All-solid-state electronic tongue and its application for beverage analysis

Lvova, Larisa; Kim, Soon Shin; Legin, Andrey; Vlasov, Yu. G.; Yang, Jong Soo; Sig, Geun; Nam, Hakhyun

doi:10.1016/s0003-2670(02)00690-6

Cited by 99 publications

(50 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In the last decade, potentiometric sensor arrays have been widely used in food analysis namely, for milk recognition and classification [2,[4][5][6], wine recognition and quantitative analysis and its correlation with human sensory perception [7], beer recognition [2,8], plant samples recognition and classification [9], beverage analysis [2,[10][11][12], soy sauce taste analysis [13] and honey classification according to the pollen type [14]. In these works, several types of sensors have been tested in the potentiometric devices, namely lipid membranes [2,13], chalcogenide sensors [15], cation and anion-sensitive PVC based membranes [5,11], cation and anion-sensitive and partially selective electrodes [4,6,8,12,16], and polymeric membranes formed on solid conducting silver supports [14].…”

Section: Introductionmentioning

confidence: 99%

“…In these works, several types of sensors have been tested in the potentiometric devices, namely lipid membranes [2,13], chalcogenide sensors [15], cation and anion-sensitive PVC based membranes [5,11], cation and anion-sensitive and partially selective electrodes [4,6,8,12,16], and polymeric membranes formed on solid conducting silver supports [14].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An electronic tongue taste evaluation: Identification of goat milk adulteration with bovine milk

Dias

Peres

Veloso

et al. 2009

Sensors and Actuators B: Chemical

185

112

View full text Add to dashboard Cite

a b s t r a c tAn electronic tongue with 36 cross-sensibility sensors was built allowing a successful recognition of the five basic taste standards, showing high sensibility to acid, salty and umami taste substances and lower performance to bitter and sweet tastes. The taste recognition capability was afterwards tested in the detection of goat milk adulteration with bovine milk, which is a problem for the dairy industry. This new methodology is an alternative to the classical analytical methods used to detect caprine milk adulterations with bovine milk, being a simpler, faster and economical procedure. The different signal profiles recorded by the e-tongue device together with linear discriminant analysis allowed the implementation of a model that could distinguish between raw skim milk groups (goat, cow and goat/cow) with an overall sensibility and specificity of 97% and 93%, respectively. Furthermore, cross-validation showed that the model was able to correct classify unknown milk samples with a sensibility and specificity of 87% and 70%, respectively. Additionally, the model robustness was confirmed since it correctly or incorrectly classified milk samples with, respectively, higher and lower probabilities than those that could be expected by chance.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An electronic tongue taste evaluation: Identification of goat milk adulteration with bovine milk

Dias

Peres

Veloso

et al. 2009

Sensors and Actuators B: Chemical

185

112

View full text Add to dashboard Cite

show abstract

“…Ejemplo de estos dispositivos son la nariz electrónica, que utiliza sensores químicos capaces de detectar gases y aromas [1][2][3] y la lengua electrónica [3][4][5][6], o sensor de gusto [7], instrumento analítico basada en la combinación de una matriz de sensores, que presentarán alteraciones de algunas de sus propiedades, esta alteración se puede relacionar con los compuestos químicos específicos que la han producido y permiten identificarlos y cuantificarlos [8].…”

Section: Introductionunclassified

“…Entre las técnicas electroquímicas utilizadas en una lengua electrónica se encuentran la potenciometría [4,[22][23], la amperometría [24,25] y la voltametría [5,18,[26][27]. El uso de la voltametría presenta varias ventajas como mayor sensibilidad, versatilidad, sencillez, robustez y es menos influenciada por las perturbaciones eléctricas y por lo tanto tendrá una señal con mayor inmunidad al ruido, y como desventaja está la arquitectura de la celda [25,28].…”

Section: Introductionunclassified

Sistema multicanal con instrumentación virtual para una lengua electrónica

2014

Ingeniare. Rev. chil. ing.

View full text Add to dashboard Cite

RESUMENSe desarrolló un sistema multipotenciostato para una lengua electrónica utilizando la instrumentación virtual para el control, adquisición y manipulación de los datos generados y obtenidos en un proceso electroquímico basado en la técnica de voltametría cíclica. Se desarrolló un software de aplicación con Labview 2009 ® y se utilizaron los módulos de adquisición de datos NI 9263 (módulo de entrada de corriente analógica de ocho canales), NI 9203 (módulo de entrada de voltaje analógico de cuatro canales) y el chasis CompactDAQ USB 9174 de National Instruments ®. Se implementó el circuito básico del multipotenciostato con amplificadores operacionales OP77 y se diseñó una fuente regulada de ±5 V para la alimentación de los operacionales. Los electrodos utilizados en las pruebas fueron desarrollados en el laboratorio de la Universidad Pontificia Bolivariana Seccional Montería. Adicionalmente, el sistema implementado se utilizó para la discriminación y clasificación de muestras de café de tipo comercial en la región. Este tipo de desarrollos tecnológicos basados en instrumentación virtual no han sido reportados en la literatura, lo que convierte a esta investigación en un aporte novedoso en el campo de las lenguas electrónicas.Palabras clave: Adquisición de datos, instrumentación virtual, multipotenciostato, voltametría cíclica, lengua electrónica. ABSTRACT A multipotentiostat system for an electronic tongue by using virtual instrumentation for the control, adquisition and manipulation of the data generated and obtained in an electrochemical process based on the cyclic voltammetry technique was developed. A Labview

show abstract

“…The taste sensors proposed by Toko and his co-workers (Toko 2000) consist of potentiometric electrodes with lipid membranes (PVC membranes with lipid derivatives) and claimed to be capable of discriminating several kinds of foodstuffs such as beer, coffee, and even tomatoes (Kikkawa et al 1993) with the help of principal component analysis (PCA). Another version of the potentiometric electronic tongue composed of solid-state crystalline ion-selective electrodes based on chalcogenide glass (Vlasov et al 1994;Vlasov et al 2000) was applied for the discrimination of beverages (Lvova et al 2002). The pattern recognition block of that system involved mainly PCA and some kinds of artificial neural networks (ANN) (Vlasov et al 1997).…”

Section: Introductionmentioning

confidence: 99%

Classification of Green and Black Teas by PCA and SVM Analysis of Cyclic Voltammetric Signals from Metallic Oxide-Modified Electrode

et al. 2013

View full text Add to dashboard Cite

Forty-three samples of green and black teas were analyzed by an electronic tongue technique. A class of metallic oxide-modified nickel foam electrodes (SnO 2 , ZnO, TiO 2 , Bi 2 O 3 ) was compared in their sensitivity in this system. The signals obtained by cyclic voltammetry were submitted to multivariate data analysis. In the explorative analysis based on principal component analysis (PCA), the score plots showed that two of these sensors were able to distinguish varieties of teas. The resulting PCA scores were modeled with a support vector machine (SVM) that accomplished final prediction with the qualitative classification of teas. The optimal SVM model was achieved after grid search optimization of some parameters and the conduction of the three commonly used kernel functions. With a comparison of classification accuracies, Bi 2 O 3 -modified nickel foam electrode performed the best among the four electrodes and SVM model using the polynomial kernel attained the highest within the three used kernels. This work demonstrated that cyclic voltammetry combined with the SVM pattern recognition method could be successfully applied in the classification of green and black teas.

show abstract

All-solid-state electronic tongue and its application for beverage analysis

Cited by 99 publications

References 29 publications

An electronic tongue taste evaluation: Identification of goat milk adulteration with bovine milk

An electronic tongue taste evaluation: Identification of goat milk adulteration with bovine milk

Sistema multicanal con instrumentación virtual para una lengua electrónica

Classification of Green and Black Teas by PCA and SVM Analysis of Cyclic Voltammetric Signals from Metallic Oxide-Modified Electrode

Contact Info

Product

Resources

About