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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 | |
| 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
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| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/297327 |
| 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 | . Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis[J],2024,4(4). |
| APA | (2024).Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis.ACS FOOD SCIENCE & TECHNOLOGY,4(4). |
| MLA | "Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis".ACS FOOD SCIENCE & TECHNOLOGY 4.4(2024). |
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