Polina Fomina, Antoni Femenias, Miriam Aledda, Valeria Tafintseva, Stephan Freitag, Michael Sulyok, Achim Kohler, Rudolf Krska, Boris Mizaikoff
{"title":"Innovative Infrared Spectroscopic Technologies for the Prediction of Deoxynivalenol in Wheat.","authors":"Polina Fomina, Antoni Femenias, Miriam Aledda, Valeria Tafintseva, Stephan Freitag, Michael Sulyok, Achim Kohler, Rudolf Krska, Boris Mizaikoff","doi":"10.1021/acsfoodscitech.4c00730","DOIUrl":null,"url":null,"abstract":"<p><p>Mycotoxin contamination in cereals is a global food safety concern. One of the most common mycotoxins in grains is deoxynivalenol (DON), a secondary metabolite produced by the fungi<i>Fusarium graminearum</i> and <i>Fusarium culmorum</i>. Exposure to DON can lead to adverse health effects in both humans and animals including vomiting, dizziness, and fever. Hence, the development of analytical technologies capable of predicting mycotoxin contamination levels in grains is crucial. In this study, we emphasize innovative infrared (IR) spectroscopic technologies for the prediction of DON in wheat along the food supply chain. The performance of an IR laser spectroscopic platform for on-site or laboratory confirmative analysis was evaluated. Furthermore, the performance of a handheld IR spectrometer for preliminary screening during transportation, storage, or harvesting was assessed. The accuracy of cross validation (Acc<sub>CV</sub>) obtained with the laser spectrometer reached 92%, while the handheld IR spectrometer achieved 84.6%. Hence, both technologies prove significant potential for rapid mycotoxin detection.</p>","PeriodicalId":72048,"journal":{"name":"ACS food science & technology","volume":"5 1","pages":"209-217"},"PeriodicalIF":2.6000,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11744748/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS food science & technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1021/acsfoodscitech.4c00730","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/17 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Mycotoxin contamination in cereals is a global food safety concern. One of the most common mycotoxins in grains is deoxynivalenol (DON), a secondary metabolite produced by the fungiFusarium graminearum and Fusarium culmorum. Exposure to DON can lead to adverse health effects in both humans and animals including vomiting, dizziness, and fever. Hence, the development of analytical technologies capable of predicting mycotoxin contamination levels in grains is crucial. In this study, we emphasize innovative infrared (IR) spectroscopic technologies for the prediction of DON in wheat along the food supply chain. The performance of an IR laser spectroscopic platform for on-site or laboratory confirmative analysis was evaluated. Furthermore, the performance of a handheld IR spectrometer for preliminary screening during transportation, storage, or harvesting was assessed. The accuracy of cross validation (AccCV) obtained with the laser spectrometer reached 92%, while the handheld IR spectrometer achieved 84.6%. Hence, both technologies prove significant potential for rapid mycotoxin detection.