Discriminant analysis of multiple physicochemical properties for thai rough rice varietal authentication

Abstract

Rough rice variety is a factor influencing milling and eating qualities. To accomplish the prediction of five Thai rough rice varieties with high accuracy, physicochemical properties of those varieties were investigated and used for discriminant analysis. The results indicated that dry weight of a hundred rough rice grains and the content of brown rice protein offered moderate accuracy of 65.38 and 55.38%, respectively, in varietal differentiation in the validation set. Better distinction could be achieved using multiple properties, namely, the hundred-grain weight, brown rice protein content, milled rice protein content, apparent amylose content, and alkali spreading value. The developed model performed the definite prediction with 84.9% explained variances in the first two functions and 100% accuracy. Copyright © Taylor and Francis Group, LLC.