Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractVolatile organic compound data of ready-to-cook tuna fish-burgers: Time evolution in function of different and/or combined mild preservation technologies and relevant statistical analysis    Next AbstractPrediction of oral squamous cell carcinoma based on machine learning of breath samples: a prospective controlled study »

Phytochem Anal


Title:Volatolomics approach by HS-SPME-GC-MS and multivariate analysis to discriminate olive tree varieties infected by Xylella fastidiosa
Author(s):Mentana A; Camele I; Mang SM; De Benedetto GE; Frisullo S; Centonze D;
Address:"Dipartimento di Scienze Agrarie, degli Alimenti e dell'Ambiente, Universita degli Studi di Foggia, Via Napoli, Foggia, Italy. School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, Via dell'Ateneo Lucano, Potenza, Italy. Dipartimento di Beni Culturali, Universita del Salento, Lecce, Italy"
Journal Title:Phytochem Anal
Year:2019
Volume:20190424
Issue:6
Page Number:623 - 634
DOI: 10.1002/pca.2835
ISSN/ISBN:1099-1565 (Electronic) 0958-0344 (Linking)
Abstract:"INTRODUCTION: Xylella fastidiosa (Xf) is a pathogenic bacterium that causes diseases in olive trees. Therefore, analytical methods for both the characterisation of the host/pathogen interaction and infection monitoring are needed. Volatile organic compounds (VOCs) are emitted by plants relate to their physiological state, therefore VOCs monitoring can assist in detecting stress or infection states before visible signs are present. OBJECTIVE: In this work, the headspace-solid phase microextraction-gaschromatography-mass spectrometry (HS-SPME-GC-MS) technique was used for the first time to highlight VOCs differences between healthy and Xf-infected olive trees. METHODOLOGY: VOCs from olive tree twig samples were extracted and analysed by HS-SPME-GC-MS, and hence identified by comparing the experimental linear retention indexes with the reference values and by MS data obtained from NIST library. Data were processed by principal component analysis (PCA) and analysis of variance (ANOVA). RESULTS: The HS-SPME step was optimised in terms of adsorbent phase and extraction time. HS-SPME-GC-MS technique was applied to the extraction and analysis of VOCs of healthy and Xf-infected olive trees. More than 100 compounds were identified and the differences between samples were evidenced by the multivariate analysis approach. The results showed the marked presence of methyl esters in Xf-infected samples, suggesting their probable involvement in the mechanism of diffusible signal factor. CONCLUSION: The proposed approach represents an easy and solvent-free method to evaluate the presence of Xf in olive trees, and to evidence volatiles produced by host/pathogen interactions that could be involved in the defensive mechanism of the olive tree and/or in the infective action of Xf"
Keywords:Gas Chromatography-Mass Spectrometry/*methods Multivariate Analysis Olea/*chemistry/classification/*microbiology Solid Phase Microextraction/*methods Volatile Organic Compounds/*analysis Xylella/*pathogenicity Hs-spme-gc-ms Xylella fastidiosa olive tree v;
Notes:"MedlineMentana, Annalisa Camele, Ippolito Mang, Stefania M De Benedetto, Giuseppe E Frisullo, Salvatore Centonze, Diego eng EZIOCONTROL / B36J16002210007/Apulia Region (Italy) through the Research Programme 'Sperimentazione Finalizzata alla Prevenzione e al Contenimento del Complesso del Disseccamento Rapido dell'olivo (CODIRO)'/ England 2019/04/26 Phytochem Anal. 2019 Nov; 30(6):623-634. doi: 10.1002/pca.2835. Epub 2019 Apr 24"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 22-11-2024