Abstract
Mycotoxins are a class of highly carcinogenic substances often naturally occurring in the moldy foods especially cereals. In the present work, a smart chemometrics-assisted analytical strategy that combines liquid chromatography-full scan-mass spectrometry (LC-MS) detection with second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm is developed for direct, fast and interference-free determination of multi-class regulated mycotoxins in complex cereal samples with one-step ultrasound-assisted extraction. Ten mycotoxins with different property are fast eluted out (9.0min) under a simple gradient LC-separation and detected by full scanning MS with a segmented fragment program. With the aid of prominent "second-order advantage" of the algorithm, the problems of co-eluted peaks, unknown interferences and baseline drifts occurring in the LC-MS profiles are mathematically resolved, making "pure signals" of targeted analytes can be extracted out from heavily interferential information. The new strategy avoids intricate physical/chemical clean-up steps to significantly improve the accuracy of the trace analysis of mycotoxins, average recoveries of ten analytes in both complex cereal samples (maize and rice) range from 93.8 to 109% with standard deviations (SD) lower than 9.8%, and the limits of detection (LOD) range from 0.01 to 1.17 μg kg−1. In order to further confirm the reliability of the method, the same batch of samples is analyzed using LC-MS2 method with complicated immunoaffinity column (IAC) purification step, the elliptical joint confidence region (EJCR) tests of quantitative results of ten mycotoxins show that higher precision is obtained using the proposed method. Therefore, this new strategy can be as an attractive alternative for simple, fast and accurate determination of multi-class mycotoxins in complex cereal samples.
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