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Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition

Bacterial canker of tomato is caused by Clavibacter michiganensis subsp. michiganensis (Cmm). The disease is highly destructive, because it produces latent asymptomatic infections that favor contagion rates. The present research aims consisted on the implementation of Raman spectroscopy (RS) and mac...

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Autores principales: Vallejo-Pérez, Moisés Roberto, Sosa-Herrera, Jesús Antonio, Navarro-Contreras, Hugo Ricardo, Álvarez-Preciado, Luz Gabriela, Rodríguez-Vázquez, Ángel Gabriel, Lara-Ávila, José Pablo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399098/
https://www.ncbi.nlm.nih.gov/pubmed/34451590
http://dx.doi.org/10.3390/plants10081542
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author Vallejo-Pérez, Moisés Roberto
Sosa-Herrera, Jesús Antonio
Navarro-Contreras, Hugo Ricardo
Álvarez-Preciado, Luz Gabriela
Rodríguez-Vázquez, Ángel Gabriel
Lara-Ávila, José Pablo
author_facet Vallejo-Pérez, Moisés Roberto
Sosa-Herrera, Jesús Antonio
Navarro-Contreras, Hugo Ricardo
Álvarez-Preciado, Luz Gabriela
Rodríguez-Vázquez, Ángel Gabriel
Lara-Ávila, José Pablo
author_sort Vallejo-Pérez, Moisés Roberto
collection PubMed
description Bacterial canker of tomato is caused by Clavibacter michiganensis subsp. michiganensis (Cmm). The disease is highly destructive, because it produces latent asymptomatic infections that favor contagion rates. The present research aims consisted on the implementation of Raman spectroscopy (RS) and machine-learning spectral analysis as a method for the early disease detection. Raman spectra were obtained from infected asymptomatic tomato plants (BCTo) and healthy controls (HTo) with 785 nm excitation laser micro-Raman spectrometer. Spectral data were normalized and processed by principal component analysis (PCA), then the classifiers algorithms multilayer perceptron (PCA + MLP) and linear discriminant analysis (PCA + LDA) were implemented. Bacterial isolation and identification (16S rRNA gene sequencing) were realized of each plant studied. The Raman spectra obtained from tomato leaf samples of HTo and BCTo exhibited peaks associated to cellular components, and the most prominent vibrational bands were assigned to carbohydrates, carotenoids, chlorophyll, and phenolic compounds. Biochemical changes were also detectable in the Raman spectral patterns. Raman bands associated with triterpenoids and flavonoids compounds can be considered as indicators of Cmm infection during the asymptomatic stage. RS is an efficient, fast and reliable technology to differentiate the tomato health condition (BCTo or HTo). The analytical method showed high performance values of sensitivity, specificity and accuracy, among others.
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spelling pubmed-83990982021-08-29 Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition Vallejo-Pérez, Moisés Roberto Sosa-Herrera, Jesús Antonio Navarro-Contreras, Hugo Ricardo Álvarez-Preciado, Luz Gabriela Rodríguez-Vázquez, Ángel Gabriel Lara-Ávila, José Pablo Plants (Basel) Article Bacterial canker of tomato is caused by Clavibacter michiganensis subsp. michiganensis (Cmm). The disease is highly destructive, because it produces latent asymptomatic infections that favor contagion rates. The present research aims consisted on the implementation of Raman spectroscopy (RS) and machine-learning spectral analysis as a method for the early disease detection. Raman spectra were obtained from infected asymptomatic tomato plants (BCTo) and healthy controls (HTo) with 785 nm excitation laser micro-Raman spectrometer. Spectral data were normalized and processed by principal component analysis (PCA), then the classifiers algorithms multilayer perceptron (PCA + MLP) and linear discriminant analysis (PCA + LDA) were implemented. Bacterial isolation and identification (16S rRNA gene sequencing) were realized of each plant studied. The Raman spectra obtained from tomato leaf samples of HTo and BCTo exhibited peaks associated to cellular components, and the most prominent vibrational bands were assigned to carbohydrates, carotenoids, chlorophyll, and phenolic compounds. Biochemical changes were also detectable in the Raman spectral patterns. Raman bands associated with triterpenoids and flavonoids compounds can be considered as indicators of Cmm infection during the asymptomatic stage. RS is an efficient, fast and reliable technology to differentiate the tomato health condition (BCTo or HTo). The analytical method showed high performance values of sensitivity, specificity and accuracy, among others. MDPI 2021-07-28 /pmc/articles/PMC8399098/ /pubmed/34451590 http://dx.doi.org/10.3390/plants10081542 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Vallejo-Pérez, Moisés Roberto
Sosa-Herrera, Jesús Antonio
Navarro-Contreras, Hugo Ricardo
Álvarez-Preciado, Luz Gabriela
Rodríguez-Vázquez, Ángel Gabriel
Lara-Ávila, José Pablo
Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition
title Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition
title_full Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition
title_fullStr Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition
title_full_unstemmed Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition
title_short Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition
title_sort raman spectroscopy and machine-learning for early detection of bacterial canker of tomato: the asymptomatic disease condition
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399098/
https://www.ncbi.nlm.nih.gov/pubmed/34451590
http://dx.doi.org/10.3390/plants10081542
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