Volatolomics approach by HS-SPME-GC-MS and multivariate analysis to discriminate olive tree varieties infected by Xylella fastidiosa.

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.