气候变化领域集成服务门户(CCPortal): Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis

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DOI	10.1021/acsfoodscitech.3c00674
	Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis
	Fomina, Polina; Femenias, Antoni; Tafintseva, Valeria; Freitag, Stephan; Sulyok, Michael; Aledda, Miriam; Kohler, Achim; Krska, Rudolf; Mizaikoff, Boris
发表日期	2024
EISSN	2692-1944
起始页码	4
结束页码	4
卷号	4 期号:4
英文摘要	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 mu g/kg but also provided valuable insights into the relevant parameters shaping these models.
英文关键词	attenuated total reflection; ATR; infraredspectroscopy; Fourier transform infrared spectroscopy; FTIR; deoxynivalenol; DON; fungalinfection; mycotoxins; wheat; sparse partialdiscriminant least-squares analysis; SPLS-DA
语种	英语
WOS研究方向	Food Science & Technology
WOS类目	Food Science & Technology
WOS记录号	WOS:001192142000001
来源期刊	ACS FOOD SCIENCE & TECHNOLOGY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/297328
作者单位	Ulm University; Norwegian University of Life Sciences; BOKU University; Queens University Belfast
推荐引用方式 GB/T 7714	Fomina, Polina,Femenias, Antoni,Tafintseva, Valeria,et al. Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis[J],2024,4(4).
APA	Fomina, Polina.,Femenias, Antoni.,Tafintseva, Valeria.,Freitag, Stephan.,Sulyok, Michael.,...&Mizaikoff, Boris.(2024).Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis.ACS FOOD SCIENCE & TECHNOLOGY,4(4).
MLA	Fomina, Polina,et al."Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis".ACS FOOD SCIENCE & TECHNOLOGY 4.4(2024).