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IVES 9 IVES Conference Series 9 DISCRIMINATION OF BOTRYTIS CINEREA INFECTED GRAPES USING UNTARGE-TED METABOLOMIC ANALYSIS WITH DIRECT ELECTROSPRAY IONISATION MASS SPECTROMETRY

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:

Publication date: February 9, 2024

Issue: OENO Macrowine 2023

Type: Article

Authors

Liang Jiang1-3, Morphy C. Dumlao1,2,4, William A. Donald4, Christopher C. Steel1,3, Leigh M. Schmidtke1-3

1. Gulbali Institute, Charles Sturt University, Wagga Wagga, New South Wales, Australia 2678
2. The Australian Research Council Training Centre for Innovative Wine Production, University of Adelaide (Waite Campus), South Australia 5064
3. School of Agricultural, Environmental and Veterinary Science, Faculty of Science, Charles Sturt University, Wagga Wagga, New South Wales, Australia 2678
4. School of Chemistry, Faculty of Science, University of New South Wales (Sydney), New South Wales, Australia, 2052

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Keywords

Rapid analysis, metabolomics work flow, high resolution mass spectrometry, fruit quality

Tags

IVES Conference Series | oeno macrowine 2023 | oeno-macrowine

Citation

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