scholarly journals Exploring the links between secondary metabolites and leaf spectral reflectance in a diverse genus of Amazonian trees

Ecosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Paul V. A. Fine ◽  
Diego Salazar ◽  
Roberta E. Martin ◽  
Margaret R. Metz ◽  
Tracy M. Misiewicz ◽  
...  
2020 ◽  
Vol 10 (7) ◽  
pp. 2259 ◽  
Author(s):  
Haixia Qi ◽  
Bingyu Zhu ◽  
Lingxi Kong ◽  
Weiguang Yang ◽  
Jun Zou ◽  
...  

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.


1992 ◽  
Vol 43 (4) ◽  
pp. 577-584 ◽  
Author(s):  
GREGORY A CARTER ◽  
ROBERT J. MITCHELL ◽  
ARTHUR H. CHAPPELKA ◽  
CHARLES H BREWER

2016 ◽  
Vol 6 (2) ◽  
pp. 221-230 ◽  
Author(s):  
Miloš Barták ◽  
Josef Hájek ◽  
Ana Carolina Amarillo ◽  
Jana Hazdrová ◽  
Hebe Carreras

Recently, spectral characteristics of lichens are in focus because of increasing number of spectral data applications in remote sensing of treeless polar and alpine regions. Therefore, species-specific spectral reflectance indices are measured in lichen species dominating polar ecosystems. Hydration status of the lichen thalli, as well as the presence of intrathalline secondary metabolites - which are UV-B absorbing compounds - both affects the spectral reflectance curves as well as numeric values of spectral reflectance indices. In the present paper, the reflectance spectra in 380-800 nm was measured in selected lichens to assess the effects of full hydration, and to evaluate the influence of secondary metabolites, they were wash out from lichen thalli with acetone (i.e. acetone rinsing) and then the spectra were also measured. For these experiments, Antarctic (Xanthoria elegans, Leptogium puberulum, Physconia muscigena and Rhizoplaca melanophthalma) and Argentinean lichens from mountain regions (Parmotrema conferendum and Ramalina celastri) were used. Changes in several spectral reflectance indices were evaluated and discussed in relation with hydration status and the absence of secondary metabolites. For the great majority of studied lichens, MCARI (Modified Chlorophyll Absorption in Reflectance Index) was the most effective index to reflect the changes between dry and wet state of thallus.


2013 ◽  
Vol 51 ◽  
pp. 444-452 ◽  
Author(s):  
Fangfang Jia ◽  
Guoshun Liu ◽  
Songshuang Ding ◽  
Yongfeng Yang ◽  
Yunpeng Fu ◽  
...  

2021 ◽  
Vol 13 (5) ◽  
pp. 980
Author(s):  
Shahar Weksler ◽  
Offer Rozenstein ◽  
Nadav Haish ◽  
Menachem Moshelion ◽  
Rony Wallach ◽  
...  

Symptoms of root stress are hard to detect using non-invasive tools. This study reveals proof of concept for vegetation indices’ ability, usually used to sense canopy status, to detect root stress, and performance status. Pepper plants were grown under controlled greenhouse conditions under different potassium and salinity treatments. The plants’ spectral reflectance was measured on the last day of the experiment when more than half of the plants were already naturally infected by root disease. Vegetation indices were calculated for testing the capability to distinguish between healthy and root-damaged plants using spectral measurements. While no visible symptoms were observed in the leaves, the vegetation indices and red-edge position showed clear differences between the healthy and the root-infected plants. These results were achieved after a growth period of 32 days, indicating the ability to monitor root damage at an early growing stage using leaf spectral reflectance.


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