Chemometric Data Analysis for Black Tea Fermentation using Principal Component Analysis.

This study will provide a chemometric data analysis for fermented black tea that will help tea manufacturer to ensure the consistency and quality of black tea they produce. It will aim to create a device that will detect the aroma of black tea and generate the standard for the quality of black tea. The study utilized matlab and principal component analysis for the chemometric data gathered in black tea. Based on the analysis done, it can be concluded that the electronic nose was able to classify most of the black tea samples correctly. The overall recognition rate of the system is 75%. The system can be improved by increasing the number of training data. [ABSTRACT FROM AUTHOR]