This study was carried out in Ghana, which has seen an increase in rice consumption, but also an increase in mislabelling and fraud of rice supplies. A rapid assay was developed using a pocket-sized NIR spectrometer and multivariate data for detecting rice integrity and fraud. A total of 112 rice samples were used in the study, made up of three different categories; 36 samples of the Jasmine variety, 36 samples of the Agra variety, and 40 adulterated Jasmine with Agra (10–40% w/w). It was found that powdered rice samples gave better results than rice grains. Chemometric analysis was used to model the best technique for simultaneous identification and quantification of rice variety integrity and adulteration. Spectral analysis by SD-PLSDA (second derivative - partial least squares discriminant analysis) could identify a variety and adulterated samples at 98% in both training and test sets. For quantification of the level of adulteration, Si-PLS (synergy interval - partial least squares) was a promising tool with R2 = 0.94 in both the training and testing sets. However, the authors of the study note that further investigation will be needed to establish whether satisfactory authentication of rice is possible for a wider population of rice samples.
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