Quality of Industrially Processed Fruit Juices: An Assessment Using Multivariate Framework

Abstract

A multivariate statistical technique, called Discriminant Analysis (DA) has been applied for the evaluation of fruit juices quality variations and the interpretation of juices quality. Data set on two types namely, mango (Mangifera indica) and orange (Citrus sinensis) fruit juices in Bangladesh incorporating 17 variables for 9 different local manufacturing companies have been used. One sample t-test and independent samples t-test were also used to analyze the physico-chemical values and microbiological counts. DA gave the best result to identify the relative contribution of variables in discriminating (distinguishing) the two types of juices affording 100% correct assignations. This study illustrates the benefit of multivariate statistical techniques for analyzing and interpretation of complex data sets and to plan for future studies. DA indicated that copper was the main contributor in discriminating the two types of fruit juices. The t-tests results obtained showed that there were no significant differences in acidity, arsenic, lead, zinc, copper and standard plate count content between samples standards, while significant differences were observed in total soluble solid, ash and vitamin C compositions between samples standards.