No 2 (2025)

Trees are an integral part of public urban spaces. Woody plants in urban areas perform ecosystem, sanitary, aesthetic, and socio-economic functions, so maintaining their high viability is highly significant. Another important characteristic of green spaces is their floral composition in terms of diversity, structure and functionality. The Yoshkar-Ola city, the capital of the Mari El Republic, has been growing rapidly in recent decades, peripheral areas of the city are being built up, industry is developing, new infrastructure facilities are appearing, and the appearance of the city is changing. The expansion of development and accelerated aging of tree stands in the urban environment leads to the need for the development of green infrastructure. There is a steady decrease in the area of urban green areas and an increase in the degree of isolation of individual vegetation areas, which increases the risk of their violations under conditions of constantly increasing anthropogenic load. The purpose of the study is to analyze the systematic composition and vital condition of woody plants in Sovetskaya Street in the historical area of Yoshkar-Ola. The study was conducted in May 2025 by taking a complete inventory of the available woody plants. The sanitary condition was assessed according to a 5-point scale given in the Rules of Sanitary Safety in Forests (2020). A section of the street between Vashskaya and Krasnoarmeyskaya streets with a length of 1.4 km has been surveyed. It was found that 276 plants grow on the surveyed territory, of which 83% are deciduous trees, 9% are deciduous shrubs, and 8% are coniferous plants. There are 22 species from 12 families. Tilia cordata prevails in the number of specimens. Most of the plants are classified as weakened. Many trees on this street grow in small trunk holes among the asphalt pavement, which negatively affects their viability. Pruning also has an impact on the vital condition. It is proposed to supplement the existing plantings with beautifully flowering and decorative deciduous species.

The study examines how the 2024 growing season’s extreme weather – cold spring with frosts followed by a hot, dry summer – affected the biochemical composition and feed value of narrow-leaved lupine (Lupinus angustifolius L.), seed pea (Pisum sativum L.), and field pea (Pisum arvense L., “pelyushka”) in the Kirov region. Given rising climate instability, assessing legume adaptability to stress – particularly the ability to maintain nutrient content while limiting toxic compounds – is crucial. Key feed-value indicators analyzed included crude protein, fat, fiber, ash, metabolizable energy, and alkaloids, the latter being critical for lupine safety in animal feed. The field experiment was conducted at Vyatka State Agricultural and Technological University’s Agrotechnopark. Grain analyses were performed in accredited labs: standard chemical methods were used for protein, fat, fiber, and ash; alkaloids were measured by wet chemistry at VNII Lupin. For the first time in the region, all crops retained high metabolizable energy (12.6-13.3 MJ/kg) and dry matter (86.0-90.1%) despite climatic stress. Seed and field peas significantly exceeded average Russian norms for crude protein and biological extractive substances, demonstrating strong adaptive capacity. In contrast, all lupine varieties showed unacceptably high alkaloid levels (0.331-0.60%), exceeding the GOST R 54632-2011 limit for the 3rd quality class (0.30%), indicating stress-induced synthesis of secondary metabolites. Among them, the Mezenat variety displayed the most balanced profile – 32.5% protein, 6.4% fat, and the lowest alkaloid content (0.331%). These results are practically valuable for breeding and agronomic strategies in northern Russia, highlighting the need to select varieties not only for nutritional quality but also for resilience to climate-induced toxin accumulation.

The article examines the processes of digital transformation of the agro-industrial complex in the context of the use of artificial intelligence technologies in the use of pesticides. The subject of research in this article is the legal relations that arise in the process of using pesticides in agriculture in the context of the introduction and use of artificial intelligence technologies, including the features of algorithmic management, issues of responsibility allocation and the specifics of legal regulation of digital agricultural technologies. The relevance of the introduction of intelligent systems in agriculture in the context of population growth and limited expansion of agricultural land is substantiated. It is shown that algorithms of machine learning, computer vision and big data analysis make it possible to move from average chemical processing models to precision and individualized application of plant protection products, reducing the environmental burden and increasing production efficiency. Special attention is paid to legal aspects: the fragmented nature of Russian regulation is revealed, focused mainly on the chemical and sanitary characteristics of pesticides and not taking into account the specifics of algorithmic decision-making. A comparative analysis of foreign approaches has been conducted, primarily the European Union model with its risk-based regulation of artificial intelligence and the precautionary principle, as well as American practices based on industry standards and administrative control. The relevance of the topic is due to the need for legal understanding and regulation of the use of artificial intelligence in the use of pesticides in the context of digitalization of the agro-industrial complex, growing food demand and increased environmental and legal risks. It was analyzed that the introduction of artificial intelligence technologies into the agro-industrial complex is an objective necessity due to the growth of food demand with limited opportunities for expanding agricultural land, and can significantly increase the efficiency and environmental sustainability of pesticide use through the transition to precision and individualized processing methods. At the same time, the current legal regulation in the Russian Federation is not adapted to the conditions of algorithmic management and autonomous decision-making, which creates regulatory uncertainty and risks, primarily in the area of the distribution of legal liability for possible harm. Under these conditions, the formation of an integrated and risk-based legal mechanism that takes into account the specifics of the use of artificial intelligence in crop production and based on the best foreign practices is a prerequisite for the safe and sustainable development of the agricultural sector.