Development of a Traceability Model for Geographical Origin of Kenya’s Black Teas Based on Principal Component Analysis of FTIR and UV-Vis Spectral Data

James Waweru, Warren Andrew Andayi, Jane Mburu, Sharon Kiprotich and Kimani Shadrack
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James Waweru: Department of Physical and Biological Science, Murang’a University of Technology
Warren Andrew Andayi: Department of Physical and Biological Science, Murang’a University of Technology
Jane Mburu: Department of Physical and Biological Science, Murang’a University of Technology
Sharon Kiprotich: Department of Physical and Biological Science, Murang’a University of Technology
Kimani Shadrack: Department of Biological and Physical Sciences, Karatina University

International Journal of Research and Innovation in Applied Science, 2025, vol. 10, issue 5, 643-654

Abstract: Authentic tracing of the origins of black tea is important in the tea market as this helps to extrapolate the quality and thus prices. Tasting on its own can be a misleading test for tea quality and origin tracing since the method can be compromised by subjectivity of the taster and adulteration. Therefore, there is a need to develop an analytical chemical method for tracing tea origin that is void of subjectivity. This study presents a traceability model based on chemical fingerprinting techniques, specifically FTIR and UV-Vis spectroscopy combined with principal component analysis PCA and heat map analyses that can be applied in distinguishing the geographical origins of Kenyan black tea. In this study, processed black tea leave samples were collected from seven Kenya Tea development Authority KTDA, tea factories in tea growing geographical regions in Kenya. The dry black tea samples were characterized by Fourier transform infrared spectroscopy (FT-IR) at a wavelength range of 400-4000cm-1 whereas the tea aqueous extracts were analysed within 190-600nm range using Ultra violet visible spectroscopy (UV-vis). The resulting spectral data was subjected to PCA and the heat maps analyses and the clustering used in model development. The output showed clustering patterns among tea samples based on similarities in their chemical constituents. The spectral data revealed the presence of phenolic O-H and other O-H stretching vibration(3100-3400cm-1), C-H peak associated with alkane (2850-2950cm-1, with the asymmetric and symmetric stretching vibration at 2919cm-1 and 2851cm-1). The peaks in the range 1590-1620cm-1 were identified as vibration frequencies of C=O of catechins and flavonoids. The stretching vibration of C-O associated with carboxylic acids, esters and alcohol was observed at 1032cm-1. The PCA score plot for the FT-IR spectrum showed 82.45% with PC1 (Principal Component 1) contributing 56.15% and PC2 (Principal Component 2) contributing 26.30%. The tea samples from Kericho, Nyeri, Meru and Vihiga had positive score in the PC showing greater variation in characteristics. However, teas from Kericho, Meru, Nyeri and Vihiga exhibited similar characteristics. which were clearly distinct from samples from Bomet, Murang’a, and Kiambu teas. The intra group variance of samples from Murang’a was low indicating uniformity in the quality. This was also confirmed using UV-vis spectral data that showed variability index of 0.09 in PC output indicating relatively low variability compared to neighboring counties. From UV Vis data the samples from Kericho were predominantly situated at the centre of PC2 axis showing less distinct differences in the chemical properties. Overall the findings revealed that black tea samples from the same geographical origin clustered together thus enhancing distinction. The Heat maps from both UV Vis and FT IR data revealed that teas from Vihiga, Nyeri and Bomet had the lowest levels of phytochemicals and macro elements while those from Meru MERKA, had the highest levels followed by samples from Kericho, KERTOP and one from Nyeri NYRGA. From the findings, Meru tea MERKA is a potential standard since has the highest levels of the desired phytochemicals and macronutrients key to quality and origin tracing

Date: 2025
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