On the public citation graph

Hyperspectral determination of feed quality constituents in temperate pastures: Effect of processing methods on predictive relationships from partial least squares regression

https://doi.org/10.1016/j.jag.2012.06.006
0 signed · 99 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4612-3302-2_7openalex-snapshot
Evaluation of Canopy Biochemistry
inferredcites →https://doi.org/10.1016/0034-4257(88)90092-2openalex-snapshot
Prediction of leaf chemistry by the use of visible and near infrared reflectance spectroscopy
inferredcites →https://doi.org/10.1016/0034-4257(92)90133-5openalex-snapshot
Reflectance spectroscopy of fresh whole leaves for the estimation of chemical concentration
inferredcites →https://doi.org/10.1016/0034-4257(93)90104-6openalex-snapshot
Use of second derivatives of canopy reflectance for monitoring prairie vegetation over different soil backgrounds
inferredcites →https://doi.org/10.1016/0034-4257(95)00135-nopenalex-snapshot
Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400–2500 nm) at leaf and canopy scales
inferredcites →https://doi.org/10.1016/j.jqsrt.2010.03.007openalex-snapshot
Brightness-normalized Partial Least Squares Regression for hyperspectral data
inferredcites →https://doi.org/10.1016/j.rse.2003.11.001openalex-snapshot
Predicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features
inferredcites →https://doi.org/10.1016/j.rse.2004.06.008openalex-snapshot
Estimating foliage nitrogen concentration from HYMAP data using continuum removal analysis
inferredcites →https://doi.org/10.1016/j.rse.2004.08.006openalex-snapshot
Estimation of pasture growth rate in the south west of Western Australia from AVHRR NDVI and climate data
inferredcites →https://doi.org/10.1016/j.rse.2007.02.027openalex-snapshot
Estimating forage quantity and quality using aerial hyperspectral imagery for northern mixed-grass prairie
inferredcites →https://doi.org/10.1016/j.rse.2007.08.005openalex-snapshot
Retrieval of chlorophyll concentration from leaf reflectance spectra using wavelet analysis
inferredcites →https://doi.org/10.1016/j.rse.2009.08.010openalex-snapshot
Forage quality of savannas — Simultaneously mapping foliar protein and polyphenols for trees and grass using hyperspectral imagery
inferredcites →https://doi.org/10.1016/j.rse.2011.07.021openalex-snapshot
Synergies between VSWIR and TIR data for the urban environment: An evaluation of the potential for the Hyperspectral Infrared Imager (HyspIRI) Decadal Survey mission
inferredcites →https://doi.org/10.1016/j.still.2005.11.013openalex-snapshot
Remote sensing of crop residue cover and soil tillage intensity
inferredcites →https://doi.org/10.1016/s0034-4257(00)00113-9openalex-snapshot
Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance
inferredcites →https://doi.org/10.1016/s0034-4257(00)00163-2openalex-snapshot
Investigating a Physical Basis for Spectroscopic Estimates of Leaf Nitrogen Concentration
inferredcites →https://doi.org/10.1016/s0034-4257(01)00182-1openalex-snapshot
Estimating the foliar biochemical concentration of leaves with reflectance spectrometry
inferredcites →https://doi.org/10.1016/s0034-4257(01)00191-2openalex-snapshot
Detecting vegetation leaf water content using reflectance in the optical domain
inferredcites →https://doi.org/10.1016/s0034-4257(02)00011-1openalex-snapshot
Remote sensing of nitrogen and lignin in Mediterranean vegetation from AVIRIS data
inferredcites →https://doi.org/10.1016/s0034-4257(02)00049-4openalex-snapshot
Remote sensing of forest pigments using airborne imaging spectrometer and LIDAR imagery
inferredcites →https://doi.org/10.1016/s0034-4257(02)00113-xopenalex-snapshot
Steady-state chlorophyll a fluorescence detection from canopy derivative reflectance and double-peak red-edge effects
inferredcites →https://doi.org/10.1016/s0034-4257(02)00133-5openalex-snapshot
Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data
inferredcites →https://doi.org/10.1016/s0034-4257(98)00013-3openalex-snapshot
Processing of High Spectral Resolution Reflectance Data for the Retrieval of Canopy Water Content Information
inferredcites →https://doi.org/10.1016/s0034-4257(98)00032-7openalex-snapshot
Derivative Analysis of Hyperspectral Data
inferredcites →https://doi.org/10.1016/s0034-4257(98)00038-8openalex-snapshot
Estimating Canopy Water Content of Chaparral Shrubs Using Optical Methods
inferredcites →https://doi.org/10.1016/s0034-4257(98)00059-5openalex-snapshot
Quantifying Chlorophylls and Caroteniods at Leaf and Canopy Scales
inferredcites →https://doi.org/10.1016/s0034-4257(98)00081-9openalex-snapshot
The Propagation of Foliar Biochemical Absorption Features in Forest Canopy Reflectance
inferredcites →https://doi.org/10.1016/s0034-4257(98)00084-4openalex-snapshot
Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear Regression
inferredcites →https://doi.org/10.1016/s0034-4257(99)00048-6openalex-snapshot
Relationships between Spectral Reflectance and Pigment Concentrations in Stacks of Deciduous Broadleaves
inferredcites →https://doi.org/10.1016/s0034-4257(99)00082-6openalex-snapshot
Plant Litter and Soil Reflectance
inferredcites →https://doi.org/10.1016/s0303-2434(01)85040-6openalex-snapshot
Use of high spectral resolution remote sensing to determine leaf palatability of eucalypt trees for folivorous marsupials
inferredcites →https://doi.org/10.1016/s0377-8401(97)00087-4openalex-snapshot
The prediction of intake potential and organic matter digestibility of grass silages by near infrared spectroscopy analysis of undried samples
inferredcites →https://doi.org/10.1016/s0377-8401(97)00175-2openalex-snapshot
The use of near infrared reflectance spectroscopy (NIRS) on undried samples of grass silage to predict chemical composition and digestibility parameters
inferredcites →https://doi.org/10.1029/jb089ib07p06329openalex-snapshot
Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications
inferredcites →https://doi.org/10.1073/pnas.0707823105openalex-snapshot
Global mapping of ecosystem services and conservation priorities
inferredcites →https://doi.org/10.1080/01431160110104683openalex-snapshot
Spectral characteristics of lignin and soluble phenolics in the near infrared- a comparative study
inferredcites →https://doi.org/10.1080/01431160410001720207openalex-snapshot
Discriminating sodium concentration in a mixed grass species environment of the Kruger National Park using field spectrometry
inferredcites →https://doi.org/10.1080/01431160500497119openalex-snapshot
A bootstrap procedure to select hyperspectral wavebands related to tannin content
inferredcites →https://doi.org/10.1080/01431160512331326738openalex-snapshot
Estimating tropical pasture quality at canopy level using band depth analysis with continuum removal in the visible domain
inferredcites →https://doi.org/10.1080/01431160600928625openalex-snapshot
Wavelet decomposition of hyperspectral data: a novel approach to quantifying pigment concentrations in vegetation
inferredcites →https://doi.org/10.1080/01431161003743181openalex-snapshot
Quantitative mapping of pasture biomass using satellite imagery
inferredcites →https://doi.org/10.1080/01431168408948849openalex-snapshot
The remote sensing of contaminated land
inferredcites →https://doi.org/10.1080/01431169008955129openalex-snapshot
Visible and near infrared reflectance characteristics of dry plant materials
inferredcites →https://doi.org/10.1080/014311698215441openalex-snapshot
On spectral estimates of fresh leaf biochemistry
inferredcites →https://doi.org/10.1080/10106049009354272openalex-snapshot
Remote Sensing of Biosphere Functioning
inferredcites →https://doi.org/10.1080/14498596.2006.9635087openalex-snapshot
Detection of Sclerotinia rot disease on celery using hyperspectral data and partial least squares regression
inferredcites →https://doi.org/10.1088/0957-0233/12/10/708openalex-snapshot
Multivariate Analysis of Quality. An Introduction
inferredcites →https://doi.org/10.1109/36.298007openalex-snapshot
Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection approach
inferredcites →https://doi.org/10.1109/36.563280openalex-snapshot
Remote sensing the biochemical composition of a slash pine canopy
inferredcites →https://doi.org/10.1109/36.79425openalex-snapshot
The derivative ratio algorithm: avoiding atmospheric effects in remote sensing
inferredcites →https://doi.org/10.1109/36.934078openalex-snapshot
Discrimination of arid vegetation with airborne multispectral scanner hyperspectral imagery
inferredcites →https://doi.org/10.1109/igarss.2001.976632openalex-snapshot
Nutrient estimation of eucalypt foliage derived from hyperspectral data
inferredcites →https://doi.org/10.1109/tgrs.2003.813135openalex-snapshot
Prediction of eucalypt foliage nitrogen content from satellite-derived hyperspectral data
inferredcites →https://doi.org/10.1111/j.1365-2494.2003.00391.xopenalex-snapshot
Assessment of seasonal dry‐matter yield and quality of grass swards with imaging spectroscopy
inferredcites →https://doi.org/10.1111/j.1744-697x.2008.00116.xopenalex-snapshot
Estimating forage biomass and quality in a mixed sown pasture based on partial least squares regression with waveband selection
inferredcites →https://doi.org/10.1139/x26-068openalex-snapshot
Determination of carbon fraction and nitrogen concentration in tree foliage by near infrared reflectances: a comparison of statistical methods
inferredcites →https://doi.org/10.1198/004017004000000167openalex-snapshot
A User-Friendly Guide to Multivariate Calibration and Classification
inferredcites →https://doi.org/10.1255/978-1-906715-25-0openalex-snapshot
A user-friendly guide to Multivariate Calibration and Classification
inferredcites →https://doi.org/10.1562/0031-8655(2002)0750272accipl2.0.co2openalex-snapshot
Assessing Carotenoid Content in Plant Leaves with Reflectance Spectroscopy¶
inferredcites →https://doi.org/10.18174/121541openalex-snapshot
Hyperspectral remote sensing of tropical grass quality and quantity
inferredcites →https://doi.org/10.1890/0012-9658(2002)083[0339:rvifca]2.0.co;2openalex-snapshot
REGIONAL VARIATION IN FOLIAR CHEMISTRY AND N CYCLING AMONG FORESTS OF DIVERSE HISTORY AND COMPOSITION*
inferredcites →https://doi.org/10.1890/1051-0761(1997)007[0431:hsrrso]2.0.co;2openalex-snapshot
HIGH SPECTRAL RESOLUTION REMOTE SENSING OF FOREST CANOPY LIGNIN, NITROGEN, AND ECOSYSTEM PROCESSES
inferredcites →https://doi.org/10.2135/cropsci2005.0258openalex-snapshot
Development of Canopy Reflectance Algorithms for Real‐Time Prediction of Bermudagrass Pasture Biomass and Nutritive Values
inferredcites →https://doi.org/10.2307/2680018openalex-snapshot
Regional Variation in Foliar Chemistry and N Cycling among Forests of Diverse History and Composition
inferredcites →https://doi.org/10.2527/jas1976.434889xopenalex-snapshot
Predicting Forage Quality by Infrared Replectance Spectroscopy
inferredcites →https://doi.org/10.4081/ijas.2004.363openalex-snapshot
Quality evaluation of regional forage resources by means of near infrared reflectance spectroscopy

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4571009openalex-extracted
inferred← citeshttps://doi.org/10.1002/ece3.2876openalex-snapshot
Correlating species and spectral diversities using hyperspectral remote sensing in early‐successional fields
inferred← citeshttps://doi.org/10.1007/978-981-16-5437-4_9openalex-snapshot
Nutritional Quality Estimation of Forages
inferred← citeshttps://doi.org/10.1007/978-981-19-6020-8_13openalex-snapshot
Quality Evaluation of Natural Grasslands and Pastures
inferred← citeshttps://doi.org/10.1016/j.anifeedsci.2020.114670openalex-snapshot
Use of traditional, modern, and hybrid modelling approaches for in situ prediction of dry matter yield and nutritive characteristics of pasture using hyperspectral datasets
inferred← citeshttps://doi.org/10.1016/j.chemolab.2023.104925openalex-snapshot
Enhancing tomato leaf nitrogen analysis through portable NIR spectrometers combined with machine learning and chemometrics
inferred← citeshttps://doi.org/10.1016/j.compag.2023.108275openalex-snapshot
Comparing the predictive ability of Sentinel-2 multispectral imagery and a proximal hyperspectral sensor for the estimation of pasture nutritive characteristics in an intensive rotational grazing system
inferred← citeshttps://doi.org/10.1016/j.compag.2024.109714openalex-snapshot
Estimation of crude protein content in natural pasture grass using unmanned aerial vehicle hyperspectral data
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2016.08.004openalex-snapshot
Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield
inferred← citeshttps://doi.org/10.1016/j.jag.2013.06.002openalex-snapshot
Estimating soil salinity in Pingluo County of China using QuickBird data and soil reflectance spectra
inferred← citeshttps://doi.org/10.1016/j.jag.2015.04.019openalex-snapshot
Spectral indicators of forage quality in West Africa’s tropical savannas
inferred← citeshttps://doi.org/10.1016/j.jag.2017.02.013openalex-snapshot
Hyperspectral-based predictive modelling of grapevine water status in the Portuguese Douro wine region
inferred← citeshttps://doi.org/10.1016/j.rse.2015.06.009openalex-snapshot
Remote sensing of foliar nitrogen in cultivated grasslands of human dominated landscapes
inferred← citeshttps://doi.org/10.1016/j.rse.2018.02.030openalex-snapshot
The functional characterization of grass- and shrubland ecosystems using hyperspectral remote sensing: trends, accuracy and moderating variables
inferred← citeshttps://doi.org/10.1016/j.rse.2018.11.016openalex-snapshot
Mapping foliar functional traits and their uncertainties across three years in a grassland experiment
inferred← citeshttps://doi.org/10.1016/j.rse.2021.112353openalex-snapshot
Field spectroscopy of canopy nitrogen concentration in temperate grasslands using a convolutional neural network
inferred← citeshttps://doi.org/10.1039/c3em00388dopenalex-snapshot
Detection of multiple stresses in Scots pine growing at post-mining sites using visible to near-infrared spectroscopy
inferred← citeshttps://doi.org/10.1071/cp19324openalex-snapshot
Proximal sensing of Urochloa grasses increases selection accuracy
inferred← citeshttps://doi.org/10.1080/01431161.2015.1024893openalex-snapshot
Predicting C3 and C4 grass nutrient variability using in situ canopy reflectance and partial least squares regression
inferred← citeshttps://doi.org/10.1080/22797254.2021.1934556openalex-snapshot
Towards Forage Resource Monitoring in subtropical Savanna Grasslands: going multispectral or hyperspectral?
inferred← citeshttps://doi.org/10.1088/1748-9326/ac09afopenalex-snapshot
Estimating integrated measures of forage quality for herbivores by fusing optical and structural remote sensing data
inferred← citeshttps://doi.org/10.1109/tgrs.2021.3105482openalex-snapshot
Estimating the Forage Neutral Detergent Fiber Content of Alpine Grassland in the Tibetan Plateau Using Hyperspectral Data and Machine Learning Algorithms
inferred← citeshttps://doi.org/10.1111/2041-210x.13237openalex-snapshot
A novel procedure for measuring functional traits of herbaceous species through field spectroscopy
inferred← citeshttps://doi.org/10.12760/02-2015-2-06openalex-snapshot
Evaluation of leaf area index and dry matter predictions for crop growth modelling and yield esti-mation based on field reflectance measurements
inferred← citeshttps://doi.org/10.1371/journal.pone.0232313openalex-snapshot
Suitability of resampled multispectral datasets for mapping flowering plants in the Kenyan savannah
inferred← citeshttps://doi.org/10.14941/grass.60.167openalex-snapshot
航空機リモートセンシングによるハイパースペクトルデータを用いた飼料用トウモロコシ(Zea mays L.)の収量と飼料成分含有率の推定
inferred← citeshttps://doi.org/10.18002/10612/5735openalex-snapshot
Estimación de la biomasa aérea de herbáceas con sensores aerotransportados de alta resolución = Estimating aboveground biomass of herbaceous with high resolution airborne sensors
inferred← citeshttps://doi.org/10.3390/agriengineering3020021openalex-snapshot
Predicting Key Grassland Characteristics from Hyperspectral Data
inferred← citeshttps://doi.org/10.3390/rs10071117openalex-snapshot
Integrating Airborne Hyperspectral, Topographic, and Soil Data for Estimating Pasture Quality Using Recursive Feature Elimination with Random Forest Regression
inferred← citeshttps://doi.org/10.3390/rs15194866openalex-snapshot
Advancing Skyborne Technologies and High-Resolution Satellites for Pasture Monitoring and Improved Management: A Review
inferred← citeshttps://doi.org/10.3390/rs16173168openalex-snapshot
Soil Organic Carbon Estimation via Remote Sensing and Machine Learning Techniques: Global Topic Modeling and Research Trend Exploration
inferred← citeshttps://doi.org/10.3390/s150817990openalex-snapshot
Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method
inferred← citeshttps://doi.org/10.4236/ajps.2014.57113openalex-snapshot
Predicting Levels of Crude Protein, Digestibility, Lignin and Cellulose in Temperate Pastures Using Hyperspectral Image Data
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.