Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7591672 | Food Chemistry | 2015 | 28 Pages |
Abstract
Mango slices were dried by microwave-vacuum drying using a domestic microwave oven equipped with a vacuum desiccator inside. Two lab-scale hyperspectral imaging (HSI) systems were employed for moisture prediction. The Page and the Two-term thin-layer drying models were suitable to describe the current drying process with a fitting goodness of R2Â =Â 0.978. Partial least square (PLS) was applied to correlate the mean spectrum of each slice and reference moisture content. With three waveband selection strategies, optimal wavebands corresponding to moisture prediction were identified. The best model RC-PLS-2 (Rp2Â =Â 0.972 and RMSEPÂ =Â 4.611%) was implemented into the moisture visualization procedure. Moisture distribution map clearly showed that the moisture content in the central part of the mango slices was lower than that of other parts. The present study demonstrated that hyperspectral imaging was a useful tool for non-destructively and rapidly measuring and visualizing the moisture content during drying process.
Keywords
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Yuan-Yuan Pu, Da-Wen Sun,