Potential of hyperspectral remote sensing on estimating foliar chemistry and predicting the quality of tea (Camellia sinensis)

Meng Bian*, Andrew K. Skidmore, Dejiang Ni, Jan De Leeuw, Martin Schlerf, Yanfang Liu, Teng Fei

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

In this study, we monitored the quality of fresh tea leaves as raw materials of tea products by hyperspectral technology, as a way to explore the potential of hyperspectral remote sensing to detect the taste-related chemical components with low concentration in living plants. At leaf scale, empirical models have been established to find the relationships between quality-related chemicals in fresh tea leaves and foliar spectral data. Tea polyphenols (TP) and amino acid (AA) and water-soluble protein (SP) are three target chemicals in this paper. Near infrared spectroscopy (NIRS) was also been applied to estimate these chemicals for dried and ground leaves in laboratory. They are compared in terms of retrieval precision. Two main methodologies have been employed for modelling: (a) two bands normalized ratio index (NRI), (b) partial least squares (PLS) regression. The PLS method was performed using the original and transformed spectra: mean centred spectra, standard first derivative and standard normal variate (SNV) transformed spectra. The results demonstrated that the biochemical parameters related to the quality of tea can be estimated with satisfactory accuracy both at dried powder and fresh leaf scales.

Original languageEnglish
Title of host publicationInternational Conference on Earth Observation Data Processing and Analysis (ICEODPA)
Subtitle of host publicationproceedings
EditorsDeren Li, Jianya Gong, Huayi Wu
Place of PublicationBellingham, Washington
PublisherSPIE
Number of pages11
ISBN (Print)9780819475459
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventInternational Conference on Earth Observation Data Processing and Analysis - Wuhan, China
Duration: 28 Dec 200830 Dec 2008

Publication series

NameProceedings of SPIE
PublisherSPIE
Volume7285
ISSN (Print)0277-786X

Conference

ConferenceInternational Conference on Earth Observation Data Processing and Analysis
Abbreviated titleICEODPA
CountryChina
CityWuhan
Period28/12/0830/12/08

Keywords

  • biochemical parameters
  • Camellia sinensis
  • hyperspectral
  • quality
  • remote sensing

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