Sweetness Sensor with Lipid/Polymer Membranes: Response to Various Sugars

India is the second-largest tea producer and consumer in the world after China. In 2017, the Indian tea market size accounted for 130 billion Indian rupees. An estimated global tea market size was at USD 13.31 billion in 2019, and the expected compound annual growth rate is 5.5% up to the year 2025. India can grab worth tea market size globally by making market strategies with AI and ML-based demonstrations for the unique identity of tea flavor. Conventional instruments available are not handy, time-consuming and require a skilled person to operate. The tea attributes should be digitally recognizable before purchase from the consumer's perspective, significantly enlarging the tea market circle. In the paper, the comprehensive review about an artificial perception of tea has been briefly discussed. Three major attributes of the tea sample, its taste, smell, and color, are under consideration. With the help of various sensors, the attributes of liquefied tea samples had got converted into their digital signature. By analyzing the correlation of them with the pattern recognition, their classification had done. The electronic feature fusion of tea liquor attributes may cause handling issues with the formation of redundant data. So this paper explains the method and guidelines of an application of specific filters which remove the redundant data. The constructive sample data can establish the decision matrix for correlation. With the established decision matrix, précised test prediction can be achieved for the tea sample based on correlation and regression. The limitations and glitches of the conventional instruments for an artificial perception have been discussed in-depth for possible improvement. The paper ends with a bibliometric analysis of the topic "artificial taste perception of tea," which had derived from the standard repository of Web of Science. The bibliometric analysis is very useful to showcase the current research trends in the artificial taste perception of tea.

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Suitability of E-tongue Sensors to Assess Taste-Masking of Pediatric Liquids by Different Beverages Considering Their Physico-chemical Properties

Immohr

Hedfeld

Lang

et al. 2016

AAPS PharmSciTech

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Manipulation of liquid oral drugs by mixing them into foodstuff is a common procedure for taste-masking of OTC pharmaceuticals when administered to children. However, the taste-masking capability of such application media is not systematically evaluated, and recommendations for suitable media are hardly published. In this study, a sensor array of commercially available and self-developed electronic tongue sensors was employed to assess the taste-masking efficiency of eight different beverages (tap water, apple juice, carrot juice, fennel tea, fruit tea, milk, cocoa, and Alete meal to drink) on the OTC pharmaceuticals Ambroxol-ratiopharm®, Cetirizin AL, and Laxoberal® by multivariate data analysis. The Euclidean distances between each pure application medium and its corresponding drug mixture were used as an indicator for the taste-masking efficiency and correlated to the physico-chemical properties of the beverages. Thus, the pH value, the viscosity, as well as the fat and sugar content of the beverages were included, whereas only the viscosity appeared to be insignificant in all cases. The sugar content as well as the fat content and pH value emerged to be a significant variable in taste-masking efficiency for some of the tested drug products. It was shown that the applied electronic tongue sensors were capable to demonstrate the impact of the physico-chemical properties of the application media on their taste-masking capacity regardless of their non-selectivity towards these characteristics.

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Sweetness Sensor with Lipid/Polymer Membranes: Response to Various Sugars

Cited by 6 publications

References 9 publications

Gliadins in Foods and the Electronic Tongue

Gliadins in Foods and the Electronic Tongue

Artificial Perception of the Beverages: An In-Depth Review of the Tea Sample

Suitability of E-tongue Sensors to Assess Taste-Masking of Pediatric Liquids by Different Beverages Considering Their Physico-chemical Properties

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