4.5 Article

Black tea quality determination using a generic resistive gas sensor

Journal

MEASUREMENT SCIENCE AND TECHNOLOGY
Volume 33, Issue 12, Pages -

Publisher

IOP Publishing Ltd
DOI: 10.1088/1361-6501/ac9154

Keywords

black tea; generic gas sensor; optimum fermentation time; tea quality; temperature modulation

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In this study, the dynamic fermentation profile of a resistive gas sensor was analyzed to optimize the process of turning green leaves into black tea and determine the quality of manufactured black tea. The results showed that the tea leaves' optimum fermentation time coincides with the second highest peak in the sensor's dynamic fermentation profile. By introducing a coordinate plane based on the first peak's amplitude and the occurrence of the second peak in the sensor's dynamic fermentation profile, the final black tea quality and the tea taster's score can be predicted with a difference of +/- 0.5 marks.
In this study, we present an analysis on the dynamic fermentation profile of a generic resistive gas sensor to optimize the process of turning green leaves into black tea and determine the quality of manufactured black tea, which are two crucial issues in the tea industry. The leaves were plucked from Lahijan and Rudsar, two important cultivation areas in Iran, in spring, summer and autumn. The results showed that the tea leaves optimum fermentation time (OFT) coincides with the second highest peak in the sensor's dynamic fermentation profile. For example, various experiments showed that the second peak in the sensor's dynamic response for the Lahijan summer tea samples, which had experienced optimal manufacturing stages, occurs in 117 +/- 2 min. Also, tea tasters announced the OFT of 120 min for these samples by carefully examining five traits of the manufactured black tea. It was observed that the occurrence of this second peak is prolonged and even disappears as the quality of black tea decreases. To find the final black tea quality, we introduce a coordinate plane whose axes are determined based on the amplitude of the first peak and the occurrence of the second peak in the sensor's dynamic fermentation profile. In this method, the characteristics of an optimal sample should be considered as a reference point. In the introduced classification space, the Euclidean distance of each point from the origin of the coordinates could also predict the tea taster's score with a difference of +/- 0.5 marks. Finally, we show that the dynamic responses of a temperature-modulated gas sensor have sufficient discriminative features to segregate manufactured black tea samples based on their quality.

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