Discrimination of rice varieties using smartphone-based colorimetric sensor arrays and gas chromatography techniques.

Autor: Arslan M; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Zareef M; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Tahir HE; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Guo Z; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Rakha A; National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan., Xuetao H; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Shi J; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Zhihua L; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Xiaobo Z; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China. Electronic address: zou_xiaobo@ujs.edu.cn., Khan MR; National Institute of Food Science and Technology, University of Agriculture, Faisalabad 38000, Pakistan.
Jazyk: angličtina
Zdroj: Food chemistry [Food Chem] 2022 Jan 30; Vol. 368, pp. 130783. Date of Electronic Publication: 2021 Aug 06.
DOI: 10.1016/j.foodchem.2021.130783
Abstrakt: A smartphone-based colorimetric sensor array system was established for discrimination of rice varieties having different geographical origins. Purposely, aroma profiling of nine rice varieties was performed using solid-phase microextraction gas chromatography-mass spectrometry. Alcohols, aldehydes, alkanes, ketones, heterocyclic compounds, and organic acids represent the abundant compounds. Colorimetric sensor array system produced a characteristic color difference map upon its exposure to volatile compounds of rice. Discrimination of rice varieties was subsequently achieved using principal component analysis, hierarchical clustering analysis, and k-nearest neighbors. Rice varieties from same geographical source were clustered together in the scatter plot of principal component analysis and hierarchical clustering analysis dendrogram. The k-nearest neighbors algorithm delivered optimal results with discrimination rate of 100% for both calibration and prediction sets using sensor array system. The smartphone-based colorimetric sensor array system and gas chromatography technique were able to effectively differentiate rice varieties with the advantage of being simple, rapid, and low-cost.
(Copyright © 2021 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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