Literature DB >> 26988658

Raman Spectroscopy an Option for the Early Detection of Citrus Huanglongbing.

Moisés Roberto Vallejo Pérez1, María Guadalupe Galindo Mendoza2, Miguel Ghebre Ramírez Elías3, Francisco Javier González4, Hugo Ricardo Navarro Contreras5, Carlos Contreras Servín2.   

Abstract

This research describes the application of portable field Raman spectroscopy combined with a statistical analysis of the resulting spectra, employing principal component analysis (PCA) and linear discriminant analysis (LDA), in which we determine that this method provides a high degree of reliability in the early detection of Huanglongbing (HLB) on Sweet Orange, disease caused by the bacteria Candidatus Liberibacter asiaticus. Symptomatic and asymptomatic plant samples of Sweet Orange (Citrus sinensis), Persian Lime (C. latifolia), and Mexican Lime (C. aurantifolia) trees were collected from several municipalities, three at Colima State and three at Jalisco State (HLB presence). In addition, Sweet Orange samples were taken from two other Mexican municipalities, one at San Luis Potosí and the other at Veracruz (HLB absent). All samples were analyzed by real-time PCR to determine its phytosanitary condition, and its spectral signatures were obtained with an ID-Raman mini. Spectral anomalies in orange trees HLB-positive, were identified in bands related to carbohydrates (905 cm(-1), 1043 cm(-1), 1127 cm(-1), 1208 cm(-1), 1370 cm(-1), 1272 cm(-1), 1340 cm(-1), and 1260-1280 cm(-1)), amino acids, proteins (815 cm(-1), 830 cm(-1), 852 cm(-1), 918 cm(-1), 926 cm(-1), 970 cm(-1), 1002 cm(-1), 1053 cm(-1), and 1446 cm(-1)), and lipids (1734 cm(-1), 1736 cm(-1), 1738 cm(-1), 1745 cm(-1), and 1746 cm(-1)). Moreover, PCA-LDA showed a sensitivity of 86.9 % (percentage of positives, which are correctly identified), a specificity of 91.4 % (percentage of negatives, which are correctly identified), and a precision of 89.2 % (the proportion of all tests that are correct) in discriminating between orange plants HLB-positive and healthy plants. The Raman spectroscopy technique permitted rapid diagnoses, was low-cost, simple, and practical to administer, and produced immediate results. These are essential features for phytosanitary epidemiological surveillance activities that may conduct a targeted selection of highly suspicious trees to undergo molecular DNA analysis.
© The Author(s) 2016.

Entities:  

Keywords:  Spectroscopy; chemometrics; citrus greening disease; citrus species

Mesh:

Year:  2016        PMID: 26988658     DOI: 10.1177/0003702816638229

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  8 in total

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Journal:  ISSS J Micro Smart Syst       Date:  2022-05-05

Review 2.  Raman-Based Diagnostics of Biotic and Abiotic Stresses in Plants. A Review.

Authors:  William Z Payne; Dmitry Kurouski
Journal:  Front Plant Sci       Date:  2021-01-20       Impact factor: 5.753

3.  Rapid Collection and Aptamer-Based Sensitive Electrochemical Detection of Soybean Rust Fungi Airborne Urediniospores.

Authors:  Vadim Krivitsky; Eran Granot; Yoav Avidor; Ella Borberg; Ralf T Voegele; Fernando Patolsky
Journal:  ACS Sens       Date:  2021-01-28       Impact factor: 7.711

4.  Citrus Huanglongbing Detection Based on Multi-Modal Feature Fusion Learning.

Authors:  Dongzi Yang; Fengcheng Wang; Yuqi Hu; Yubin Lan; Xiaoling Deng
Journal:  Front Plant Sci       Date:  2021-12-23       Impact factor: 5.753

5.  Surface-Enhanced Raman Scattering Spectroscopy Combined With Chemical Imaging Analysis for Detecting Apple Valsa Canker at an Early Stage.

Authors:  Shiyan Fang; Yanru Zhao; Yan Wang; Junmeng Li; Fengle Zhu; Keqiang Yu
Journal:  Front Plant Sci       Date:  2022-03-04       Impact factor: 5.753

6.  Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging.

Authors:  Yan-Ru Zhao; Ke-Qiang Yu; Xiaoli Li; Yong He
Journal:  Sci Rep       Date:  2016-12-13       Impact factor: 4.379

7.  Detection of Clavibacter michiganensis subsp. michiganensis Assisted by Micro-Raman Spectroscopy under Laboratory Conditions.

Authors:  Moisés Roberto Vallejo Pérez; Hugo Ricardo Navarro Contreras; Jesús A Sosa Herrera; José Pablo Lara Ávila; Hugo Magdaleno Ramírez Tobías; Fernando Díaz-Barriga Martínez; Rogelio Flores Ramírez; Ángel Gabriel Rodríguez Vázquez
Journal:  Plant Pathol J       Date:  2018-10-01       Impact factor: 1.795

8.  Root samples provide early and improved detection of Candidatus Liberibacter asiaticus in Citrus.

Authors:  W Evan Braswell; Jong-Won Park; Philip A Stansly; Barry Craig Kostyk; Eliezer S Louzada; John V da Graça; Madhurababu Kunta
Journal:  Sci Rep       Date:  2020-10-12       Impact factor: 4.379

  8 in total

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