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推进谷物和油籽中真菌及霉菌毒素污染的检测:用于加强食品安全的高光谱成像技术

Advancing detection of fungal and mycotoxins contamination in grains and oilseeds: Hyperspectral imaging for enhanced food safety.

作者信息

Guo Zhen, Zhang Jing, Wang Haifang, Li Shiling, Shao Xijun, Xia Lianming, Darwish Ibrahim A, Guo Yemin, Sun Xia

机构信息

School of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo, Shandong 255049, China; Shandong Provincial Engineering Research Center of Vegetable Safety and Quality Traceability, No. 266 Xincun Xilu, Zibo, Shandong 255049, China; Zibo City Key Laboratory of Agricultural Product Safety Traceability, No. 266 Xincun Xilu, Zibo, Shandong 255049, China.

School of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo, Shandong 255049, China.

出版信息

Food Chem. 2025 Apr 1;470:142689. doi: 10.1016/j.foodchem.2024.142689. Epub 2024 Dec 30.

DOI:10.1016/j.foodchem.2024.142689
PMID:39742592
Abstract

Grains and oilseeds, including maize, wheat, and peanuts, are essential for human and animal nutrition but are vulnerable to contamination by fungi and their toxic metabolites, mycotoxins. This review provides a comprehensive investigation of the applications of hyperspectral imaging (HSI) technologies for the detection of fungal and mycotoxins contamination in grains and oilseeds. It explores the capability of HSI to identify specific spectral features of contamination and emphasized the critical role of sample properties and sample preparation techniques in HSI applications. Additionally, it reveals the challenges posed by the voluminous HSI data generated and discusses the application of sophisticated data processing techniques, including chemometrics methods and machine learning algorithms. The review highlights future research directions focused on refining HSI applications for practical use. Ultimately, this review underscores the potential of integrating HSI with advanced technologies to significantly enhance food safety and quality assurance.

摘要

谷物和油籽,包括玉米、小麦和花生,对人类和动物营养至关重要,但易受真菌及其有毒代谢产物——霉菌毒素的污染。本综述全面研究了高光谱成像(HSI)技术在检测谷物和油籽中真菌及霉菌毒素污染方面的应用。它探讨了HSI识别污染特定光谱特征的能力,并强调了样品特性和样品制备技术在HSI应用中的关键作用。此外,它揭示了所产生的大量HSI数据带来的挑战,并讨论了复杂数据处理技术的应用,包括化学计量学方法和机器学习算法。该综述突出了专注于完善HSI实际应用的未来研究方向。最终,本综述强调了将HSI与先进技术相结合以显著提高食品安全和质量保证的潜力。

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