2004Unpublished venueRequires access

Aroma characterization of orthodox black tea with electronic nose

Nabarun Bhattacharyya, Bipan Tudu, Rajib Bandyopadhyay, Muhibul Haque Bhuyan, Rajani K. Mudi

Open publisher page 15 citations

Abstract

Black tea quality is a very complex phenomenon. There are almost two hundred varieties of bio-chemical compounds, both volatile and nonvolatile present in tea and each of these compounds contribute to tea quality (B. Banerjee, 1996), The major quality attributes of tea are flavour, aroma, colour and strength. Acceptance by consumers and price realized depend on these attributes (S.Y. Dheodhar et al.,). Out of these, aroma is the most important of the attributes and in common parlance, aroma means smell of the tea. Characterization of aroma of tea has been a challenge for tea scientists for long. Efforts have been made towards this through chemical analysis and instrumental studies through gas chromatography (GC) and high profile liquid chromatography (HPLC) techniques. Research and studies have been reported with success for quality characterization of food and beverages using electronic nose (T.C. Pearce et al., 2003). This paper reports a study and results on applicability of electronic nose for aroma characterization of orthodox black tea. Six varieties of orthodox tea samples were tested using Alpha MOS 2000 Electronic Nose and data obtained from the experimental setup have been successfully classified using principal component analysis (PCA) and back-propagation multilayer perceptron model.

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What this paper is about

Black tea quality is a very complex phenomenon. There are almost two hundred varieties of bio-chemical compounds, both volatile and nonvolatile present in tea and each of these compounds contribute to tea quality (B. Banerjee, 1996), The major quality attributes of tea are flavour, aroma, colour and strength. Acceptance by consumers and price realized depend on these attributes (S.Y. Dheodhar et al.,). Out of these, aroma is the most important of the attributes and in common parlance, aroma means smell of the tea. Characterization of aroma of tea has been a challenge for tea scientists for long. Efforts have been made towards this through chemical analysis and instrumental studies through gas chromatography (GC) and high profile liquid chromatography (HPLC) techniques. Research and studies have been reported with success for quality characterization of food and beverages using electronic nose (T.C. Pearce et al., 2003). This paper reports a study and results on applicability of electronic nose for aroma characterization of orthodox black tea. Six varieties of orthodox tea samples were tested using Alpha MOS 2000 Electronic Nose and data obtained from the experimental setup have been successfully classified using principal component analysis (PCA) and back-propagation multilayer perceptron model.

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Available abstract

Black tea quality is a very complex phenomenon. There are almost two hundred varieties of bio-chemical compounds, both volatile and nonvolatile present in tea and each of these compounds contribute to tea quality (B. Banerjee, 1996), The major quality attributes of tea are flavour, aroma, colour and strength. Acceptance by consumers and price realized depend on these attributes (S.Y. Dheodhar et al.,). Out of these, aroma is the most important of the attributes and in common parlance, aroma means smell of the tea. Characterization of aroma of tea has been a challenge for tea scientists for long. Efforts have been made towards this through chemical analysis and instrumental studies through gas chromatography (GC) and high profile liquid chromatography (HPLC) techniques. Research and studies have been reported with success for quality characterization of food and beverages using electronic nose (T.C. Pearce et al., 2003). This paper reports a study and results on applicability of electronic nose for aroma characterization of orthodox black tea. Six varieties of orthodox tea samples were tested using Alpha MOS 2000 Electronic Nose and data obtained from the experimental setup have been successfully classified using principal component analysis (PCA) and back-propagation multilayer perceptron model.

Key concepts: Aroma, Electronic nose, Black tea, Flavour, Principal component analysis, Chemistry, Characterization (materials science), Food science

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