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Related Concept Videos

Gustation01:43

Gustation

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Gustation is a chemical sense that, along with olfaction (smell), contributes to our perception of taste. It starts with the activation of receptors by chemical compounds (tastants) dissolved in the saliva. The saliva and filiform papillae on the tongue distribute the tastants and increase their exposure to the taste receptors.
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A Quantitative Method for Acesulfame K Using the Taste Sensor.

Yuanchang Liu1, Xiao Wu2, Yusuke Tahara2

  • 1Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan.

Sensors (Basel, Switzerland)
|January 16, 2020
PubMed
Summary
This summary is machine-generated.

A new taste sensor quantifies high-potency sweeteners, even with salty substances. A predictive model using relative values accurately estimates acesulfame potassium concentration in food and beverages.

Keywords:
acesulfame Khigh-potency sweetenerslipid polymer membranesweetness sensortaste sensor

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Area of Science:

  • * Analytical Chemistry
  • * Food Science
  • * Sensor Technology

Background:

  • * Quantifying sweetness in complex mixtures, especially with negatively charged high-potency sweeteners, presents analytical challenges.
  • * Existing taste sensors may lack selectivity or sensitivity when multiple taste substances are present.

Purpose of the Study:

  • * To develop a method for accurately quantifying high-potency sweeteners in the presence of other taste substances.
  • * To enhance the sensitivity and selectivity of taste sensors for sweetener analysis.

Main Methods:

  • * Development of a taste sensor utilizing lipid polymer membranes.
  • * Measurement of two output values: relative value and CPA (change in membrane potential caused by adsorption).
  • * Application of nonlinear regression analysis using relative values from sweetness and saltiness sensors to predict sweetener concentration.

Main Results:

  • * The CPA value demonstrated good selectivity for high-potency sweeteners.
  • * A predictive model combining relative values from sweetness and saltiness sensors achieved high correlation (R² = 0.99) for acesulfame potassium.
  • * The model accurately predicted acesulfame potassium concentrations (0.2-0.7 mM) relevant to food and beverage applications.

Conclusions:

  • * The developed method effectively quantifies sweeteners like acesulfame potassium in complex matrices.
  • * The combined sensor approach overcomes limitations of individual sensor outputs, offering both sensitivity and selectivity.
  • * This taste sensor system shows significant potential for evaluating sweeteners in the food and beverage industry.