Abstract

Fermentation is critical in cacao processing which breakdowns sugar compounds in the pulp into organic acids. The produced organic acids stimulate enzymatic reactions in the beans which affect the flavor, taste, and color of the cacao beans. Acidity (pH) and moisture content of cacao beans influence the quality of cacao during fermentation. Those parameters are commonly measured using pH meter and gravimetric methods which are time-consuming and destructive.Therefore, the objective of this study was to develop non-destructive calibration models to predict the pH and moisture content of cacao beans at various fermentation levels using a visible near-infrared spectrometer and chemometric methods. The samples consisted of 315 cacao beans obtained from 3 regions (Lampung, Makasar, and Kulon Progo) at 3 levels of fermentation (non, half, full). The calibration and prediction models were performed by PLS regression which involves X variables (Vis/NIR measurement results) and Y variable (pH and moisture content). Smoothing, normalization baseline correction, standard normal variate (SNV), and multiplicative scattered correction (MSC) were used for spectra pre-processing. The research showed that the MSC method resulted in the best model for pH with the correlation coefficient of calibration and prediction were 0.76 and 0.68, respectively. Original and MSC methods resulted in the best model for moisture content with the same value of of 0.55 and of 0.41. The results showed the capability of Vis/NIR spectroscopy and the important role of chemometrics in developing models for predicting cacao bean quality parameters during fermentation.

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