College of Agriculture and Biotechnology, Hunan University of Humanities, Science and Technology, Loudi 417000, China; State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Quality and Standards for Agricultural Products, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China.
State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Quality and Standards for Agricultural Products, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2020 Jul 5;235:118266. doi: 10.1016/j.saa.2020.118266. Epub 2020 Mar 16.
In this work, a smart analytical strategy that combines excitation-emission matrix (EEM) fluorescence detection with alternating trilinear decomposition (ATLD) algorithm was developed for fast, on-line and interference-free study on the photodegradation kinetics of aflatoxin B (AFB) and aflatoxin G (AFG) in rice and wheat under UV-Vis light (λ = 250-500 nm) treatment. With the aid of prominent "second-order advantage" of ATLD method, pure fluorescence signals of two targeted analytes can be directly resolved out from heavily overlapping spectral environment and accurately quantified even in the presence of unknown matrix interferences. Cereal samples in kinetic processing of photodegradation were detected without complex pretreatment steps except for a simple extraction using methanol/water solution (4:1, v/v), which solves the problem facing varied matrix interferences in the case of on-line monitoring of aflatoxins. The kinetic signals of analytes of interest were directly extracted regardless of varied matrix backgrounds of various cereals. The kinetic curves and degradation speeds of AFB and AFG can be estimated by resolved quantitative data, optimal radiation conditions including 365 nm wavelength and 35 J m density were discussed for high-efficiency detoxification control of aflatoxins in rice and wheat. This strategy was promising to be as an alternative tool for eco-friendly photodegradation kinetic study of mycotoxins or other hazards in complex foodstuff matrixes.
在这项工作中，开发了一种将激发-发射矩阵（EEM）荧光检测与交替三线性分解（ATLD）算法相结合的智能分析策略，用于快速、在线且无干扰地研究在 UV-Vis 光（λ = 250-500 nm）处理下，大米和小麦中黄曲霉毒素 B（AFB）和黄曲霉毒素 G（AFG）的光降解动力学。借助 ATLD 方法的显著“二阶优势”，即使存在未知的基质干扰，也可以直接从严重重叠的光谱环境中解析出两个目标分析物的纯荧光信号，并对其进行准确量化。在光降解动力学处理过程中，无需进行复杂的预处理步骤，只需使用甲醇/水溶液（4:1，v/v）进行简单提取，即可检测谷物样品，从而解决了在线监测黄曲霉毒素时面临的各种基质干扰问题。无论各种谷物的基质背景如何，都可以直接提取感兴趣分析物的动力学信号。通过解析定量数据，可以估算 AFB 和 AFG 的动力学曲线和降解速度，并讨论了最佳辐射条件，包括 365nm 波长和 35 J m密度，以实现大米和小麦中黄曲霉毒素的高效解毒控制。该策略有望成为替代工具，用于研究复杂食品基质中真菌毒素或其他危害物的生态友好型光降解动力学。
