期刊
BIOSYSTEMS ENGINEERING
卷 166, 期 -, 页码 170-183出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.biosystemseng.2017.12.001
关键词
Hyper-spectral imaging; Convective drying; Partial least square; Moisture content; Wavelength selection
资金
- German Academic Exchange Service (DAAD) Germany Forschungsstipendien fur Doktoranden und Nachwuchswissenschaftler [57076385]
- Core Organic Plus Program [2814OE006]
- University of Kassel, Germany within the Nachwuchsgruppen program
Hyperspectral imaging (HSI) was utilised for the determination of moisture content of potato slices with three thicknesses (5 mm, 7 mm, 9 mm) at three drying temperatures (50 degrees C, 60 degrees C, 70 degrees C) during convective drying in a laboratory hot air dryer. The Page, thin-layer drying model was found better to explain the drying kinetics with a fitting accuracy of R-2 (0.96-0.99) and lowest reduced Chi-square (0.00024-0.00090), Root mean square errors (RMSE) (0.014- 0.026), and relative percentage error (1.5%-5.1%) under the used drying conditions. Spectral data were analysed using partial least squares regression (PLS) analysis, a multivariate calibration technique, alongside Monte Carlo Uninformative Variable Elimination (MCUVE-PLS) and competitive adaptive reweighted sampling (CARS-PLS). The feasibility of both moisture content and CIELAB prediction with a reduced wavelength set from the Visible near-infrared (VNIR) region (500-1000 nm) was investigated with these three models. The PLS model (R-2 = 0.93-0.98, RMSE = 0.16-0.36 and the lowest number of optimal wavelengths = 6, for all drying conditions) was found suitable to implement for the moisture visualisation procedure. Potato chromaticity was also shown to be predictable during drying using a similar number of wavelengths, with PLS models for CIELAB a* performing well (R-2 = 0.91-0.65, RMSE = 0.61-1.78). PLS Models for CIELAB b* more variably (R-2 = 0.91-0.62, RMSE = 2.16-4.42) due to potato colour mainly varying along this axis. The current study showed that hyperspectral imaging was a useful tool for non-destructive measurement and visualisation of the moisture content and chromaticity during the drying process. (C) 2017 IAgrE. Published by Elsevier Ltd. All rights reserved.
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