NDLI: Prototype instruments for determination of aroma and flavor quality of brewed black tea

Content Provider	IEEE Xplore Digital Library
Author	Irsyad Waluyo Blit Adinda Bunga Juwita Suprijanto Nugraha
Copyright Year	2015
Description	Author affiliation: Master Program of Instrumentation and Control, Faculty of Industrial Technology, Institut Teknologi Bandung, Indonesia 40132 (Irsyad Waluyo Blit) \|\| Engineering Physics Research Group, Faculty of Industrial Technology, Institut Teknologi Bandung, Indonesia 40132 (Nugraha) \|\| Instrumentation and Control Research Group, Faculty of Industrial Technology, Institut Teknologi Bandung, Indonesia 40132 (Suprijanto) \|\| Undergraduate Program of Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Indonesia 40132 (Adinda Bunga Juwita)
Abstract	Black tea is one of Indonesia's major leading export products. In terms of trading, quality of black tea, especially flavor and aroma, will determine its selling price. The purpose of this research is to design a prototype of electronic nose, which integrated gas sensors, data acquisition, and computer, to detect the aroma of brewed black tea. This electronic nose consists of four gas sensors (TGS 822, TGS 825, TGS 826, and TGS 2620) MOS type with SnO2 as sensing element. The response of sensor is processed by using power spectral estimation method and the result is being used as an input for Artificial Neural Network (ANN) to classify the quality of brewed black tea. ANN is trained by varying 4 sets of data input for each quality classes: 31, 35, 37, and 39, which are being used as an ANN inputs. The performance of ANN that has been developed is tested by using 9 sets of brewed black tea aroma data which are different from trained data. The results of the test show that the system is able to recognize the aroma with 11,11% errors.
Starting Page	138
Ending Page	142
File Size	580880
Page Count	5
File Format	PDF
e-ISBN	9781467378000
DOI	10.1109/ICICI-BME.2015.7401351
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-02
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Instruments Artificial neural networks Electronic nose Aroma and flavor Temperature measurement Brewed black tea Biomedical measurement Electronic noses Gas sensor Artificial neural network Power spectral estimation Gas detectors Testing
Content Type	Text
Resource Type	Article

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