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Combined analysis of near-infrared spectra, colour, and physicochemical information of brown rice to develop accurate calibration models for determining amylose content

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/78880

Title: Combined analysis of near-infrared spectra, colour, and physicochemical information of brown rice to develop accurate calibration models for determining amylose content
Authors: Diaz, Edenio Olivares Browse this author
Kawamura, Shuso Browse this author →KAKEN DB
Matsuo, Miki Browse this author
Kato, Mizuki Browse this author
Koseki, Shigenobu Browse this author →KAKEN DB
Keywords: Rice quality
Amylose content
Near-infrared spectroscopy
Calibration model accuracy
Chemometric techniques
Issue Date: 15-Jul-2019
Publisher: Elsevier
Journal Title: Food Chemistry
Volume: 286
Start Page: 297
End Page: 306
Publisher DOI: 10.1016/j.foodchem.2019.02.005
PMID: 30827610
Abstract: Amylose content is an important determinant of rice quality. Accurate non-destructive determination of amylose content remains a primary challenge for the rice industry. Here, we analysed the accuracy of three models for the non-destructive determination of amylose content. The models were developed by combining near-infrared spectra, colour, and physicochemical information relative to 832 brown rice samples from ten varieties produced between 2009 and 2017 in various regions of Hokkaido, Japan. Models describing low and ordinary amylose varieties were developed individually, merged, and validated using production year samples (2016-2017) different from the calibration set (2009-2015). The resulting accuracy was suitable for industrial application. With standard error of prediction = 0.70% and ratio of performance deviation = 3.56, the combination of near-infrared spectra and physicochemical information produced the most robust model, enabling more precise rice quality screening at grain elevators.
Rights: © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
https://creativecommons.org/licenses/by-nc-nd/4.0/
Type: article (author version)
URI: http://hdl.handle.net/2115/78880
Appears in Collections:農学院・農学研究院 (Graduate School of Agriculture / Faculty of Agriculture) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: Edenio Olivares Díaz

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