Development of a Hyperspectral Field Monitoring Method for Digital Twins of Plants

Digital Twins of Plants (DTP) enable the planning and simulation of the production process of cultivated plants with performance sufficient for practical applications. At the current stage of research on the development of DTP, conducted by the authors over several years, efforts have been made to improve the quality of growth and development predictions for crops. This includes ground-based hyperspectral imaging of field experiment plots and analysis of the reflectance characteristics of spring wheat at a specific phenological stage and with a defined level of mineral nutrition. The study describes the implementation of hyperspectral imaging of experimental crops in several farms within the Middle Volga region of Russia. The results of hyperspectral imaging of the experimental crops revealed correlations between vegetation condition, its visual representation in the images, and vegetation index values. The conducted studies confirm the possibility of expanding the sources of information used to refine calculations performed in the DTP through hyperspectral monitoring data.

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Publication Details

Journal
WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT
Published
2025-05-29
DOI
https://doi.org/10.37394/232015.2025.21.49
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Development of a Hyperspectral Field Monitoring Method for Digital Twins of Plants

Aleksey Tabachinskiy, Petr Skobelev, Elena Simonova, Yulia Zhuravel
WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT
Remote Sensing in Agriculture
article

Development of a Hyperspectral Field Monitoring Method for Digital Twins of Plants

Aleksey Tabachinskiy, Petr Skobelev, Elena Simonova, Yulia Zhuravel
article en

Abstract

Digital Twins of Plants (DTP) enable the planning and simulation of the production process of cultivated plants with performance sufficient for practical applications. At the current stage of research on the development of DTP, conducted by the authors over several years, efforts have been made to improve the quality of growth and development predictions for crops. This includes ground-based hyperspectral imaging of field experiment plots and analysis of the reflectance characteristics of spring wheat at a specific phenological stage and with a defined level of mineral nutrition. The study describes the implementation of hyperspectral imaging of experimental crops in several farms within the Middle Volga region of Russia. The results of hyperspectral imaging of the experimental crops revealed correlations between vegetation condition, its visual representation in the images, and vegetation index values. The conducted studies confirm the possibility of expanding the sources of information used to refine calculations performed in the DTP through hyperspectral monitoring data.

WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENTVol. 21
Samara National Research University (RU), Samara Federal Research Scientific Center (RU), Institute of Informatics of the Slovak Academy of Sciences (SK)
Openalex Percentile: Top 88%
Remote Sensing in Agriculture
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