One-component Model Approach for Sensing the Sweetness, Sourness and Astringency of Rice

Abstract

This paper deals with a new one-component model approach for sensing the sweetness, sourness, and astringency of rice. Chemical indexes of rice were analyzed, and the sensory score was obtained by sensory evaluation. It was resulted that dominant components for sweetness, sourness and astringency of rice were sucrose, acidity and tannic acid, respectively. A multi-metal sensor was used to quantify the taste perception of sweetness, sourness and astringency through taste stimuli corresponding to dominant components. Continuous Wavelet Transform (CWT) was applied to transform the original voltammetric signal into CWT coefficient curve. The one-component (OC) model with the accuracy of 81.5% was established via neural network method, and used to predict the gustatory values of rice. The correlation analysis between sensory score and gustatory value was applied to clarity the ability of OC model. It was concluded that one-component model approach could accurately sense the sweetness, sourness, astringency of rice.

Sensorial Perception of Astringency: Oral Mechanisms and Current Analysis Methods

“…The recently suggested one-component model (OC) approach could determine rice sweetness, acidity, and astringency through sensor measurement, sensory evaluation, chemical analysis, and data processing [ 118 ]. The OC model was developed for the multi-metal sensor using artificial neural network methods that simulate the biological neural network seeking to implement its basic taste behavior and predict the gustatory values.…”