the main sources of carbon dioxide emissions into the atmosphere. Increasing chemical loads, especially the application of high doses of mineral fertilizers, increase soil respiration. It is necessary to determine the influence of various factors on the rate of carbon dioxide production in order to predict overall carbon dioxide emission fluxes in agroecosystems. The aim of this study was to determine the influence of soil temperature and moisture on intensity of carbon dioxide emissions in spring wheat crops with increasing doses of mineral fertilizers in the forest-steppe zone of Trans-Urals. The work was carried out in 2023-2024 years on leached chernozem. The experimental scheme included variants with a natural nutrient level (without fertilizers) and doses of mineral fertilizers for an estimated yield of 3.0...6.0 t/ha of spring wheat grain. Carbon dioxide emissions were determined using closedchamber gas analyzers. Soil respiration in the variant without fertilizers ranged from 12 to 113 kg/ha per day. In the fertilized variants CO2 production ranged from 13 to 174 kg/ha per day. A strong relationship was observed between soil respiration and its temperature (r=0.79...0.87) and a moderate relationship with moisture (r=0.63...0.69) regardless of the nutrient level A change in soil temperature by 1℃ without fertilizers led to a variation in CO2 emissions per day by 7.7 kg/ha, its range increased to ±9.1...13.0 kg/ha per day with an increase in the nutrient level. A change in soil moisture by 1% was accompanied by a daily variation in emissions of 2.4 kg CO2/ha and 3.2-3.9 kg CO2/ha, respectively.
Yield development begins with seed germination and continues throughout the growing season. Natural plant processes include an increase in leaf area and accumulation of dry biomass; these factors determine the photosynthetic potential of plants and, subsequently, productivity. The aim of study was to evaluate the yield and grain quality development of spring soft wheat depending on plant development during the tillering stage. The study was conducted from 2023 to 2025 in a field experiment in the southern forest-steppe of Omsk region. In terms of moisture availability, 2023 was characterized as dry, while 2024 and 2025 were waterlogged. The object of study was the spring soft wheat of Tarskaya 12 variety (included in State Register of the Russian Federation in 2023). Grain weight per ear, yield and protein content in spring soft wheat grain were strongly directly dependent on the leaf area and the total assimilation surface of plants at the tillering stage (r = 0.817...0.998) and inversely with the accumulation of dry aboveground biomass (r = -0.954...0.999), indicating competition between the accumulation of dry matter in vegetative and generative parts. The obtained results indicate that early spring soft wheat plant growth significantly influenced the development of quality and yield characteristics of Tarskaya 12 variety.
In the context of personnel shortage of in the Russian labor market, the agro-industrial complex faces the pressing need to change traditional approaches to improving production efficiency. The key approach is considered to be the relationship between staffing in the agro-industrial complex and sustainable development goals, as well as the integration of ESG approach into enterprise strategies. An analysis of employment and productivity trends in Russian agriculture from 2017 to 2023 reveals that labor shortages and rising personnel costs make extensive development models economically ineffective. The correlation coefficient between the gross regional product and number of people employed in agriculture as a percentage of the average annual employed population in the region was 0.83. The impact of wages on the gross regional product was significantly higher than the share of people employed in agriculture as a percentage of the average annual employed population in the region – 1.39 versus 0.035. It has been revealed that the drivers of wage increases include the introduction of modern technologies and automation, improved personnel skills, the development of efficient value chains and cooperation, and the transition to high-value-added production. This study substantiates that the transition to intensive production models based on digitalization, automation and technological modernization is a prerequisite for improving the efficiency and sustainability of the industry. The integration of ESG principles enhances the effectiveness of intensive strategies: the environmental aspect contributes to a reduction in resource consumption and emissions, the social aspect ensures the development of human resources and rural infrastructure and the management aspect increases business transparency and accountability. It is demonstrated that ESG approach is becoming an internal factor in the competitiveness of enterprises, rather than an external requirement. The practical significance of the study lies in the development of recommendations for the implementation of digital management platforms, the development of corporate training programs, and the creation of an attractive social environment in rural areas. Based on the findings, it was determined that integrating ESG into intensive development ensures the sustainability, innovation, and social orientation of Russia’s agro-industrial complex.
Seed treatment in agriculture is aimed at increasing the safety of seed, improving its sowing qualities and creating favorable conditions for uniform seedling emergence. This article examines the impact of various inserts on seed movement in a drum-type treater using the discrete element method. Three working surface options are considered: smooth steel, with cylindrical inserts and a spiral rubber insert. Modeling and laboratory testing showed that the spiral insert provides better seed mixing, increases seed residence time in the drum and improves treatment uniformity. The obtained results confirm the feasibility of using this design to improve the quality of pre-sowing seed treatment. Furthermore, the use of discrete element method modeling allows for an early assessment of the impact of design changes on seedbed kinematics without extensive field testing. This makes the proposed approach a convenient tool for designing and improving drum seed treaters.
