Simultaneous Measurement of Titratable Acidity and Fermentation Index in Cocoa Beans by Electronic Tongue Together with Linear and Non-linear Multivariate Technique

Abstract

Titratable acidity (TA) and fermentation index (FI) are important quality indicators of cocoa beans. This paper attempted the simultaneous analysis of these indicators by electronic tongue (ET) and two multivariate calibrations. ET was used for data acquisition, while partial least squares (PLSs) and principal component support vector machine regression (PC-SVMR) were used to build the calibration models. Some parameters were optimized simultaneously by leave-one-out cross-validation (LOOCV) in calibrating the model. The performance of the model was tested according to root mean square error of prediction (RMSEP) and correlation coefficient (R pre) in the prediction set. The results revealed that PC-SVMR model was superior to PLS model in this work. The optimal PC-SVMR model for TA was R pre = 0.960 and RMSEP = 0.0077, while for FI, this was R pre = 0.954 and RMSEP = 0.058. This study demonstrated that ET together with SVMR could be used to analyze titratable acidity and fermentation index in cocoa beans for quality control purposes.