|CHUANG, YUNG-KUN - NATIONAL TAIWAN UNIVERSITY|
|CHEN, SUMING - NATIONAL TAIWAN UNIVERSITY|
|Delwiche, Stephen - Steve|
|LO, Y. MARTIN - UNIVERSITY OF MARYLAND|
|TSAI, CHAO-YIN - NATIONAL TAIWAN UNIVERSITY|
|YANG, I-CHANG - NATIONAL SCIENCE COUNCIL|
Submitted to: Journal of Cereal Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/27/2014
Publication Date: 4/23/2014
Citation: Chuang, Y., Chen, S., Delwiche, S.R., Lo, Y., Tsai, C., Yang, I. 2014. Integration of independent component analysis with near infrared spectroscopy for evaluation of rice freshness. Journal of Cereal Science. 60:238-242.
Interpretive Summary: Rice, along with wheat and corn, is a major staple in the human diet worldwide. Upon harvest, the crop is typically stored under ambient conditions and eventually dehulled and milled to produce white rice. During this storage period, biochemical changes to the lipids within the seed result in undesirable changes to flavor. Conventional procedures for measuring rice freshness, such as by fat acidity analysis, are labor intensive and time consuming. This study examined an alternative approach, freshness characterization by near-infrared reflectance spectroscopy. Using a set of commercial samples drawn from six harvest periods corresponding to four years of storage, the near-infrared technique, through either graphical representation or linear regression modeling, demonstrated an ability to track age-related biochemical changes and hence rice freshness. This technology has immediate application in rice commerce where premiums are paid for new stock, which means that the need for monitoring becomes critical.
Technical Abstract: Determination of freshness is an important issue for rice quality. Near infrared spectroscopy, a rapid non-destructive inspection method based on specific absorptions within a given range of wavelengths, has been widely applied for evaluation of internal quality of agricultural products. For the purpose of this study the NIR spectra of a mixture are approximated as the linear addition of individual spectra of the constituents in the mixture using a technique called independent component analysis. By example, 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 of pH were determined by a conventional (bromothymol blue - methyl red) method. The calibration model of white rice pH yielded R-squared = 0.882, SEC = 0.20, SEP = 0.23, and bias = 0.068 using original full wavelength range (400 to 2498 nm) spectra and 5 independent components. Freshness of white rice can 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 a useful tool for evaluating rice freshness.