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Vol. 145, No. 10, September 2012, pp. 77-85

 

Bullet

 

Non Destructive Classification of Himalayan Orthodox Black Teas
 
1 S. KUMAR, 1 P. C. PANCHARIYA, 1 Bhanu Prasad P. and 2 A. L. SHARMA

1 Digital Systems Group, CSIR-Central Electronics Engineering Research Institute, Pilani-333031, India

Tel.: +91-1596-252267, fax:+91-1596-242294

2 School of Instrumentation, Devi Ahilya University, Takshila Campus, Khandwa Road, Indore-452001, India

E-mail: pcp@ceeri.ernet.in

 

 

Received: 9 October 2012   /Accepted: 29 October 2012   /Published: 31 October 2012

Digital Sensors and Sensor Sysstems

 

Abstract: This paper reports the non destructive qualitative discrimination of Kangra orthodox tea (Himalayan teas) samples based on their aroma profiles using a new type of electronic nose called Z-nose which is based on ultra-fast gas chromatography (GC) embedded with surface acoustic wave (SAW) sensor. Seven different types of orthodox black tea samples from same origin were analyzed by recording the frequency spectra of SAW sensor. The frequency spectral features of each category are reasonably differentiated and the spectral differences provided enough qualitative information for identification of tea samples. Discrimination of orthodox black teas based on their frequency spectral data as well as on biochemical data were performed by principal component analysis (PCA), a common chemometric method used for data reduction and visualization. The results demonstrate the ability of ultra fast GC techniques to differentiate between orthodox black teas of same origin manufactured at different seasons. Linear Discriminate Analysis (LDA) was used to construct the identification model based on Principal Components derived using PCA. The number of principal component factors (PCs) was optimized in the constructing models. The experimental results showed good performance of the PCA - LDA model. The optimal model was achieved when four PCs with the identification rates of 97.5 % was achieved for the prediction set. The overall results demonstrated that zNose frequency spectral data with suitable pattern recognition methods can be successfully applied as a rapid method to identify orthodox black tea varieties of same origin.

 

Keywords: Himalayan orthodox black tea, Principal component analysis, Linear discriminate analysis

 

 

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