Please use this identifier to cite or link to this item: https://scholar.ptuk.edu.ps/handle/123456789/955
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Title: Testing herbal medicines plants mixtures using a taste sensor “an electronic tongue” and multivariate data analysis
Other Titles: فحص عينات مزيج من الأعشاب الطبية باستخدام مجس التذوق ‘اللسان االلكتروني’ والتحليل المتعدد العوامل
Authors: Taha, Haneen
Keywords: electronic tongue;herbal medicines;caffeine;PCA;PLS;DFA;taste panel
Issue Date: 14-Feb-2019
Publisher: Palestine Technical University - Kadoorie
Citation: Taha,H.(2019).Testing herbal medicines plants mixtures using a taste sensor “an electronic tongue” and multivariate data analysis
Abstract: Herbal plants play important role in various health applications. Nowadays, scientists are emphasizing on analytical methods and chemometric applications for identifying many herbs from closely related species and other discrimination factors. Despite the presence of highly precise analytical methods, still there are some disadvantages for them, a multi sensor called an electronic tongue (ET) system is an alternative, promising and compatible technology. This study was carried out to present an emerging research field of sensors technology (i.e. ET). ET and multivariate data analysis (MVDA) were used in quality control of local herbal medicines, to identify various locally produced samples of herbal extracts tea and to test the ability of ET to quantify their taste. Firstly, six tea samples, including four herbal tea, black and green tea, were tested using ET. Data obtained by ET was analyzed using MVDA. Different validation methods were used including a human taste panel (i.e. consumer test) and spectrophotometric measurements of xv caffeine content in the tea brands. Secondly, two herbal tea samples (i.e. Nanus and Morning tea) were mixed in different concentrations and tested using ET. Finally, a local product called Relax (an herbal mixture used as laxative) was studied to detect the stability or benchmarking of the product, as well as its alternative products in the market. The results revealed that ET could successfully discriminate three of the six herbal tea samples and predict several taste parameters and the caffeine content in each tea brand. Moreover, ET could detect a mixture of two tea brands efficiently. As for the Relax granules, results indicated little or no effect of the storage time (shelf-time) on the analyzed production batches. Moreover, the local Relax proved its ability to compete with foreign products. The overall results of the present work provided baseline information for the possible use of ET, with the help of MVDA in data interpretation, for testing quality and taste of herbal medical plants mixtures. Furthermore, it opens a door for new possible applications in Palestine.
URI: https://scholar.ptuk.edu.ps/handle/123456789/955
Appears in Collections:Master Thesis/ Agricultural Biotechnology

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