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

被引:15
|
作者
Vallejo-Perez, Moises Roberto [1 ,2 ]
Sosa-Herrera, Jesus Antonio [3 ]
Navarro-Contreras, Hugo Ricardo [2 ]
Alvarez-Preciado, Luz Gabriela [2 ]
Rodriguez-Vazquez, Angel Gabriel [2 ]
Lara-Avila, Jose Pablo [4 ]
机构
[1] Univ Autonoma San Luis Potosi, CIACYT, CONICET, Alvaro Obregon 64,Col Ctr, San Luis Potosi 78000, San Luis Potosi, Mexico
[2] Univ Autonoma San Luis Potosi, Coordinac Innovac & Aplicac Ciencia & Tecnol CIAC, Av Sierra Leona 550,Col Lomas 2a Secc, San Luis Potosi 78210, San Luis Potosi, Mexico
[3] Consejo Nacl Ciencia & Technol, Lab Nacl Geointeligencia, Ctr Invest Ciencias Informac Geoespacial AC, Aguascalientes 20313, Aguascalientes, Mexico
[4] Univ Autonoma San Luis Potosi, Fac Agron & Vet, Km 145 Carretera San Luis Potosi,Matehuala,Ejido, San Luis Potosi 78321, San Luis Potosi, Mexico
来源
PLANTS-BASEL | 2021年 / 10卷 / 08期
关键词
Clavibacter michiganensis subsp; michiganensis; plant disease surveillance; precision farming; principal component analysis (PCA); multilayer perceptron (MLP); linear discriminant analysis (LDA); MICHIGANENSIS SUBSP MICHIGANENSIS; MAIZE KERNELS; RESISTANCE; SCATTERING; PIGMENT; PEPPER; LEAVES;
D O I
10.3390/plants10081542
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
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.
引用
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页数:13
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