The Differentiation of the Infestation of Wheat Grain with Fusarium poae from Three Other Fusarium Species by GC–MS and Electronic Nose Measurements

Piotr Borowik (), Marcin Stocki, Miłosz Tkaczyk, Przemysław Pluta, Tomasz Oszako, Rafał Tarakowski and Adam Okorski
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Piotr Borowik: Faculty of Physics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland
Marcin Stocki: Institute of Forest Sciences, Faculty of Civil Engineering and Environmental Sciences, Białystok University of Technology, ul. Wiejska 45E, 15-351 Białystok, Poland
Miłosz Tkaczyk: Forest Protection Department, Forest Research Institute, ul. Braci Leśnej 3, 05-090 Sękocin Stary, Poland
Przemysław Pluta: Forestry Students’ Scientific Association, Forest Department, Warsaw University of Life Sciences, Nowoursynowska 166, 02-787 Warsaw, Poland
Tomasz Oszako: Forest Protection Department, Forest Research Institute, ul. Braci Leśnej 3, 05-090 Sękocin Stary, Poland
Rafał Tarakowski: Faculty of Physics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland
Adam Okorski: Department of Entomology, Phytopathology and Molecular Diagnostics, Faculty of Agriculture and Forestry, University of Warmia and Mazury in Olsztyn, Pl. Łódzki 5, 10-727 Olsztyn, Poland

Agriculture, 2024, vol. 14, issue 7, 1-19

Abstract: The massive import of uncontrolled technical grain from the East into the European Community poses a risk to public health when it ends up in the mills to be used as flour for food purposes instead of being burnt (biofuel). In fungal infections of wheat, the most dangerous species belong to the genus Fusarium . F. poae is a pathogen that is most commonly isolated from cereals worldwide and causes various types of diseases in animals and humans due to the numerous toxins it produces. The manuscript reports an attempt to distinguish between four species of Fusarium , F. avanceum, F. langsethiae, F. poae , and F. sporotrichioides , in wheat grains by measuring the volatiles emitted. The patterns obtained from the signals captured by the electronic nose PEN3 were used to build the Random Forests classification model. The recall and precision of the classification performance for F. poae reached 91 and 87%, respectively. The overall classification accuracy reached 70%. Gas chromatography coupled with mass spectrometry (GC–MS) was used to analyze the chemical composition of the emitted volatiles. The patterns found in the GC–MS results allowed an explanation of the main patterns observed when analyzing the electronic nose data. The mycotoxins produced by the Fusarium species analyzed were detected. The results of the reported experiment confirm the potential of the electronic nose as a technology that can be useful for screening the condition of the grain and distinguishing between different pathogenic infestations.

Keywords: gas sensor; odor differentiation; pathogenic fungi; food biosecurity; Fusarium avenaceum; Fusarium langsethiae; Fusarium poae; Fusarium sporotrichioides (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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