Estimation of sugarcane leaf nitrogen concentration using in situ spectroscopy

Abdel‐Rahman, Elfatih M.; Ahmed, Fethi; Berg, M. van den

doi:10.1016/j.jag.2009.11.003

Cited by 72 publications

(55 citation statements)

References 32 publications

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“…In addition, we found that the estimation models developed from the FDS exhibited a higher correlation with the observed nitrogen concentration than those generated from the CRDR and BD. This conclusion agrees with the results of previous studies [26].…”

Section: Utility Of the Methods Used In This Study In Estimating Thesupporting

confidence: 94%

“…In fact, previous studies using a predictive approach based on hyperspectral remote sensing mainly focused on a single crop species [10,23,24] or one age group [25]. Few studies have attempted to apply hyperspectral data to determine the status of sugarcane nutrients at the foliar or canopy level [26][27][28][29]. As applications of hyperspectral data are in the infancy stage, studies are needed to achieve a better understanding of sugarcane spectral information.…”

Section: Introductionmentioning

confidence: 99%

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Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

et al. 2012

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Abstract:The retrieval of nutrient concentration in sugarcane through hyperspectral remote sensing is widely known to be affected by canopy architecture. The goal of this research was to develop an estimation model that could explain the nitrogen variations in sugarcane with combined cultivars. Reflectance spectra were measured over the sugarcane canopy using a field spectroradiometer. The models were calibrated by a vegetation index and multiple linear regression. The original reflectance was transformed into a First-Derivative Spectrum (FDS) and two absorption features. The results indicated that the sensitive spectral wavelengths for quantifying nitrogen content existed mainly in the visible, red edge and far near-infrared regions of the electromagnetic spectrum. Normalized Differential Index (NDI) based on FDS (750/700) and Ratio Spectral Index (RVI) based on FDS (724/700) The strong correlation between measured and estimated nitrogen concentration indicated that the methods proposed in this study could be used for the reliable diagnosis of nitrogen quantity in sugarcane. Finally, the success of the field spectroscopy used for estimating the nutrient quality of sugarcane allowed an additional experiment using the polar orbiting hyperspectral data for the timely determination of crop nutrient status in rangelands without any requirement of prior cultivar information.

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Section: Utility Of the Methods Used In This Study In Estimating Thesupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

et al. 2012

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“…According to the findings reported by Blackburn and Ferwerda [9], first derivative reflectance spectra can be more suitable as input for WT analysis than original reflectance spectra, due to the strengthening of feature peaks and valleys by derivative analysis. The reduced spectra were then subjected to first derivative analysis with the Savitzky-Golay smoothing method to minimize the impact of soil background and multiple scattering of radiation on canopy reflectance spectra [9,10].…”

Section: Spectral Pre-processingmentioning

confidence: 99%

“…Hyperspectral remote sensing is a valid alternative to traditional ground-based methods, and it has been widely used to quantify the biophysical (e.g., leaf area index and net primary productivity) [7] and biochemical (e.g., chlorophyll and nitrogen) [8][9][10] properties of plants at the leaf, canopy, and landscape levels. Numerous studies have focused on the retrieval of the spectrally active biochemical properties of plants (e.g., water, chlorophyll, and nitrogen) using physical or statistical models [8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…Numerous studies have focused on the retrieval of the spectrally active biochemical properties of plants (e.g., water, chlorophyll, and nitrogen) using physical or statistical models [8][9][10][11][12][13][14][15][16][17][18][19][20]. In contrast, much less progress has been made to estimate foliar heavy metal concentrations [21][22][23][24][25], which may be due to their very low concentrations in plant leaves (e.g., normally 5−30 mg•kg −1 for Cu) [26] and absence of evident physical absorption features existing for major constituents (e.g., water, chlorophyll, and starch) [27].…”

Section: Introductionmentioning

confidence: 99%

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A Wavelet-Based Area Parameter for Indirectly Estimating Copper Concentration in Carex Leaves from Canopy Reflectance

Wang

Shi

et al. 2015

Remote Sensing

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Due to the absence of evident absorption features and low concentrations, the copper (Cu) concentration in plant leaves has rarely been estimated from hyperspectral remote sensing data. The capability of remotely-sensed estimation of foliar Cu concentrations largely depends on its close relation to foliar chlorophyll concentration. To enhance the subtle spectral changes related to chlorophyll concentration under Cu stress, this study described a wavelet-based area parameter (SWT (605−720), the sum of reconstructed detail reflectance at fourth decomposition level over 605−720 nm using discrete wavelet transform) from the canopy hyperspectral reflectance (350−2500 nm, N = 71) of Carex (C. cinerascens). The results showed that Cu concentrations had negative and strong correlation with chlorophyll concentrations (r = -0.719, p < 0.001). Based on 1000 random dataset partitioning experiments, the 1000 linear calibration models provided a mean R 2 Val (determination coefficient of validation) value of 0.706 and an RPD (residual prediction deviation) value of 1.75 for Cu estimation. The bootstrapping and ANOVA test results showed that SWT (605−720) significantly (p < 0.05) outperformed published chlorophyll-related and wavelet-based spectral parameters. It was concluded here that the wavelet-based area parameter (i.e., SWT (605−720)) has potential ability to indirectly estimate OPEN ACCESSRemote Sens. 2015, 7 15341Cu concentrations in Carex leaves through the strong correlation between Cu and chlorophyll. The method presented in this pilot study may be used to estimate the concentrations of other heavy metals. However, further research is needed to test its transferability and robustness for estimating Cu concentrations on other plant species in different biological and environmental conditions.

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Hyperspectral Remote Sensing with Emphasis on Land Cover Mapping: From Ground to Satellite Observations

Petropoulos

Manevski

Carlson

2014

Scale Issues in Remote Sensing

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Estimation of sugarcane leaf nitrogen concentration using in situ spectroscopy

Cited by 72 publications

References 32 publications

Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

A Wavelet-Based Area Parameter for Indirectly Estimating Copper Concentration in Carex Leaves from Canopy Reflectance

Hyperspectral Remote Sensing with Emphasis on Land Cover Mapping: From Ground to Satellite Observations

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