Abstract

Patulin (PAT) and alternariol (AOH) are the main mycotoxin contaminants in fruits and their products, which have great toxic effects on human body due to their teratogenicity and carcinogenicity. This study proposed a surface enhanced Raman spectroscopy (SERS) technology combining chemometrics and coffee-ring effect to build high-throughput label-free detection models for PAT and AOH. A stable coffee ring structure was built by optimizing the drying temperature and droplet volume. Comparing the partial least squares (PLS) models grounded on variables selection method, the best performance was obtained by using synergy interval (Si) and genetic algorithm (GA) for PAT (Rc = 0.9905, Rp = 0.9759) and AOH (Rc = 0.9829, Rp = 0.9808), respectively. The limits of detection (LOD) for PAT and AOH were as low as 1 μg L−1, and the recovery rates were 92.80%–114.83% with relative standard deviation (RSD) ≤ 4.86 for PAT and 82.06%–108.13% with RSD ≤2.28% for AOH. The SERS technology combined with chemometrics and coffee-ring effect holds promise for high-throughput label-free detection of PAT and AOH in fruits and their products.

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