Abstract

Nutritional parameters vary significantly among different varieties of mango. It is therefore necessary to have simple method to classify mango pulps according to their nutritional parameters by effective and economic technique. The present study was carried out to develop a method to classify mango varieties by using two chemometric techniques namely, Artificial Neural Network (ANN) and Linear Discrimination Analysis (LDA). At first, 9 physico-chemical parameters have been chosen from 18 of them by applying Factor Analysis (FA), as quantification of each parameter involves time and cost. Nine varieties of mango available in Bangladesh were studied her. LDA can classify the mango pulps on the basis of their nutritional properties 100 percent accurately, and this rate for ANN is 96.3 percent. Therefore, a method is being proposed where mango can be classified with their 9 physico-chemical parameters into their right varieties by LDA. The proposed chemometric method could be used for regular classification of mango pulps at laboratory and mango product manufacturing industries to improve the quality of mango products.Bangladesh J. Sci. Ind. Res. 51(4), 253-260, 2016

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