Document Detail

Nondestructive prediction of total phenolics, flavonoid contents, and antioxidant capacity of rice grain using near-infrared spectroscopy.
MedLine Citation:
PMID:  18729464     Owner:  NLM     Status:  MEDLINE    
Phytochemicals such as phenolics and flavonoids, which are present in rice grains, are associated with reduced risk of developing chronic diseases such as cardiovascular disease, type 2 diabetes, and some cancers. The phenolic and flavonoid compounds in rice grain also contribute to the antioxidant activity. Biofortification of rice grain by conventional breeding is a way to improve nutritional quality so as to combat nutritional deficiency. Since wet chemistry measurement of phenolic and flavonoid contents and antioxidant activity are time-consuming and expensive, a rapid and nondestructive predictive method based on near-infrared spectroscopy (NIRS) would be valuable to measure these nutritional quality parameters. In the present study, calibration models for measurement of phenolic and flavonoid contents and antioxidant capacity were developed using principal component analysis (PCA), partial least-squares regression (PLS), and modified partial least-squares regression (mPLS) methods with the spectra of the dehulled grain (brown rice). The results showed that NIRS could effectively predict the total phenolic contents and antioxidant capacity by PLS and mPLS methods. The standard errors of prediction (SEP) were 47.1 and 45.9 mg gallic acid equivalent (GAE) for phenolic content, and the coefficients of determination ( r (2)) were 0.849 and 0.864 by PLS and mPLS methods, respectively. Both PLS and mPLS methods gave similarly accurate performance for prediction of antioxidant capacity with SEP of 0.28 mM Trolox equivalent antioxidant capacity (TEAC) and r (2) of 0.82. However, the NIRS models were not successful for flavonoid content with the three methods ( r (2) < 0.4). The models reported here are usable for routine screening of a large number of samples in early generation screening in breeding programs.
Caiya Zhang; Yun Shen; Jian Chen; Peng Xiao; Jinsong Bao
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2008-08-27
Journal Detail:
Title:  Journal of agricultural and food chemistry     Volume:  56     ISSN:  1520-5118     ISO Abbreviation:  J. Agric. Food Chem.     Publication Date:  2008 Sep 
Date Detail:
Created Date:  2008-09-17     Completed Date:  2008-11-10     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0374755     Medline TA:  J Agric Food Chem     Country:  United States    
Other Details:
Languages:  eng     Pagination:  8268-72     Citation Subset:  IM    
Institute of Statistics, Department of Mathematics, Zhejiang University, Yuquan Campus, Hangzhou 310027, People's Republic of China.
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MeSH Terms
Antioxidants / analysis*
Cereals / chemistry*
Flavonoids / analysis*
Oryza sativa / chemistry*
Phenols / analysis*
Reproducibility of Results
Spectroscopy, Near-Infrared*
Reg. No./Substance:
0/Antioxidants; 0/Flavonoids; 0/Phenols

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