Changes in the first derivatives of leaf reflectance spectra of various plants induced by variations of chlorophyll content

Kochubey, Svetlana M.; Kazantsev, Taras

doi:10.1016/j.jplph.2006.11.007

Cited by 66 publications

(17 citation statements)

References 21 publications

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“…Additionally, there was a red shift in the derivative peak from 706 nm (control plants) to 715 nm (plant treated with arsenic solutions) while in the region of shorter wavelengths no shift was observed (results not shown). It is well documented that changes in derivative reflectance spectra are associated to changes in chlorophyll content (Kochubey and Kazantsev, 2007), however in this work a dependency with chlorophyll concentration has not been found. Actually, variations on chlorophyll content depend not only on the applied As concentration, but also on its speciation, the time of contact, the plant species studied, and others.…”

Section: Arsenic Effects On Photophysical Propertiescontrasting

confidence: 58%

Biosorption of arsenic from groundwater using Vallisneria gigantea plants. Kinetics, equilibrium and photophysical considerations

2015

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Section: Arsenic Effects On Photophysical Propertiescontrasting

confidence: 58%

Biosorption of arsenic from groundwater using Vallisneria gigantea plants. Kinetics, equilibrium and photophysical considerations

2015

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“…Second derivative of reflectance of some crops and land covers. chlorophyll content in maize, winter wheat, sugar beet and wild vine crops (Kochubey and Kazantsev, 2007), which have also been used to determine the effect of glyphosate on plants (Yao et al, 2012).…”

Section: Resultsmentioning

confidence: 99%

Relationship between crop nutritional status, spectral measurements and Sentinel 2 images

Martínez

2017

Agron. colomb.

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RESUMENIn order to monitor the nutritional status of some crops based on plant spectroscopy and Sentinel 2 satellite images in Colombia, spectral reflectance data were taken between 350 and 2,500 nm with a FieldSpec 4 spectrometer in rubber, rice, sugar cane, maize, soybean, cashew, oil palm crops, pastures and natural savanna. Furthermore contents of mineral nutrients in leaves were determined. Several vegetation indexes and red edge positions were calculated using various methods from spectral data and Sentinel 2 satellite images and were correlated with leaf nutrient content. The results showed correlations between spectral indices, mainly those involving a spectral response in the red-edge range with the N, P, K and Cu although the best correlation coefficients were for N. First reflectance derivatives, transformations by the State Normal Variate and second reflectance derivatives showed great potential to monitor N content in crops. The green model index and the red-edge model computed from Sentinel 2 images had the best performance to monitor N content, although in the study area, presence of clouds affected the use of these images. The Sentinel 2 images allowed calculating some vegetation indexes obtained with other images, such as Landsat or SPOT, but additionally other indexes and calculations based on the bands of the red-edge, which is a great contribution to obtain more information of crops on their spatial and temporal variability Con el fin de monitorear el estado nutricional de algunos cultivos con base en espectroscopía de plantas e imágenes satelitales 2 en Colombia, se tomaron datos de reflectancia entre 350 y 2.500 nm con un espectrómetro FieldSpec 4 en cultivos de caucho, arroz, caña de azúcar, maíz, soya, marañón y palma de aceite, en pasturas y sabanas naturales y se determinó el contenido de nutrientes minerales en hojas. Se calcularon varios índices de vegetación y posiciones de borde rojo usando varios métodos, a partir de datos espectrales e imágenes de satélite Sentinel 2 y se correlacionaron con el contenido de nutrientes en las hojas. Los resultados mostraron correlaciones entre índices espectrales, principalmente aquellos que involucraron la respuesta espectral en el rango de borde rojo, con N, P, K y Cu aunque los mejores coeficientes de correlación fueron para N. La primera derivada de la reflectancia, su transformación por la state normal variate y la segundas derivadas mostraron un gran potencial para monitorear el contenido de N en los cultivos. El índice del modelo verde y el modelo de borde rojo calculados a partir de imágenes Sentinel 2 tuvieron el mejor desempeño para monitorear el contenido de N, aunque en las condiciones del área de estudio la presencia de nubes afectó el uso de estas imágenes. Las imágenes Sentinel 2 permitieron calcular algunos índices de vegetación que se obtienen con otras imágenes, como Landsat o SPOT, pero adicionalmente otros índices y cálculos basados en las bandas del borde rojo, lo cual es una gran contribución para obtener más informac...

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“…So far, most of leaf chlorophyll reflectance indices have been developed and tested for herbaceous crops, grasses, or common deciduous tree and coniferous tree species (Horler et al, 1983;Carter, 1994;Datt, 1998Datt, , 1999Sims and Gamon, 2002;Kochubey and Kazantsev, 2007). A limited study was carried out on fruity vegetables such as bean and capsicum (Buschman and Nagel, 1993;Filella and Penuelas, 1994).…”

Section: Introductionmentioning

confidence: 99%

Deriving leaf chlorophyll content of green-leafy vegetables from hyperspectral reflectance

Xue

Yang

2009

ISPRS Journal of Photogrammetry and Remote Sensing

128

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Changes in the first derivatives of leaf reflectance spectra of various plants induced by variations of chlorophyll content

Cited by 66 publications

References 21 publications

Biosorption of arsenic from groundwater using Vallisneria gigantea plants. Kinetics, equilibrium and photophysical considerations

Biosorption of arsenic from groundwater using Vallisneria gigantea plants. Kinetics, equilibrium and photophysical considerations

Relationship between crop nutritional status, spectral measurements and Sentinel 2 images

Deriving leaf chlorophyll content of green-leafy vegetables from hyperspectral reflectance

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