UDC 10.36461/NP.2025.75.3.021
DOI 633.11+556.3.06;519.237.5;528.88

FORECASTING WINTER WHEAT YIELD BASED ON AGROCLIMATIC CONDITIONS AND NDVI IN THE PENZA REGION
A.S. Shcherbakov, Senior Lecturer, S.V. Bogomazov, Candidate of Agricultural Sciences, Associate Professor
“Penza State Agrarian University, Penza, Russia е–mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

This article deals with statistical correlation between winter wheat yield, meteoconditions, and the Normalized Difference Vegetation Index (NDVI) to develop a methodological guide for forecasting yields and assessing winter wheat growing over time. The research is based on a nine–year data analysis (2015–2023) using statistical methods, including cluster and correlation–regression analysis. During the research 27 municipal districts of the Penza region were clustered, and then divided into four groups. Multiple linear regression equations with a determination coefficient (R²) ranging from 0.71 to 0.85 were done for each cluster. The model consists of five key variables, including precipitation at different growing seasons, thermal conditions, and max NDVI. Model verification showed the mean absolute error (MAE) of 2.7 c/ha and the mean absolute percentage error (MAPE) of 9.2%. The accuracy of the general yield forecasting model was 97.0% (error of 3.0%). The observed models made possible to forecast yields for 2024, with a range of 21.3 to 41.0 c/ha by the regional districts and the average yield of 31.9 c/ha for the region. The results of the current research can be used by agricultural authorities for forecasting and risk assessment in crop production.
Keywords: winter wheat, yield, forecasting, remote sensing, NDVI, regression model, cluster analysis, agroclimatic conditions.

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UDC 633.854:581.192:502.17
DOI 10.36461/NP.2025.75.3.017

ASSESSMENT OF THE CHEMICAL COMPOSITION AND ECOLOGICAL POTENTIAL OF GIANT MISCANTHUS
V.A. Gushchina, Doctor of Agricultural Sciences, Professor;
A.A. Volodkin, Candidate of Agricultural Sciences, Associate Professor;
A.S. Lykova, Candidate of Agricultural Sciences, Associate Professor;
N.I. Ostroborodova, Candidate of Agricultural Sciences, Associate Professor
Federal State Budgetary Educational Institution of Higher Education "Penza State Agrarian University",
Penza, Russia, tel. (8412) 628-367, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Due to its high productivity and positive environmental impact, giant miscanthus is considered a sustainable and cost-efficient crop to replace traditional raw materials in the pulp and paper and bioenergy industries. The purpose of this study is to conduct a comparative analysis of giant miscanthus raw materials of different ages (planted in 2013 and 2017) to assess its potential as a component for use as raw material in bioenergy and the pulp and paper industry. A chemical analysis of raw materials grown on meadow-chernozem soil at the collection site of Penza State Agrarian University revealed a significant dependence of composition on plantation age and the morphological structure of the biomass. The highest cellulose content (54.6%) and lowest ash content (1.88%) were found in the stems of 12-year-old plants. In younger plantations (eighth year of vegetation), the cellulose content decreases (to 48.6%), while the lignin content increases. The presence of leaves has the most negative impact on raw material quality, causing a significant increase in ash content (up to 8.16%) and a decrease in cellulose content. To increase bioeconomy efficiency, the most rational method is to harvest miscanthus stems without leaves, which allows for obtaining more useful product and removing most unnecessary impurities. The study confirms the high potential of miscanthus as a renewable raw material for resource-efficient industries and the development of a green economy.
Keywords: giant miscanthus, cellulose, chemical composition, bioeconomics, lignin, ash content, non-wood raw materials, bioenergy, environmental advantage

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UDC 623.746.4 - 519
DOI 10.36461/NP.2025.75.3.020

UNMANNED AERIAL VEHICLES IN AGRICULTURE: LEGAL, TAX AND ACCOUNTING ASPECTS
I.V. Pavlova, Candidate of Economic Sciences, Associate Professor;
O.V. Lavrina, Candidate of Economic Sciences, Associate Professor;
I.E. Shpagina, Candidate of Economic Sciences, Associate Professor;
E.V. Shirokova, Candidate of Economic Sciences, Associate Professor
Penza State Agrarian University, Penza, Russia, tel. 8 (412) 62-81-33, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Unmanned aerial vehicles (UAVs) in agriculture are capable of performing critical technological operations that reduce environmental damage, cash and labor costs, optimize agricultural processes and, as a result, increase operational efficiency. However, the use of unmanned aerial systems is currently associated with problems at legal, tax and accounting levels, that requires some more information and details clarified. The article deals with a reasonable justification for efficient impact of unmanned technologies on global agriculture, the reasons for their temporarily limited use in Russia, and prospects for the future. The classification of the UAVs and the accompanying operating procedures for each group of the UAVs were observed. Current research identified most common problems in legal regulation of the agricultural UAVs use along with their interpretation in the Experimental legal regime program and further implementation into practice. The research also observed tax and accounting aspects towards the use of unmanned aerial systems. Efficient measures were proposed to solve several problems connected with the UAV practical use in agriculture.
Keywords: Unmanned aerial vehicle, max take-off weight, state registration, legal registration, aviation regulations, flight safety, accounting system, taxable object.

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UDC 636.2.034
DOI 10.36461/NP.2025.75.3.013

MILK YIELD DYNAMICS IN PUREBRED AND CROSSBRED COWS DURING THE PEAK MILKING PERIOD
I.R. Gazeev¹, Candidate of Agricultural Sciences, Associate Professor
S.V. Karamaev², Doctor of Agricultural Sciences, Professor
A.S. Karamaeva², Candidate of Biological Sciences, Associate Professor
¹Federal State Budgetary Educational Institution of Higher Education "Bashkir State Agrarian University", Ufa, Republic of Bashkortostan, Russia, tel. 8-987-015-06-02, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
²Federal State Budgetary Educational Institution of Higher Education "Samara State Agrarian University", Kinel, Russia, tel. 8-927-651-88-54, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

The purpose of the study is to improve the efficiency of breeding purebred and crossbred dairy and dual-purpose cows in the Southern Urals and Middle Volga region. Four groups of fifteen animals each were formed from the corresponding breed types: I – purebred black-and-white breed, II – crossbred with black-and-white Holsteins, III – purebred Bestuzhev breed, and IV – crossbred with red-and-white Holsteins. It was found that high milk yields in crossbred animals lead to a more pronounced decline in body condition during the peak lactation period. On the 100th day of lactation, the body condition score of crossbred cows was 0.25–0.5 points lower than that of purebred animals. Due to increased milk yield during the first lactation, crossbred black-and-white cows produced 13.9% more milk over 305 days of lactation than purebred cows (P < 0.001), and Bestuzhev cows produced 14.1% more (P < 0.001). During the second lactation, the increases were 12.4% (P < 0.001) and 12.1% (P < 0.001), and during the third lactation, 15.5% (P < 0.001) and 12.6% (P < 0.001), respectively. At the same time, the proportion of milk yield during the first lactation period, relative to the total 305-day lactation, was higher in purebred black-and-white cows by 1.4% and in Bestuzhev cows by 0.7%; in the second lactation by 0.7% and 0.7%; and in the third lactation by 0.4% and 0.7%, respectively. This indicates a more even distribution of milk yields throughout lactation and explains the higher productivity of crossbred cows. However, the increased stress on the animals' bodies resulted in a higher culling rate of crossbred cows as they aged. After the first lactation, 20.0% of animals were culled in group I, 33.3% in group II, 6.7% in group III, and 20.0% in group IV. After the second lactation, the culling rates were 41.7%, 60.0%, 21.4%, and 33.3%, respectively.
Keywords: breed, breed type, cow, peak milking period, milk yield, lactation, body condition.

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