Recent achievements in electronic tongue and bioelectronic tongue as taste sensors

Ha, Da; Sun, Qiyong; Su, Kaile; Wan, Hao; Liu, Hai-Bo; Xu, Ning; Sun, Fei; Zhuang, Liujing; Hu, Ning; Wang, Ping

doi:10.1016/j.snb.2014.09.077

Cited by 153 publications

(76 citation statements)

References 113 publications

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“…The first was reproducing, by usage of conventional potentiometric sensors, as it is the case with commercial instruments Astree (from Alpha-MOS) [81] and Insent [82]. On the other hand, the most recent attempts to replicate taste have been done by designing BioETs that employ as sensing elements sensing proteins and receptors originally intervening in the sense of taste, therefore doing a complete translation of physiology into a biosensing instrument [83].…”

Section: Discussionmentioning

confidence: 99%

Bioelectronic Tongues Employing Electrochemical Biosensors

Valle

2016

Bioanalytical Reviews

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This chapter presents recent advances concerning work with electronic tongues that employ electrochemical biosensors, that is, bioelectronic tongues. (Bio)electronic tongues represent a new methodological use of (bio)sensors; they start by the use of biosensor arrays and assume the coupling of the obtained complex response with advanced chemometric data treatment; the goal is improving performance of existing sensors. Most of the bioelectronic tongues reported employ enzyme biosensors, essentially based on potentiometric or voltammetric/ amperometric transduction. This report is organized considering the different forms to incorporate biosensors, i.e. considering the number of biosensors in the array, the number of different enzymes used, if the determination is aimed to substrates or inhibitors, etc. Significant applications in real problem-solving, mainly in the food and clinical or environmental fields, are commented.

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Section: Discussionmentioning

confidence: 99%

Bioelectronic Tongues Employing Electrochemical Biosensors

Valle

2016

Bioanalytical Reviews

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“…15 the brain interprets these signals and makes a judgment or classification to identify the substances concerned, based on the experiences or neural network pattern recognition (Ha et al, 2015). However, sensory evaluation using a human panel is highly influenced by physical and psychological conditions as well as individual preference of the panellist, which may result in low objectivity and reproducibility.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Challenges in relating concentrations of aromas and tastes with flavor features of foods

Regueiro

Negreira

Simal‐Gándara

2015

Critical Reviews in Food Science and Nutrition

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Flavor sensations in food are highly influenced by the aroma and taste compounds. Reviewing the extensive literature of recent years in this field has shown that the reconstitution of flavor based on aroma and taste compounds poses numerous problems. These are of different nature and include among others (a) chemical transformations among these compounds, (b) changes in the concentrations of the compounds responsible for the perceived flavor, (c) interactions among the chemical compounds that enhance or reduce a specific flavor sensation, and finally, (d) the complexity of the different food matrices and its influence in the flavor perception. Another difficulty that flavor scientists must face is how to properly model and visualize the complex relationships existing between the chemical composition of foods and the flavor perception. These problems have repercussions on the reconstitution of the flavor signature of food based on the natural concentrations of its key aroma and taste compounds. Therefore, the main aim of this review is to deal with all these issues to propose potential solutions for a robust transformation in a science-based quality approach.

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“…An artificial taste system named electronic tongue (e-tongue) has become a potential approach for liquid-phase evaluations [1,2]. A sensor array and the proper pattern recognition algorithm are the two main parts of an e-tongue.…”

Section: Introductionmentioning

confidence: 99%

An Active Feature Selection Strategy for DWT in Artificial Taste

Liu

Chen

et al. 2018

Journal of Sensors

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A discrete wavelet transform (DWT) extracts meaningful information in a time-frequency domain and is a favorable feature extraction approach from pulse-like responses in large pulse voltammetry (LAPV) electronic tongues (e-tongue). A regular DWT generates lots of coefficients to describe signal details and approximations at different scales. Thus, coefficient selection is necessary to reduce the feature size. However, the common DWT-based feature selection follows a passive mode: manipulation through human experience or exhaustive trials. It is subjective, time consuming, and barely works in nonlaboratory conditions. In this paper, we present an active feature selection strategy consisting of a dispersion ratio computation and optimal searching search. To evaluate the performance of the proposed method, we prepared several beverage samples and performed experiments with a LAPV e-tongue. Meanwhile, the features of raw response, peak-inflection point, referenced DWT method, and our proposed method were presented to indicate the effects of the refined features of the proposed method. Furthermore, we utilized several classifiers such as the k-nearest neighbor (k-NN), support vector machine (SVM), and random forest (RF) to evaluate the improvement of recognition by the refined features. Compared with other regular feature extraction methods, the proposed method can automatically explore high-quality features with an acceptable feature size. Moreover, the highest average accuracy was achieved by the proposed method for each classifier. It is an alternative feature extraction approach for a LAPV e-tongue without any manipulation in real applications.

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Recent achievements in electronic tongue and bioelectronic tongue as taste sensors

Cited by 153 publications

References 113 publications

Bioelectronic Tongues Employing Electrochemical Biosensors

Bioelectronic Tongues Employing Electrochemical Biosensors

Challenges in relating concentrations of aromas and tastes with flavor features of foods

An Active Feature Selection Strategy for DWT in Artificial Taste

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