Influence of regional and yearly weather patterns on multi‐mycotoxin occurrence in Austrian wheat: a liquid chromatographic–tandem mass spectrometric and multivariate statistics approach

Author:

Freitag Stephan1ORCID,Sulyok Michael1ORCID,Reiter Elisabeth2ORCID,Lippl Maximilian2,Mechtler Klemens3,Krska Rudolf145ORCID

Affiliation:

1. Department of Agrobiotechnology, IFA‐Tulln, Institute of Bioanalytics and Agro‐Metabolomics University of Natural Resources and Life Sciences, Vienna Tulln an der Donau Austria

2. Austrian Agency for Health and Food Safety GmbH Institute for Animal Nutrition and Feed Vienna Austria

3. Austrian Agency for Health and Food Safety GmbH Institute for Sustainable Plant Production Vienna Austria

4. FFoQSI GmbH – Austrian Competence Centre for Feed and Food Quality, Safety and Innovation Tulln Austria

5. Institute for Global Food Security, School of Biological Sciences Queen's University Belfast Belfast UK

Abstract

AbstractBACKGROUNDMycotoxin surveys play an essential role in our food safety system. The obtained occurrence data form the basis for the assessment of the exposure of humans and animals to these toxic fungal secondary metabolites. Liquid chromatography coupled with tandem mass spectrometry (LC‐MS/MS) has become the gold standard for mycotoxin determination because it enables selective and sensitive multi‐toxin analysis. Simultaneous determination of several hundreds of secondary fungal metabolites is feasible using this technique. In this study, we combined a targeted dilute‐and‐shoot LC‐MS/MS‐based multi‐analyte approach with multivariate statistics for the analysis of Austrian wheat from two different years and different geographical origins.RESULTSWe quantified 47 secondary fungal metabolites, including regulated emerging and masked mycotoxins. The resulting multi‐mycotoxin occurrence data were further analyzed using both multivariate and univariate statistics. Principal component analysis (PCA) and analysis of variance (ANOVA) simultaneous component analysis (ASCA) were employed to identify regional and yearly trends within the dataset and to quantify the variance in metabolite occurrence attributed to the different effects. In addition, secondary fungal metabolites significantly impacted by these factors were selected via ANOVA. Of the 47 secondary metabolites identified, 39 were affected by the year, region or a combined effect. Moreover, our findings show that 43 of the secondary fungal metabolites were significantly influenced by the weather conditions.CONCLUSIONThe results presented in this study underline the added value of combining targeted LC‐MS/MS with multivariate statistics for monitoring a broad spectrum of secondary fungal metabolites in food crops. Through multivariate statistics, trends associated with the year or region can be readily studied. The approach presented could pave the way for a better understanding of the impact of climate change on plant pathogenic fungi and its implications for food safety. © 2024 The Author(s). Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Funder

European Commission

Horizon 2020 Framework Programme

Publisher

Wiley

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