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The dissipation of six pesticides (carbendazim, thiabendazole, procymidone, bifenthrin, λ-cyhalothrin, and β-cyfluthrin) in shiitakes from cultivation to postharvest drying process was investigated, and the dietary exposure risk was estimated thereafter. The field trial study indicates that the half-lives of carbendazim, thiabendazole, and procymidone were much shorter than those of bifenthrin, λ-cyhalothrin, and β-cyfluthrin. Furthermore, the effects of two drying processes on the residues and processing factors (PFs) were investigated. The results showed that hot-air drying resulted in higher residues than sunlight exposure drying. Both drying processes led to pesticide residue concentration (with PF > 1), except for thiabendazole upon sunlight exposure treatment. The estimated daily intakes (EDIs) ranged from 0.06% of the acceptable daily intake (ADI) for thiabendazole to 42.43% of the ADI for procymidone. The results show that the six pesticide residues in dried shiitakes are still within acceptable levels for human consumption on the basis of a dietary risk assessment.

The potential of visible-near infrared (vis/NIR) spectroscopy (400 nm to 1100 nm) for classification of grape berries on the basis of multi inner quality parameters was investigated. Stored Vitis vinifera L. cv. Manicure Finger and Vitis vinifera L. cv. Ugni Blanc grape berries were separated into three classes based on the distribution of total soluble solid content (SSC) and total phenolic compounds (TP). Partial least squares regression (PLS) was applied to predict the quality parameters, including color space CIELAB, SSC, and TP. The prediction results showed that the vis/NIR spectrum correlated with the SSC and TP present in the intact grape berries with determination coefficient of prediction (RP2) in the range of 0.735 to 0.823. Next, the vis/NIR spectrum was used to distinguish between berries with different SSC and TP concentrations using partial least squares discrimination analysis (PLS-DA) with >77% accuracy. This study provides a method to identify stored grape quality classes based on the spectroscopy and distributions of multiple inner quality parameters.

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