Characterization of the metabolites associated with Xylella fastidiosa infection in olive trees & study of the spatial distribution of X. fastidiosa infection in the apulian olive groves according to bayesian modelling
Author(s)
Jlilat, Asmae
Date Issued
July 22, 2020
Type
Doctoral Thesis
Abstract
Xylella fastidiosa is one of the most dangerous plant pathogenic bacterium introduced recently in the EU. It is causing the death of millions of olive trees in Apulia region (southern Italy) with the Olive Quick Decline Syndrome (OQDS). The symptoms differ on a varietal basis, making difficult the detection of X. fastidiosa that spreads rapidly through its main vector, Philaenus spumarius. Since the olive tree is the primary host of the bacterium and covers most of the Apulian territory, the aim of this thesis is to establish an efficient approach for the early detection of X. fastidiosa in olive trees focusing on two different aspects. The first one is the characterisation of discriminating metabolites (associated to the infection) that can be correlated to hyperspectral data acquired remotely for largescale survey. The X. fastidiosa infection affected the concentrations of mannitol, sucrose, malic acid, oleuropein and formic acid in inoculated olive plants. The second aspect concerns the use of largescale predictive modelling. The spatial distribution of X. fastidiosa was assessed in Apulian olive groves according to Bayesian modelling. Three proposed strategies S93, S75 and S38 that correspond to the number of samples per grid cell (1 km2) were used, and S75 was considered optimal, as it can reduce the number of samples per grid cell to more than 50% but can detect 87% of infected grid cells.
Additional information
Dottorato di ricerca in Scienze delle produzioni vegetali e animali
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