Abstract

This paper presents a thorough study of the methods available for evaluating tea quality by using near infrared (NIR) spectroscopy technology as an objective universal sensory assessment procedure. The first section of this systematic study reports the assessment of tea quality by correlating chemical components with sensory evaluation using principal component analysis scores and loadings. The first three PCs account for more than 94% of the variance in input data for four original chemicals (lignin, polyphenols, caffeine and amino acids). The correlation between PC1 scores alone and tea quality classes, given by sensory tastes, is higher with R² > 0.98 in green and black teas. The second section focuses on the preparation of multi-equations in order to calibrate NIR determination of chemical components according to sensory assessment. The outcome of the established multiple linear regression equations was an ability to predict tea quality directly by NIR spectroscopy with a correlation r² = 0.86 and with less than 9.7% misclassified samples in green and black tea. In the final section, some poor correlations between tea quality and market prices in the world are reported and we suggest that NIR technology can provide an internationally accepted, objective and rapid method to assess tea quality.

© 2005 NIR Publications

Tea classification and quality assessment using laser-induced fluorescence and chemometric evaluation

Liang Mei, Patrik Lundin, Mikkel Brydegaard, Shuying Gong, Desong Tang, Gabriel Somesfalean, Sailing He, and Sune Svanberg
Appl. Opt. 51(7) 803-811 (2012)

Automated tea quality classification by hyperspectral imaging

Jiewen Zhao, Quansheng Chen, Jianrong Cai, and Qin Ouyang
Appl. Opt. 48(19) 3557-3564 (2009)

Rapid determination of the main components of corn based on near-infrared spectroscopy and a BiPLS-PCA-ELM model

Lili Xu, Jinming Liu, Chunqi Wang, Zhijiang Li, and Dongjie Zhang
Appl. Opt. 62(11) 2756-2765 (2023)

Comparison of a physical model and principal component analysis for the diagnosis of epithelial neoplasias in vivo using diffuse reflectance spectroscopy

Melissa C. Skala, Gregory M. Palmer, Kristin M. Vrotsos, Annette Gendron-Fitzpatrick, and Nirmala Ramanujam
Opt. Express 15(12) 7863-7875 (2007)

Principal frequency component analysis based on modulate chopper technique used in diffuse reflectance spectroscopy measurement

Shaoxiu Song, Gang Li, Xingwei Hou, Shengzhao Zhang, Yue Yu, and Ling Lin
Appl. Opt. 57(5) 1043-1049 (2018)