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| Titel |
A novel reflectance-based model for evaluating chlorophyll concentrations of fresh and water-stressed leaves |
| VerfasserIn |
C. Lin, S. C. Popescu, S. C. Huang, P. T. Chang, H. L. Wen |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 12, no. 1 ; Nr. 12, no. 1 (2015-01-06), S.49-66 |
| Datensatznummer |
250117758
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| Publikation (Nr.) |
 copernicus.org/bg-12-49-2015.pdf |
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| Zusammenfassung |
Water deficits can cause chlorophyll degradation which decreases the total
concentration of chlorophyll a and b (Chls). Few studies have
investigated the effectiveness of spectral indices under water-stressed
conditions. Chlorophyll meters have been extensively used for a wide variety
of leaf chlorophyll and nitrogen estimations. Since a chlorophyll meter works
by sensing leaves absorptance and transmittance, the reading of chlorophyll
concentration will be affected by changes in transmittance as if there were a
water deficit in the leaves. The overall objective of this paper was to
develop a novel and reliable reflectance-based model for estimating Chls of
fresh and water-stressed leaves using the reflectance at the absorption bands
of chlorophyll a and b and the red edge spectrum.
Three independent experiments were designed to collect data from three leaf
sample sets for the construction and validation of Chls estimation models.
First, a reflectance experiment was conducted to collect foliar Chls and
reflectance of leaves with varying water stress using the ASD FieldSpec
spectroradiometer. Second, a chlorophyll meter (SPAD-502) experiment was
carried out to collect foliar Chls and meter readings. These two data sets
were separately used for developing reflectance-based or absorptance-based
Chls estimation models using linear and nonlinear regression analysis.
Suitable models were suggested mainly based on the coefficient of
determination (R2). Finally, an experiment was conducted to collect the
third data set for the validation of Chls models using the root mean squared
error (RMSE) and the mean absolute error (MAE). In all of the experiments,
the observations (real values) of the foliar Chls were extracted from
acetone solution and determined by using a Hitachi U-2000 spectrophotometer.
The spectral indices in the form of reflectance ratio/difference/slope
derived from the Chl b absorption bands (ρ645 and ρ455) provided Chls estimates with RMSE around 0.40–0.55 mg g−1 for both
fresh and water-stressed samples. We improved Chls prediction accuracy by
incorporating the reflectance at red edge position (ρREP) in
regression models. An effective chlorophyll indicator with the form of
(ρ645–ρ455)/ρREP proved to be the most
accurate and stable predictor for foliar Chls concentration. This model was
derived with an R2 of 0.90 (P < 0.01) from the training samples
and evaluated with RMSE 0.35 and 0.38 mg g−1 for the validation samples of
fresh and water-stressed leaves, respectively. The average prediction error
was within 14% of the mean absolute error. |
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