Premium
Determination of rice type by 1 H NMR spectroscopy in combination with different chemometric tools
Author(s) -
Monakhova Yulia B.,
Rutledge Douglas N.,
Roßmann Andreas,
Waiblinger HansUlrich,
Mahler Manuela,
Ilse Maren,
Kuballa Thomas,
Lachenmeier Dirk W.
Publication year - 2014
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2576
Subject(s) - principal component analysis , chemometrics , linear discriminant analysis , independent component analysis , partial least squares regression , pattern recognition (psychology) , multivariate statistics , chemistry , mathematics , analytical chemistry (journal) , context (archaeology) , hierarchical clustering , artificial intelligence , nuclear magnetic resonance spectroscopy , chromatography , biological system , cluster analysis , statistics , computer science , stereochemistry , paleontology , biology
A 400‐MHz 1 H nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis were used in the context of food surveillance to discriminate 46 authentic rice samples according to type. It was found that the optimal sample preparation consists of preparing aqueous rice extracts at pH 1.9. For the first time, the chemometric method independent component analysis (ICA) was applied to differentiate clusters of rice from the same type (Basmati, non‐Basmati long‐grain rice, and round‐grain rice) and, to a certain extent, their geographical origin. ICA was found to be superior to classical principal component analysis (PCA) regarding the verification of rice authenticity. The chemical shifts of the principal saccharides and acetic acid were found to be mostly responsible for the observed clustering. Among classification methods (linear discriminant analysis, factorial discriminant analysis, partial least squares discriminant analysis (PLS‐DA), soft independent modeling of class analogy, and ICA), PLS‐DA and ICA gave the best values of specificity (0.96 for both methods) and sensitivity (0.94 for PLS‐DA and 1.0 for ICA). Hence, NMR spectroscopy combined with chemometrics could be used as a screening method in the official control of rice samples. Copyright © 2013 John Wiley & Sons, Ltd.