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Hyperspectral imaging for the determination of potato slice moisture content and chromaticity during the convective hot air drying process

Amjad, Waseem; Crichton, Stuart O.J.; Munir, Anjum; Hensel, Oliver and Sturm, Barbara (2018) Hyperspectral imaging for the determination of potato slice moisture content and chromaticity during the convective hot air drying process. Biosystems Engineering, 166, pp. 170-183.

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Document available online at: https://www.sciencedirect.com/science/article/pii/S1537511016305967


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 °C, 60 °C, 70 °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 R2 (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 (R2 = 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 (R2 = 0.91–0.65, RMSE = 0.61–1.78). PLS Models for CIELAB b* more variably (R2 = 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.

EPrint Type:Journal paper
Keywords:Hyper-spectral imaging, Convective drying, Partial least square, Moisture content, Wavelength selection, BÖLN, BOELN, BÖL, BOEL, FKZ 14OE006, CoreOrganicPlus, SusOrganic
Subjects: Food systems > Processing, packaging and transportation
Research affiliation:Other countries
European Union > CORE Organic Plus > SusOrganic
UK > Univ. Newcastle
Germany > University of Kassel
Related Links:http://www.bundesprogramm.de, https://orgprints.org/cgi/search/advanced?addtitle%2Ftitle=&keywords=14OE006&projects=BOEL&_order=bypublication&_action_search=Suchen, http://projects.au.dk/coreorganicplus/research-projects/susorganic/
Deposited By: von Gersdorff, Gardis J.E.
ID Code:32984
Deposited On:15 Jun 2018 09:03
Last Modified:15 Jun 2018 09:03
Document Language:English
Refereed:Peer-reviewed and accepted

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