Identification of wheat varieties with a parallel-plate capacitance sensor using fisher's linear discriminant analysis

Abstract

Fisher's linear discriminant (FLD) models for wheat variety classification were developed and validated. The inputs to the FLD models were the capacitance (C), impedance (Z), and phase angle (θ), measured at two frequencies. Classification of wheat varieties was obtained as output of the FLD models. Z and θ of a parallel-plate capacitance system, holding the wheat samples, were measured using an impedance meter, and the C value was computed. The best model developed classified the wheat varieties, with accuracy of 95.4%, over the six wheat varieties tested. This method is simple, rapid, and nondestructive and would be useful for the breeders and the peanut industry. © 2014 C. V. K. Kandala et al.