Literature DB >> 30179805

Assessing hyperspectral indices for tracing chlorophyll fluorescence parameters in deciduous forests.

Rei Sonobe1, Quan Wang2.   

Abstract

Chlorophyll fluorescence can be used to quantify the efficiency of photochemistry and heat dissipation. While several instruments such as Pulse-Amplitude-Modulation (PAM) fluorometers are available for taking direct measurements of parameters related to chlorophyll fluorescence, large-scale instantaneous ecosystem monitoring remains difficult. Several hyperspectral indices have been claimed to be closely related to some chlorophyll fluorescence parameters (e.g. photosystem II quantum yield (Yield), qP, NPQ), which may pave a way for efficient large-scale monitoring of fluorescence parameters. In this study, we have examined 30 published hyperspectral indices for their possible use in tracing chlorophyll fluorescence parameters. The comparison is based on a series of unique datasets with synchronous measurements of reflected hyperspectra and seven fluorescence parameters (i.e., Fm, F0, Fs, Fm', Yield, qP and NPQ) from leaves of Fagus crenata and other six broadleaf species sampled in Mt. Naeba, Japan. Among them, the first dataset is composed of seasonal canopy field measurements of Fagus crenata leaves, while the second is composed of field measurements of other deciduous species including Lindera umbellate, Clethra barbinervis, Viburnum furcatum, Eleutherococcus sciadophylloides, Quercus crispula and Acer japonicum. Furthermore, an additional dataset composed of data resulting from various controlled experiments using inhibitors has been applied for improving physiological interpretations of indices. Results revealed that PRI had higher coefficients of determination and lower root mean square errors than other indices evaluated with a set of chlorophyll fluorescence parameters. However, this pattern was seen only for beech leaves and performed poorly across other species. As a result, no specific indices that are currently available are recommended for tracing fluorescence parameters.
Copyright © 2018. Published by Elsevier Ltd.

Entities:  

Keywords:  Chlorophyll fluorescence; Deciduous species; PRI; Spectral indices

Mesh:

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Year:  2018        PMID: 30179805     DOI: 10.1016/j.jenvman.2018.06.085

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  1 in total

1.  Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms.

Authors:  Rei Sonobe; Yuhei Hirono; Ayako Oi
Journal:  Plants (Basel)       Date:  2020-03-17
  1 in total

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