DISCRIMINATION OF BOTRYTIS CINEREA INFECTED GRAPES USING UNTARGE-TED METABOLOMIC ANALYSIS WITH DIRECT ELECTROSPRAY IONISATION MASS SPECTROMETRY
Abstract
Infection of grapes (Vitis vinifera) by Botrytis cinerea (grey mould) is a frequent occurrence in vineyards and during prolonged wet and humid conditions can lead to significant detrimental impact on yield and overall quality. Growth of B. cinerea causes oxidisation of phenolic compounds resulting in a loss of colour and formation of a suite of off-flavours and odours in wine made from excessively infected fruit. Apart from wine grapes, developing post-harvest B. cinerea infection in high-value horticultural products during storage, shipment and marketing may cause significant loss in fresh fruits, vegetables and other crops. A rapid and sensitive assessment method to detect, screen and quantify fungal infection would greatly assist viticultural growers and winemakers in determining fruit quality.
In this study metabolites were extracted from homogenate samples using acetonitrile with the data set comprising 140 healthy and infected grapes representing different vintages, cultivars, regions and maturity stages. Sample extracts were randomly analysed by direct injection into a LTQ ion mass spectrometer, operating in negative mode, including regular quality assurance samples with data collected from 50-2000 m/z for 1 minute. Molecular feature abundances were summed between 0.1-0.4 minutes and minmax normalised prior to PCA for quality control. Samples were randomly assigned to a calibration and independent test data set, with feature reduction, a two-class model PLS-DA, cross validation and permutation testing performed with the calibration data set. Prediction of sample class in the independent test samples demonstrated an overall predictive error of less than 5%. Feature importance was assessed using a combined VIP and selectivity ratio plot which demonstrated a high level of correlation with standard volcano plots. Annotation of important molecular features was undertaken using a high resolution Orbitrap MS detector, and LCqTOF of selected samples from healthy and infected extracts.
DOI:
Issue: OENO Macrowine 2023
Type: Article
Authors
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Keywords
Rapid analysis, metabolomics work flow, high resolution mass spectrometry, fruit quality