Prediction of deoxynivalenol contamination in wheat via infrared attenuated total reflection spectroscopy and multivariate data analysis
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Date
2024-03-25
Authors
Fomina, Polina
Femenias, Antoni
Tafintseva, Valeria
Freitag, Stephan
Sulyok, Michael
Aledda, Miriam
Kohler, Achim
Krska, Rudolf
Mizaikoff, Boris
Journal Title
Journal ISSN
Volume Title
Publication Type
Wissenschaftlicher Artikel
Published in
ACS Food Science & Technology, 2024
Abstract
The climate crisis further exacerbates the challenges for food production. For instance, the increasingly unpredictable growth of fungal species in the field can lead to an unprecedented high prevalence of several mycotoxins, including the most important toxic secondary metabolite produced by Fusarium spp., i.e., deoxynivalenol (DON). The presence of DON in crops may cause health problems in the population and livestock. Hence, there is a demand for advanced strategies facilitating the detection of DON contamination in cereal-based products. To address this need, we introduce infrared attenuated total reflection (IR-ATR) spectroscopy combined with advanced data modeling routines and optimized sample preparation protocols. In this study, we address the limited exploration of wheat commodities to date via IR-ATR spectroscopy. The focus of this study was optimizing the extraction protocol for wheat by testing various solvents aligned with a greener and more sustainable analytical approach. The employed chemometric method, i.e., sparse partial least-squares discriminant analysis, not only facilitated establishing robust classification models capable of discriminating between high vs low DON-contaminated samples adhering to the EU regulatory limit of 1250 μg/kg but also provided valuable insights into the relevant parameters shaping these models.
Description
Faculties
Fakultät für Naturwissenschaften
Institutions
Institut für Analytische und Bioanalytische Chemie
Citation
DFG Project uulm
EU Project THU
Photonfood / Flexible mid-infrared photonic solutions for rapid farm-to-fork sensing of food contaminants / EC / H2020 / 101016444
Other projects THU
License
CC BY 4.0
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DOI external
DOI external
10.1021/acsfoodscitech.3c00674
Institutions
Periodical
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DFG Project THU
item.page.thu.projectEU
item.page.thu.projectOther
Series
Keywords
Attenuated total reflection, ATR, Infraredspectroscopy, Fourier transform infrared spectroscopy, FTIR, Deoxynivalenol, DON, Fungalinfection, Mycotoxins, Wheat, Sparse partialdiscriminant least-squares analysis, SPLS-DA, DDC 570 / Life sciences