Tastant quantitative analysis from complex mixtures using taste cell-based sensor and double-layered cascaded series stochastic resonance

Abstract

In this paper, tastant quantitative analysis from complex mixtures using taste cell-based sensor and double-layered cascaded series stochastic resonance (DCSSR) method has been investigated. Taste cells, NCI-H716 cells and STC-1 cells, are cultured on carbon screen printed electrode (CSPE) to fabricate integrated sensing devices. Cell culture status on CSPE is observed by scanning electron microscope (SEM) method. Molecular components referring to taste receptor protein and signal transduction (α-gustducin) in taste cells are identified by immunocytochemistry. The chemical mixtures containing sweet/bitter tastants in 7 concentrations are measured by corresponding cell-based sensor. Real-time EIS measurement data of taste cell-based sensor is recorded and processed by DCSSR. Tastant mixtures containing the same chemical components share the same eigen peak located noise intensities (EPLNIs). Correlations and statistical tests on DCSSR signal-to-noise ratio (SNR) maximums (Max-SNR) have been conducted to give a clearly comparison with stochastic resonance (SR) method. Results demonstrate that DCSSR method presents better quantitative perception abilities for sucrose/quinine tastants than SR. Sucrose/quinine concentrations can be discriminated by Max-SNR values. The proposed method provides a promising way for the construction of a novel biological tongue.