Biosensor Technologies for Early Detection and Quantification of Plant Pathogens
Copyright © 2021 Dyussembayev, Sambasivam, Bar, Brownlie, Shiddiky and Ford..
Plant pathogens are a major reason of reduced crop productivity and may lead to a shortage of food for both human and animal consumption. Although chemical control remains the main method to reduce foliar fungal disease incidence, frequent use can lead to loss of susceptibility in the fungal population. Furthermore, over-spraying can cause environmental contamination and poses a heavy financial burden on growers. To prevent or control disease epidemics, it is important for growers to be able to detect causal pathogen accurately, sensitively, and rapidly, so that the best practice disease management strategies can be chosen and enacted. To reach this goal, many culture-dependent, biochemical, and molecular methods have been developed for plant pathogen detection. However, these methods lack accuracy, specificity, reliability, and rapidity, and they are generally not suitable for in-situ analysis. Accordingly, there is strong interest in developing biosensing systems for early and accurate pathogen detection. There is also great scope to translate innovative nanoparticle-based biosensor approaches developed initially for human disease diagnostics for early detection of plant disease-causing pathogens. In this review, we compare conventional methods used in plant disease diagnostics with new sensing technologies in particular with deeper focus on electrochemical and optical biosensors that may be applied for plant pathogen detection and management. In addition, we discuss challenges facing biosensors and new capability the technology provides to informing disease management strategies.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:9 |
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| Enthalten in: |
Frontiers in chemistry - 9(2021) vom: 17., Seite 636245 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Dyussembayev, Kazbek [VerfasserIn] |
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| Links: |
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| Themen: |
Biosensor |
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| Anmerkungen: |
Date Revised 02.04.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.3389/fchem.2021.636245 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Copyright © 2021 Dyussembayev, Sambasivam, Bar, Brownlie, Shiddiky and Ford. | ||
| 520 | |a Plant pathogens are a major reason of reduced crop productivity and may lead to a shortage of food for both human and animal consumption. Although chemical control remains the main method to reduce foliar fungal disease incidence, frequent use can lead to loss of susceptibility in the fungal population. Furthermore, over-spraying can cause environmental contamination and poses a heavy financial burden on growers. To prevent or control disease epidemics, it is important for growers to be able to detect causal pathogen accurately, sensitively, and rapidly, so that the best practice disease management strategies can be chosen and enacted. To reach this goal, many culture-dependent, biochemical, and molecular methods have been developed for plant pathogen detection. However, these methods lack accuracy, specificity, reliability, and rapidity, and they are generally not suitable for in-situ analysis. Accordingly, there is strong interest in developing biosensing systems for early and accurate pathogen detection. There is also great scope to translate innovative nanoparticle-based biosensor approaches developed initially for human disease diagnostics for early detection of plant disease-causing pathogens. In this review, we compare conventional methods used in plant disease diagnostics with new sensing technologies in particular with deeper focus on electrochemical and optical biosensors that may be applied for plant pathogen detection and management. In addition, we discuss challenges facing biosensors and new capability the technology provides to informing disease management strategies | ||
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| 700 | 1 | |a Bar, Ido |e verfasserin |4 aut | |
| 700 | 1 | |a Brownlie, Jeremy C |e verfasserin |4 aut | |
| 700 | 1 | |a Shiddiky, Muhammad J A |e verfasserin |4 aut | |
| 700 | 1 | |a Ford, Rebecca |e verfasserin |4 aut | |
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