Abstract

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.

Highlights

  • Consejo Nacional de Ciencia y Tecnología-Universidad Autónoma de San Luis Potosí, CIACYT, Alvaro Obregon 64, Col

  • We identify each mechanism as (PCA + multilayer perceptron (MLP)) when a neural network is being used on the principal components and as (PCA + LDA) for the classifier using the principal components with the linear discriminant analysis

  • Detection of bacterial canker of tomato is essential for epidemiological monitoring and plant disease management

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Summary

Introduction

Consejo Nacional de Ciencia y Tecnología-Universidad Autónoma de San Luis Potosí, CIACYT, Alvaro Obregon 64, Col. Centro, San Luis Potosí 78000, Mexico. Luis Potosí, Matehuala, Ejido Palma de la Cruz, Soledad de Graciano Sánchez, San Luis Potosí 78321, Mexico; Abstract: Bacterial canker of tomato is caused by Clavibacter michiganensis subsp. 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. 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.

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