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A review of hyperspectral image analysis techniques for plant disease detection and identif ication

Plant diseases cause signif icant economic losses in agriculture around the world. Early detection, quantif ication and identif ication of plant diseases are crucial for targeted application of plant protection measures in crop production. Recently, intensive research has been conducted to develop i...

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Autor principal: Cheshkova, A.F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Federal Research Center Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8983301/
https://www.ncbi.nlm.nih.gov/pubmed/35434482
http://dx.doi.org/10.18699/VJGB-22-25
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author Cheshkova, A.F.
author_facet Cheshkova, A.F.
author_sort Cheshkova, A.F.
collection PubMed
description Plant diseases cause signif icant economic losses in agriculture around the world. Early detection, quantif ication and identif ication of plant diseases are crucial for targeted application of plant protection measures in crop production. Recently, intensive research has been conducted to develop innovative methods for diagnosing plant diseases based on hyperspectral technologies. The analysis of the ref lection spectrum of plant tissue makes it possible to classify healthy and diseased plants, assess the severity of the disease, differentiate the types of pathogens, and identify the symptoms of biotic stresses at early stages, including during the incubation period, when the symptoms are not visible to the human eye. This review describes the basic principles of hyperspectral measurements and different types of available hyperspectral sensors. Possible applications of hyperspectral sensors and platforms on different scales for diseases diagnosis are discussed and evaluated. Hyperspectral analysis is a new subject that combines optical spectroscopy and image analysis methods, which make it possible to simultaneously evaluate both physiological and morphological parameters. The review describes the main steps of the hyperspectral data analysis process: image acquisition and prepro cessing; data extraction and processing; modeling and analysis of data. The algorithms and methods applied at each step are mainly summarized. Further, the main areas of application of hyperspectral sensors in the diagnosis of plant diseases are considered, such as detection, differentiation and identif ication of diseases, estimation of disease severity, phenotyping of disease resistance of genotypes. A comprehensive review of scientif ic publications on the diagnosis of plant diseases highlights the benef its of hyperspectral technologies in investigating interactions between plants and pathogens at various measurement scales. Despite the encouraging progress made over the past few decades in monitoring plant diseases based on hyperspectral technologies, some technical problems that make these methods diff icult to apply in practice remain unresolved. The review is concluded with an overview of problems and prospects of using new technologies in agricultural production
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spelling pubmed-89833012022-04-15 A review of hyperspectral image analysis techniques for plant disease detection and identif ication Cheshkova, A.F. Vavilovskii Zhurnal Genet Selektsii Review Plant diseases cause signif icant economic losses in agriculture around the world. Early detection, quantif ication and identif ication of plant diseases are crucial for targeted application of plant protection measures in crop production. Recently, intensive research has been conducted to develop innovative methods for diagnosing plant diseases based on hyperspectral technologies. The analysis of the ref lection spectrum of plant tissue makes it possible to classify healthy and diseased plants, assess the severity of the disease, differentiate the types of pathogens, and identify the symptoms of biotic stresses at early stages, including during the incubation period, when the symptoms are not visible to the human eye. This review describes the basic principles of hyperspectral measurements and different types of available hyperspectral sensors. Possible applications of hyperspectral sensors and platforms on different scales for diseases diagnosis are discussed and evaluated. Hyperspectral analysis is a new subject that combines optical spectroscopy and image analysis methods, which make it possible to simultaneously evaluate both physiological and morphological parameters. The review describes the main steps of the hyperspectral data analysis process: image acquisition and prepro cessing; data extraction and processing; modeling and analysis of data. The algorithms and methods applied at each step are mainly summarized. Further, the main areas of application of hyperspectral sensors in the diagnosis of plant diseases are considered, such as detection, differentiation and identif ication of diseases, estimation of disease severity, phenotyping of disease resistance of genotypes. A comprehensive review of scientif ic publications on the diagnosis of plant diseases highlights the benef its of hyperspectral technologies in investigating interactions between plants and pathogens at various measurement scales. Despite the encouraging progress made over the past few decades in monitoring plant diseases based on hyperspectral technologies, some technical problems that make these methods diff icult to apply in practice remain unresolved. The review is concluded with an overview of problems and prospects of using new technologies in agricultural production The Federal Research Center Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences 2022-03 /pmc/articles/PMC8983301/ /pubmed/35434482 http://dx.doi.org/10.18699/VJGB-22-25 Text en Copyright © AUTHORS https://creativecommons.org/licenses/by/2.5/This work is licensed under a Creative Commons Attribution 4.0 License
spellingShingle Review
Cheshkova, A.F.
A review of hyperspectral image analysis techniques for plant disease detection and identif ication
title A review of hyperspectral image analysis techniques for plant disease detection and identif ication
title_full A review of hyperspectral image analysis techniques for plant disease detection and identif ication
title_fullStr A review of hyperspectral image analysis techniques for plant disease detection and identif ication
title_full_unstemmed A review of hyperspectral image analysis techniques for plant disease detection and identif ication
title_short A review of hyperspectral image analysis techniques for plant disease detection and identif ication
title_sort review of hyperspectral image analysis techniques for plant disease detection and identif ication
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8983301/
https://www.ncbi.nlm.nih.gov/pubmed/35434482
http://dx.doi.org/10.18699/VJGB-22-25
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