Effect of Chlorophyll Content & Solar Irradiance on Spectral Reflectance of Vegetation Canopies Acquired By Spectro-Radiometer

The purpose of this study is to determine a method for quickly and accurately estimating the chlorophyll content of peanut plants at different plant densities. This was explored using leaf spectral reflectance to monitor peanut chlorophyll content to detect sensitive spectral bands and the optimum spectral indicators to establish a quantitative model. Peanut plants under different plant density conditions were monitored during three consecutive growth periods; single-photon avalanche diode (SPAD) and hyperspectral data derived from the leaves under the different plant density conditions were recorded. By combining arbitrary bands, indices were constructed across the full spectral range (350–2500 nm) based on blade spectra: the normalized difference spectral index (NDSI), ratio spectral index (RSI), difference spectral index (DSI) and soil-adjusted spectral index (SASI). This enabled the best vegetation index reflecting peanut-leaf SPAD values to be screened out by quantifying correlations with chlorophyll content, and the peanut leaf SPAD estimation models established by regression analysis to be compared and analyzed. The results showed that the chlorophyll content of peanut leaves decreased when plant density was either too high or too low, and that it reached its maximum at the appropriate plant density. In addition, differences in the spectral reflectance of peanut leaves under different chlorophyll content levels were highly obvious. Without considering the influence of cell structure as chlorophyll content increased, leaf spectral reflectance in the visible (350–700 nm): near-infrared (700–1300 nm) ranges also increased. The spectral bands sensitive to chlorophyll content were mainly observed in the visible and near-infrared ranges. The study results showed that the best spectral indicators for determining peanut chlorophyll content were NDSI (R520, R528), RSI (R748, R561), DSI (R758, R602) and SASI (R753, R624). Testing of these regression models showed that coefficient of determination values based on the NDSI, RSI, DSI and SASI estimation models were all greater than 0.65, while root mean square error values were all lower than 2.04. Therefore, the regression model established according to the above spectral indicators was a valid predictor of the chlorophyll content of peanut leaves.

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Using spectral reflectance to estimate leaf chlorophyll content of tea with shading treatments

Biosystems Engineering ◽

10.1016/j.biosystemseng.2018.09.018 ◽

2018 ◽

Vol 175 ◽

pp. 168-182 ◽

Cited By ~ 21

Author(s):

Rei Sonobe ◽

Tomohito Sano ◽

Hideki Horie

Keyword(s):

Chlorophyll Content ◽

Spectral Reflectance ◽

Leaf Chlorophyll Content ◽

Leaf Chlorophyll

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Spectral Reflectance Characteristics and Chlorophyll Content Estimation Model of Quercus aquifolioides Leaves at Different Altitudes in Sejila Mountain

Applied Sciences ◽

10.3390/app10103636 ◽

2020 ◽

Vol 10 (10) ◽

pp. 3636 ◽

Cited By ~ 1

Author(s):

Jiyou Zhu ◽

Weijun He ◽

Jiangming Yao ◽

Qiang Yu ◽

Chengyang Xu ◽

...

Keyword(s):

Chlorophyll Content ◽

Spectral Reflectance ◽

Spectral Response ◽

Ecological Status ◽

Short Wave ◽

Relative Content ◽

Tibet Plateau ◽

Wave Direction ◽

Estimation Model ◽

Different Altitudes

Quercus aquifolioides is one of the most representative broad-leaved plants in Qinghai-Tibet Plateau with important ecological status. So far, understanding how to quickly estimate the chlorophyll content of plants in plateau areas is still an urgent problem. Field Spec 3 spectrometer was used to measure hyperspectral reflectance data of Quercus aquifolioides leaves at different altitudes, and CCI (chlorophyll relative content) of corresponding leaves was measured by a chlorophyll meter. The correlation and univariate linear fitting analysis techniques were used to establish their relationship models. The results showed that: (1) Chlorophyll relative content of Quercus aquifolioides, under different altitude gradients, were significantly different. From 2905 m to 3500 m, chlorophyll relative content increased first and then decreased. Altitude 3300 m was the most suitable growth area. (2) In 350~550 nm, the spectral reflectance was 3500 m > 3300 m > 2905 m. In 750~1100 nm, the spectral reflectivity was 2905 m > 3500 m > 3300 m. (3) There were 4 main reflection peaks and 5 main absorption valleys in the leaf surface spectral reflection curve. While, 750~1400 nm was the sensitive range of leaf spectral response of Quercus aquifolioides. (4) The red edge position and red valley position moved to short wave direction with the increase of altitude, while the yellow edge position and green peak position moved to long wave direction first and then to short wave direction. (5) The correlation curve between the original spectrum and the CCI value was the best between the wavelengths 509~650 nm. The correlation between the first derivative spectrum and CCI value was the best and most stable at 450~500 nm. The green peak reflectance was most sensitive to the relative chlorophyll content of Quercus aquifolioides. The estimation model R2 of green peak reflectance was the highest (y = 206.98e−10.85x, R2 = 0.8523), and the prediction accuracy was 95.85%. The research results can provide some technical and theoretical support for the protection of natural Quercus aquifolioides forests in Tibet.

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Spectral Reflectance and Transmittance of a Leaf as a Function of Chlorophyll Content

Transactions of the Society of Instrument and Control Engineers ◽

10.9746/sicetr1965.24.438 ◽

1988 ◽

Vol 24 (5) ◽

pp. 438-444

Author(s):

Norihide YAMADA ◽

Sadao FUJIMURA

Keyword(s):

Chlorophyll Content ◽

Spectral Reflectance

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Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves

Journal of Plant Physiology ◽

10.1078/0176-1617-00887 ◽

2003 ◽

Vol 160 (3) ◽

pp. 271-282 ◽

Cited By ~ 850

Author(s):

Anatoly A. Gitelson ◽

Yuri Gritz † ◽

Mark N. Merzlyak

Keyword(s):

Chlorophyll Content ◽

Spectral Reflectance ◽

Plant Leaves ◽

Higher Plant ◽

Leaf Chlorophyll Content ◽

Leaf Chlorophyll ◽

Non Destructive

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Hyperspectral Estimation Models of Winter Wheat Chlorophyll Content Under Elevated CO2

Frontiers in Plant Science ◽

10.3389/fpls.2021.642917 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yao Cai ◽

Yuxuan Miao ◽

Hao Wu ◽

Dan Wang

Keyword(s):

Winter Wheat ◽

Chlorophyll Content ◽

Spectral Reflectance ◽

Vegetation Index ◽

Estimation Model ◽

Important Indicator ◽

Spectral Bands ◽

Close Relationship ◽

The Relationship ◽

Red Edge Position

Chlorophyll content is an important indicator of winter wheat health status. It is valuable to investigate whether the relationship between spectral reflectance and the chlorophyll content differs under elevated CO2 condition. In this open-top chamber experiment, the CO2 treatments were categorized into ambient (aCO2; about 400 μmol⋅mol–1) or elevated (eCO2; ambient + 200 μmol⋅mol–1) levels. The correlation between the spectral reflectance and the chlorophyll content of the winter wheat were analyzed by constructing the estimation model based on red edge position, sensitive band and spectral index methods, respectively. The results showed that there was a close relationship between chlorophyll content and the canopy spectral curve characteristics of winter wheat. Chlorophyll content was better estimated based on sensitive spectral bands and difference vegetation index (DVI) under both aCO2 and eCO2 conditions, though the accuracy of the models varied under different CO2 conditions. The results suggested that the hyperspectral measurement can be effectively used to estimate the chlorophyll content under both aCO2 and eCO2 conditionsand could provide a useful tool for monitoring plants physiology and growth.

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The Changes of Leaf Reflectance Spectrum and Leaf Functional Traits of Osmanthus fragrans Are Related to the Parasitism of Cuscuta japonica

Applied Sciences ◽

10.3390/app11041937 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1937

Author(s):

Jiyou Zhu ◽

Qing Xu ◽

Jiangming Yao ◽

Xinna Zhang ◽

Chengyang Xu

Keyword(s):

Host Plant ◽

Chlorophyll Content ◽

Functional Traits ◽

Spectral Reflectance ◽

Spectral Parameters ◽

Osmanthus Fragrans ◽

Leaf Functional Traits ◽

Leaf Economics Spectrum ◽

Cuscuta Japonica ◽

Leaf Economics

Studies on the influence of parasitism on plants based on hyperspectral analysis have not been reported so far. To fully understand the variation characteristics and laws of leaf reflectance spectrum and functional traits after the urban plant parasitized by Cuscuta japonica Choisy. Osmanthus fragrans (Thunb.) Lour. was taken as the research object to analyze the spectral reflectance and functional traits characteristics at different parasitical stages. Results showed that the spectral reflectance was higher than those being parasitized in the visible and near-infrared range. The spectral reflectance in 750~1400 nm was the sensitive range of spectral response of host plant to parasitic infection, which is universal at different parasitic stages. We established a chlorophyll inversion model (y = −65913.323x + 9.783, R2 = 0.6888) based on the reflectance of red valley, which can be used for chlorophyll content of the parasitic Osmanthus fragrans. There was a significant correlation between spectral parameters and chlorophyll content index. Through the change of spectral parameters, we can predict the chlorophyll content of Osmanthus fragrans under different parasitic degrees. After being parasitized, the leaf functional traits of host plant were generally characterized by large leaf thickness, small leaf area, small specific leaf area, low relative chlorophyll content, high leaf dry matter content and high leaf tissue density. These findings indicate that the host plant have adopted a certain trade-off strategy to maintain their growth in the invasion environment of parasitic plants. Therefore, we suspect that the leaf economics spectrum may also exist in the parasitic environment, and there was a general trend toward the “slow investment-return” type in the global leaf economics spectrum.

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