A novel spectral index for estimation of relative chlorophyll content of sugar beet

[1]  Susan L. Ustin,et al.  Improving estimation of summer maize nitrogen status with red edge-based spectral vegetation indices , 2014 .

[2]  Stephen Smith,et al.  Contributions of Parental Inbreds and Heterosis to Morphology and Yield of Single‐Cross Maize Hybrids in China , 2014 .

[3]  Kenji Omasa,et al.  A robust vegetation index for remotely assessing chlorophyll content of dorsiventral leaves across several species in different seasons , 2018, Plant Methods.

[4]  G. Carter.  Ratios of leaf reflectances in narrow wavebands as indicators of plant stress , 1994 .

[5]  Humberto Bustince,et al.  New method to assess barley nitrogen nutrition status based on image colour analysis , 2009 .

[6]  Hong Sun,et al.  Estimation of Chlorophyll Content in Potato Leaves Based on Spectral Red Edge Position , 2018 .

[7]  W. E. Larson,et al.  Coincident detection of crop water stress, nitrogen status and canopy density using ground-based multispectral data. , 2000 .

[8]  Yang Chen.  Reference-related component analysis: A new method inheriting the advantages of PLS and PCA for separating interesting information and reducing data dimension , 2016 .

[9]  Ling Lin,et al.  Kennard-Stone combined with least square support vector machine method for noncontact discriminating human blood species , 2017 .

[10]  Qingsong Xu,et al.  A partition-based variable selection in partial least squares regression , 2020 .

[11]  Prasad S. Thenkabail,et al.  Nondestructive Estimation of Foliar Pigment (Chlorophylls, Carotenoids, and Anthocyanins) Contents: Evaluating a Semianalytical Three-Band Model , 2016 .

[12]  Anatoly A. Gitelson,et al.  Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[13]  A. Viña,et al.  Green leaf area index estimation in maize and soybean: Combining vegetation indices to achieve maximal sensitivity , 2012 .

[14]  T. Cheng,et al.  Assessment of unified models for estimating leaf chlorophyll content across directional-hemispherical reflectance and bidirectional reflectance spectra , 2019, Remote Sensing of Environment.

[15]  Yuri A. Gritz,et al.  Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. , 2003, Journal of plant physiology.

[16]  Haikuan Feng,et al.  Estimating leaf SPAD values of freeze-damaged winter wheat using continuous wavelet analysis. , 2016, Plant physiology and biochemistry : PPB.

[17]  J. M. Blonquist,et al.  In situ measurement of leaf chlorophyll concentration: analysis of the optical/absolute relationship. , 2014, Plant, cell & environment.

[18]  Jiali Shang,et al.  Assessment of red-edge vegetation indices for crop leaf area index estimation , 2019, Remote Sensing of Environment.

[19]  Li Dongsheng,et al.  Responses of rice leaf thickness, SPAD readings and chlorophyll a/b ratios to different nitrogen supply rates in paddy field , 2009 .

[20]  Jan G. P. W. Clevers,et al.  Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3 , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[21]  Ngai Paing Tan,et al.  Hyperspectral remote sensing for assessment of chlorophyll sufficiency levels in mature oil palm (Elaeis guineensis) based on frond numbers: Analysis of decision tree and random forest , 2020, Comput. Electron. Agric..

[22]  C. Evangelides,et al.  Red-Edge Normalised Difference Vegetation Index (NDVI705) from Sentinel-2 imagery to assess post-fire regeneration , 2020 .

[23]  M. Gholamhoseini,et al.  Evaluation of proline, chlorophyll, soluble sugar content and uptake of nutrients in the German chamomile (Matricaria chamomilla L.) under drought stress and organic fertilizer treatments , 2016 .

[24]  Xin-shi Zhang,et al.  Estimation of green aboveground biomass of desert steppe in Inner Mongolia based on red-edge reflectance curve area method , 2011 .

[25]  Frédéric Baret,et al.  Estimating leaf chlorophyll content in sugar beet canopies using millimeter- to centimeter-scale reflectance imagery , 2017 .

[26]  Anatoly A. Gitelson,et al.  Generic Algorithms for Estimating Foliar Pigment Content , 2017 .

[27]  Francis B. Lavoie,et al.  A novel robust NL-PLS regression methodology , 2019, Chemometrics and Intelligent Laboratory Systems.

[28]  Bisun Datt,et al.  A New Reflectance Index for Remote Sensing of Chlorophyll Content in Higher Plants: Tests using Eucalyptus Leaves , 1999 .

[29]  Jinbao Liu,et al.  Hyperspectral characteristics and quantitative analysis of leaf chlorophyll by reflectance spectroscopy based on a genetic algorithm in combination with partial least squares regression. , 2020, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[30]  Andrew K. Skidmore,et al.  Mapping forest canopy nitrogen content by inversion of coupled leaf-canopy radiative transfer models from airborne hyperspectral imagery , 2018 .

[31]  P. Kempeneers,et al.  Chlorophyll content estimation in an open-canopy conifer forest with Sentinel-2A and hyperspectral imagery in the context of forest decline , 2019, Remote sensing of environment.

[32]  Quan Wang,et al.  Hyperspectral indices for quantifying leaf chlorophyll concentrations performed differently with different leaf types in deciduous forests , 2017, Ecol. Informatics.

[33]  Moon S. Kim,et al.  Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .

[34]  F. A. Dray,et al.  In situ estimates of waterhyacinth leaf tissue nitrogen using a SPAD-502 chlorophyll meter , 2012 .

[35]  O. Mutanga,et al.  Evaluating the impact of red-edge band from Rapideye image for classifying insect defoliation levels , 2014 .

[36]  L. Alonso,et al.  A red-edge spectral index for remote sensing estimation of green LAI over agroecosystems , 2013 .

[37]  Anatoly A. Gitelson,et al.  Non-destructive estimation of foliar chlorophyll and carotenoid contents: Focus on informative spectral bands , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[38]  Guo Yu Qiu,et al.  Estimation of chlorophyll content in intertidal mangrove leaves with different thicknesses using hyperspectral data , 2019, Ecological Indicators.

[39]  Ricardo Bressan-Smith,et al.  Photosynthetic pigments, nitrogen, chlorophyll a fluorescence and SPAD-502 readings in coffee leaves , 2005 .

[40]  Hai-Teng Liu,et al.  [Estimation of chlorophyll content in apple tree canopy based on hyperspectral parameters]. , 2013, Guang pu xue yu guang pu fen xi = Guang pu.

[41]  A. Gitelson,et al.  Active Sensor Reflectance Measurements of Corn Nitrogen Status and Yield Potential , 2008 .

[42]  Andrew K. Skidmore,et al.  Advances in remote sensing of vegetation function and traits , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[43]  Xiaojuan Li,et al.  Angle effects of vegetation indices and the influence on prediction of SPAD values in soybean and maize , 2020, Int. J. Appl. Earth Obs. Geoinformation.

[44]  B. Datt.  Remote Sensing of Chlorophyll a, Chlorophyll b, Chlorophyll a+b, and Total Carotenoid Content in Eucalyptus Leaves , 1998 .

[45]  A. Gitelson,et al.  Use of a green channel in remote sensing of global vegetation from EOS- MODIS , 1996 .

[46]  Tatas H. P. Brotosudarmo,et al.  Analysis on the Chlorophyll Content of Commercial Green Leafy Vegetables , 2015 .

[47]  G. Rondeaux,et al.  Optimization of soil-adjusted vegetation indices , 1996 .

[48]  A. Gitelson,et al.  Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation , 1994 .

[49]  C. Atzberger,et al.  Evaluation of semi-empirical BRDF models inverted against multi-angle data from a digital airborne frame camera for enhancing forest type classification , 2014 .

[50]  M. Neyshabouri,et al.  Evaluation of canola chlorophyll index and leaf nitrogen under wide range of soil moisture , 2015 .

[51]  D. Sims,et al.  Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages , 2002 .

[52]  M. S. Borhan,et al.  Evaluation of computer imaging technique for predicting the SPAD readings in potato leaves. , 2017 .

[53]  Yi Ma,et al.  Evaluating chlorophyll density in winter oilseed rape (Brassica napus L.) using canopy hyperspectral red-edge parameters , 2016, Comput. Electron. Agric..