Identification of monofloral honey using voltammetric electronic tongue Original Research Article

Quality assessment of honey is often related to its floral origin which is a complex task to evaluate. Traditional technique of floral assessment is made by melissopalynological method. However, this method is quite time consuming and also often operator dependent. Thus, the fallout is a large range of error in interpretation of the result and hence there is considerable demand for instrumental methods to assess the identification of pollen in honey. In this pursuit, an electronic tongue based on cyclic voltammetry is developed to discriminate honey samples based on their floral types and is described in this paper. The technique has been investigated using platinum as the working electrode and the resultant current from the potentiostat has been considered for data analysis. The use of principal component analysis (PCA) and linear discriminate analysis (LDA) proves to be useful in clustering honey samples. Finally, classification performances are investigated using back-propagation multilayer perceptron (BP-MLP) and radial basis function (RBF) neural network models for identification of different floral origin of honey.