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Postharvest monitoring of organic potato (cv. Anuschka) during hot-air drying using Vis/NIR hyperspectral imaging

Moscetti, Roberto; Sturm, Barbara; Crichton, Stuart O.J.; Amjad, Waseem and Massantini, Riccardo (2017) Postharvest monitoring of organic potato (cv. Anuschka) during hot-air drying using Vis/NIR hyperspectral imaging. Journal of the Science of Food and Agriculture (J Sci Food Agric), 98 (7), pp. 2507-2517.

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Document available online at: http://onlinelibrary.wiley.com/doi/10.1002/jsfa.8737/abstract


The potential of hyperspectral imaging (500–1010 nm) was evaluated for monitoring of the quality of potato slices (var. Anuschka) of 5, 7 and 9 mm thickness subjected to air drying at 50 °C. The study investigated three different feature selection methods for the prediction of dry basis moisture content and colour of potato slices using partial least squares regression (PLS).
The feature selection strategies tested include interval PLS regression (iPLS), and differences and ratios between raw reflectance values for each possible pair of wavelengths (R[λ1]–R[λ2] and R[λ1]:R[λ2], respectively). Moreover, the combination of spectral and spatial domains was tested. Excellent results were obtained using the iPLS algorithm. However, features from both datasets of raw reflectance differences and ratios represent suitable alternatives for development of low-complex prediction models. Finally, the dry basis moisture content was high accurately predicted by combining spectral data (i.e. R[511 nm]–R[994 nm]) and spatial domain (i.e. relative area shrinkage of slice).
Modelling the data acquired during drying through hyperspectral imaging can provide useful information concerning the chemical and physicochemical changes of the product. With all this information, the proposed approach lays the foundations for a more efficient smart dryer that can be designed and its process optimized for drying of potato slices. © 2017 Society of Chemical Industry

EPrint Type:Journal paper
Keywords:Solanum tuberosum L., potato slice, convective air drying, smart drying, chemometrics, BÖLN, BOELN, BÖL, BOEL, FKZ 14OE006, SusOrganic
Subjects: Food systems > Processing, packaging and transportation
Research affiliation: European Union > CORE Organic Plus > SusOrganic
Germany > Federal Organic Farming Scheme - BOELN > Food > Processing
ISSN:online ISSN: 1097-0010
Related Links:http://coreorganicplus.org/research-projects/susorganic/, http://www.bundesprogramm.de, http://orgprints.org/perl/search/advanced?addtitle%2Ftitle=&keywords=14OE006&%20projects=BOELN&_order=bypublication&_action_search=Suchen
Deposited By: von Gersdorff, Gardis J.E.
ID Code:32359
Deposited On:26 Jan 2018 11:21
Last Modified:02 Jul 2018 07:39
Document Language:English
Refereed:Peer-reviewed and accepted

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