Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges

Food security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. With the expansion of the international seed market with glo...

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Main Authors: Luciellen da Costa Ferreira, Ian Carlos Bispo Carvalho, Lúcio André de Castro Jorge, Alice Maria Quezado-Duval, Maurício Rossato
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-04-01
Series:Frontiers in Plant Science
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2024.1387925/full
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author Luciellen da Costa Ferreira
Ian Carlos Bispo Carvalho
Lúcio André de Castro Jorge
Alice Maria Quezado-Duval
Maurício Rossato
author_facet Luciellen da Costa Ferreira
Ian Carlos Bispo Carvalho
Lúcio André de Castro Jorge
Alice Maria Quezado-Duval
Maurício Rossato
author_sort Luciellen da Costa Ferreira
collection DOAJ
description Food security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. With the expansion of the international seed market with global movement of this propagative plant material, and considering that about 90% of economically important crops grown from seeds, seed pathology emerged as an important discipline. Seed health testing is presently part of quality analysis and carried out by seed enterprises and governmental institutions looking forward to exclude a new pathogen in a country or site. The development of seedborne pathogens detection methods has been following the plant pathogen detection and diagnosis advances, from the use of cultivation on semi-selective media, to antibodies and DNA-based techniques. Hyperspectral imaging (HSI) associated with artificial intelligence can be considered the new frontier for seedborne pathogen detection with high accuracy in discriminating infected from healthy seeds. The development of the process consists of standardization of methods and protocols with the validation of spectral signatures for presence and incidence of contamined seeds. Concurrently, epidemiological studies correlating this information with disease outbreaks would help in determining the acceptable thresholds of seed contamination. Despite the high costs of equipment and the necessity for interdisciplinary collaboration, it is anticipated that health seed certifying programs and seed suppliers will benefit from the adoption of HSI techniques in the near future.
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spelling doaj.art-00610897115f4d49af396b7f7ebb2e802024-04-11T04:23:44ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2024-04-011510.3389/fpls.2024.13879251387925Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challengesLuciellen da Costa Ferreira0Ian Carlos Bispo Carvalho1Lúcio André de Castro Jorge2Alice Maria Quezado-Duval3Maurício Rossato4University of Brasilia, Departament of Plant Pathology, Brasília, BrazilUniversity of Brasilia, Departament of Plant Pathology, Brasília, BrazilEmbrapa Instrumentação, São Carlos, BrazilEmbrapa Hortaliças, Brasília, BrazilUniversity of Brasilia, Departament of Plant Pathology, Brasília, BrazilFood security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. With the expansion of the international seed market with global movement of this propagative plant material, and considering that about 90% of economically important crops grown from seeds, seed pathology emerged as an important discipline. Seed health testing is presently part of quality analysis and carried out by seed enterprises and governmental institutions looking forward to exclude a new pathogen in a country or site. The development of seedborne pathogens detection methods has been following the plant pathogen detection and diagnosis advances, from the use of cultivation on semi-selective media, to antibodies and DNA-based techniques. Hyperspectral imaging (HSI) associated with artificial intelligence can be considered the new frontier for seedborne pathogen detection with high accuracy in discriminating infected from healthy seeds. The development of the process consists of standardization of methods and protocols with the validation of spectral signatures for presence and incidence of contamined seeds. Concurrently, epidemiological studies correlating this information with disease outbreaks would help in determining the acceptable thresholds of seed contamination. Despite the high costs of equipment and the necessity for interdisciplinary collaboration, it is anticipated that health seed certifying programs and seed suppliers will benefit from the adoption of HSI techniques in the near future.https://www.frontiersin.org/articles/10.3389/fpls.2024.1387925/fullartificial intelligencephytopathogenmachine learningseedbornebacteriafungus
spellingShingle Luciellen da Costa Ferreira
Ian Carlos Bispo Carvalho
Lúcio André de Castro Jorge
Alice Maria Quezado-Duval
Maurício Rossato
Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges
Frontiers in Plant Science
artificial intelligence
phytopathogen
machine learning
seedborne
bacteria
fungus
title Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges
title_full Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges
title_fullStr Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges
title_full_unstemmed Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges
title_short Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges
title_sort hyperspectral imaging for the detection of plant pathogens in seeds recent developments and challenges
topic artificial intelligence
phytopathogen
machine learning
seedborne
bacteria
fungus
url https://www.frontiersin.org/articles/10.3389/fpls.2024.1387925/full
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