Integration of independent component analysis with near infrared spectroscopy for evaluation of rice freshness

Yung Kun Chuang, Yi Ping Hu, I. Chang Yang, Stephen R. Delwiche, Yangming Martin Lo, Chao Yin Tsai, Suming Chen

研究成果: 雜誌貢獻文章

14 引文 斯高帕斯(Scopus)

摘要

The storage time and conditions of rice has an enormous effect on its appearance, flavor, and quality of the nutrients; and the acidity of rice usually increases with prolonged storage. Therefore, evaluation of freshness is an important issue for rice quality. In this study, the NIR (near infrared) spectra combined with independent component analysis (ICA) technique was used to evaluate the rice freshness. A total of 180 white rice samples were collected from 6 crop seasons for the purpose of developing an ICA-NIR based procedure for rice freshness as quantified by pH values. Values of pH were determined by a BTB-MR (bromothymol blue - methyl red) method. The best calibration model of white rice was developed using the smoothed first derivative spectra, five ICs and cross-validation; the results indicated that r2 (coefficient of determination)=0.924, and in units of pH, SEC (standard error of calibration)=0.145, SEP (standard error of prediction)=0.146, bias=0.001, and RPD (residual predictive deviation)=3.65. Freshness of white rice could be distinguished either visually by a 3-dimensional diagram composed from ICs 2, 3 and 4, or statistically by a calibration model. The results show that ICA with NIR has the potential to be adopted as an effective method for evaluating rice freshness.
原文英語
頁(從 - 到)238-242
頁數5
期刊Journal of Cereal Science
60
發行號1
DOIs
出版狀態已發佈 - 2014
對外發佈Yes

ASJC Scopus subject areas

  • Food Science
  • Biochemistry

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