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DOI: 10.15507/2658-4123.035.202503.443-464

Intelligent Assessment of Wheat Yield through the Variable Potential of Seeds

Sergey P. Pronin
Dr.Sci. (Eng.), Professor of the Department of Information Technology, Polzunov Altai State Technical University (46 Lenin Ave., Barnaul 656038, Russian Federation), ORCID: https://orcid.org/0000-0001-5066-2609, Scopus ID: 6701475629, SPIN-code: 2745-4983, This email address is being protected from spambots. You need JavaScript enabled to view it.

Anastasia G. Zryumova
Cand.Sci. (Eng.), Head of the Department of Information Technology, Polzunov Altai State Technical University (46 Lenin Ave., Barnaul 656038, Russian Federation), ORCID: https://orcid.org/0009-0005-1289-6099, This email address is being protected from spambots. You need JavaScript enabled to view it.

Alexander A. Piletsky
Postgraduate Student of the Department of Information Technology, Polzunov Altai State Technical University (46 Lenin Ave., Barnaul 656038, Russian Federation), ORCID: https://orcid.org/0009-0001-2134-2662, This email address is being protected from spambots. You need JavaScript enabled to view it.

Vladimir I. Belyaev
Dr.Sci. (Eng.), Head of the Department of Agricultural Machinery and Technology, Altai State Agricultural University (98 Krasnoarmeyskiy Ave., Barnaul 656049, Russian Federation), ORCID: https://orcid.org/0000-0003-4396-2202, This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract
Introduction. Evaluation of wheat seed quality is an integral part of the technological process of its production since it increases the yield. The yield is affected by many different factors. The evaluation methods are constantly being improved taking into account new factors, physical methods and technical means. Currently seeds and crops sowing quality intelligent evaluation methods are developing very rapidly. The electrophysical method allows evaluating the soil influence on seeds by the variable potential.
Aim of the Study. The study is aimed at examining changes in the variable potential of wheat seeds of a known crop yields during seed swelling in solutions with different potassium and sodium ratios and creating a convolutional neural network to estimate potential crop yields through the variable potential and known potassium and sodium ratios.
Materials and Methods. The studies were carried out using seeds of two varieties of spring wheat with different yields. To simulate soil quality, there were used solutions with different potassium chloride and sodium chloride ratios. The variable potential was measured using a device based on the data acquisition board LA50-USB. The yield was estimated using wavelet transform and deep convolutional neural network with ResNet groups.
Results. There have been developed the experimental graphs of the variable potential change depending on the potassium and sodium ratio in a solution simulating soil quality. The neural network was used to classify the potential yield of wheat seeds through wavelet transforms of the variable potential, and potassium and sodium ratios. There has been compiled a table of neural network responses to test variable potentials.
Discussion and Conclusion. The developed graphs of the variable potential change depending on potassium change in the external environment were compared with the results of studies by other authors. The results qualitatively coincide. The developed neural network can classify the potential yield of wheat seeds through the variable potential, and potassium and sodium ratios. The conducted study is useful for agricultural enterprises and farmers. The proposed methodology for assessing potential crop yields through variable potential and water extract will allow optimizing the process of potassium application to the soil.

Keywords: variable potential, wheat, potassium and sodium ratio, neural network, yield

Conflict of interest: The authors declare that there is no conflict of interest.

For citation: Pronin S.P., Zryumova A.G., Piletsky A.А., Belyaev V.I. Intelligent Assessment of Wheat Yield through the Variable Potential of Seeds. Engineering Technologies and Systems.2025;35(3):443–464. https://doi.org/10.15507/2658-4123.035.202503.443-464

Authors contribution:
S. P. Pronin – formulating the study, aims and objectives; conducting the study, including the executing and describing the experiments, collecting and analyzing the; using statistical, mathematical, computational and other formal methods for analyzing the study data; preparing of the manuscript: critical analysis of the draft manuscript, comments and corrections made by members of the research group, including at the stages before and after publication.
A. G. Zryumova – conducting the study, describing existing control methods, executing the experiments and collecting the data; preparing the manuscript; visualizing the study results and data obtained.
A. A. Piletsky – conducting the study including the development of a neural network, its training, data processing, description of the neural network architecture, performing experiments and collecting data; preparing a manuscript: visualizing the study results and data obtained.
V. I. Belyaev – conducting the study, including the preparation of wheat seeds, consultations on the yield of varieties; preparing the manuscript: visualizing the study results and the data obtained.

All authors have read and approved the final manuscript.

Submitted 17.01.2025;
revised 13.02.2025;
accepted 25.02.2025

REFERENCES

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