Literature DB >> 23140747

Integrating satellite images and spectroscopy to measuring green and black tea quality.

R Dutta1, A Stein, R M Bhagat.   

Abstract

This study quantifies the effects of green leaf and black tea parameters that influence tea quality in Northeast India. It was motivated by a decline in tea quality that is of concern to tea growers. The rationale of the study is to identify the different parameters that have a significant influence on liquor brightness and other variables measuring tea quality. Here, we investigate several methods for estimating tea quality based on tea quality data, near infrared spectroscopy and remotely sensed data (NDVI). Attention focused on two high yielding clones (TV1 and S3A3). NDVI was obtained from ASTER images. Statistical analysis shows that liquor brightness is affected by the levels of caffeine content, theaflavins and catechins. Relationships exist between quality parameters and remote sensing in particular for the S3A3 clone. NDVI has a positive relation with caffeine, theogallin, EC, and ECG. NIR is negatively related to caffeine, theogallin, and catechins. We conclude that NDVI and Near Infrared (NIR) spectroscopy have a large potential to be used for monitoring tea quality in the future.
Copyright © 2011 Elsevier Ltd. All rights reserved.

Entities:  

Year:  2011        PMID: 23140747     DOI: 10.1016/j.foodchem.2010.12.160

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  3 in total

1.  Optimization of a tannase-assisted process for obtaining teas rich in theaflavins from Camelia sinensis leaves.

Authors:  Shuang Liang; Fang Wang; Jianxin Chen; Daniel Granato; Lijun Li; Jun-Feng Yin; Yong-Quan Xu
Journal:  Food Chem X       Date:  2022-01-03

2.  Effects of Fermentation Temperature and Time on the Color Attributes and Tea Pigments of Yunnan Congou Black Tea.

Authors:  Jiayi Zhu; Jinjin Wang; Haibo Yuan; Wen Ouyang; Jia Li; Jinjie Hua; Yongwen Jiang
Journal:  Foods       Date:  2022-06-23

3.  Tea cultivar classification and biochemical parameter estimation from hyperspectral imagery obtained by UAV.

Authors:  Yexin Tu; Meng Bian; Yinkang Wan; Teng Fei
Journal:  PeerJ       Date:  2018-05-28       Impact factor: 2.984

  3 in total

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