A simple taste analyzing system design for visual and quantitative analysis of different tastes using multi-array chemical sensors and pattern recognition techniques

Kim, Jeong-Do; Byun, Hyung‐Gi; Kim, Dong-Jin; Ham, Yu-Kyung; Jung, Wi Hoon; Yoon, Chul-Oh

doi:10.1016/j.talanta.2006.01.020

Cited by 29 publications

(15 citation statements)

References 3 publications

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“…Um exemplo de biossensor existente são as línguas eletrônicas [57]. Esse tipo de sensor tem sido empregado para análise de diferentes substâncias que envolvem, por exemplo, a distinção de diferentes vinhos tintos [44], sucos de fruta, amostras de cerveja e chá [35], café, leite e derivados, além de detecção de traços de impurezas ou poluentes emágua [57]. Embora sensores e biossensores sejam ferramentas bastante difundidas, a interpretação dos dados gerados nãoé trivial devidoàs características nanométricas do seu processo de fabricação.É nesse cenário que as técnicas de projeção são empregadas, ajudando os especialistas no processo de exploração dos dados.…”

Section: Visualização De Dados Provenientes De Sensores E Biossensoresunclassified

Análise Visual utilizando Projeções Multidimensionais

Neves

Fadel

Coimbra

et al. 2015

RITA

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Section: Visualização De Dados Provenientes De Sensores E Biossensoresunclassified

Análise Visual utilizando Projeções Multidimensionais

Neves

Fadel

Coimbra

et al. 2015

RITA

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“…59 Uchida et al 60 evaluated orally disintegrating tablets (ODTs), 61 which disintegrate easily in the mouth without water and are prescribed for the elderly, children and patients with poor swallowing ability, using TS-5000Z and OD-mate (Model IMC-14D1, Higuchi Inc., Tokyo, Japan), which is based on a disintegration test method. 62 Other commercialized sensors are Astree II, [63][64][65] manufactured by Alpha MOS, France, and a Multiarray chemical sensor, 66 by McScience, Korea. These instruments help in market research, food control, and taste design for food and pharmaceuticals.…”

Section: Introductionmentioning

confidence: 99%

Taste Sensor: Electronic Tongue with Lipid Membranes

Tahara

Yatabe

et al. 2019

ANAL. SCI.

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Taste is of five basic types, namely, sourness, saltiness, sweetness, bitterness and umami. In this review, we focus on a potentiometric taste sensor that we developed and fabricated using lipid polymer membranes. The taste sensor can measure the taste perceived by humans and is called an electronic tongue with global selectivity, which is the property to discriminate taste qualities and quantify them without discriminating each chemical substance. This property is similar to the gustatory system; hence, the taste sensor is a type of biomimetic device. In this paper, we first explain the sensing mechanism of the taste sensor, its application to beer evaluation and the measurement mechanism. Second, results recently obtained are introduced; i.e., the application of the senor to high-potency sweeteners and the improvement of the bitterness sensor are explained. Last, quantification of the bitterness-masking effect of high-potency sweeteners is explained using a regression analysis based on both the outputs of bitterness and sweetness sensors. The taste sensor provides a biomimetic method different from conventional analytical methods.

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“…It is considered a kind of artificial intelligence (term applied to technologies that mimics knowledge similar to humans) [9] known for its capacity in converting numerical inputs into linguistic variables. However, few reports concerning the use of ET systems and Fuzzy logic are found in the literature [4,[10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Use of an Electronic Tongue System and Fuzzy Logic to Analyze Water Samples

Braga¹,

Paterno²,

Fonseca³

et al. 2009

AIP Conference Proceedings

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An electronic tongue (ET) system incorporating 8 chemical sensors was used in combination with two pattern recognition tools, namely principal component analysis (PCA) and Fuzzy logic for discriminating/classification of water samples from different sources (tap, distilled and three brands of mineral water). The Fuzzy program exhibited a higher accuracy than the PCA and allowed the ET to classify correctly 4 in 5 types of water. Exception was made for one brand of mineral water which was sometimes misclassified as tap water. On the other hand, the PCA grouped water samples in three clusters, one with the distilled water; a second with tap water and one brand of mineral water, and the third with the other two other brands of mineral water. Samples in the second and third clusters could not be distinguished. Nevertheless, close grouping between repeated tests indicated that the ET system response is reproducible. The potential use of the Fuzzy logic as the data processing tool in combination with an electronic tongue system is discussed.

show abstract

A simple taste analyzing system design for visual and quantitative analysis of different tastes using multi-array chemical sensors and pattern recognition techniques

Cited by 29 publications

References 3 publications

Análise Visual utilizando Projeções Multidimensionais

Análise Visual utilizando Projeções Multidimensionais

Taste Sensor: Electronic Tongue with Lipid Membranes

Use of an Electronic Tongue System and Fuzzy Logic to Analyze Water Samples

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