Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols properties

Spectral data contain information on soil organic and mineral composition, which can be useful for soil quality monitoring. The objective of research was to evaluate hyperspectral visible and near infrared reflectance (VNIR) spectroscopy for field-scale prediction of soil properties and assessment o...

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Main Authors: Ivana ŠESTAK, Milan MESIĆ, Željka ZGORELEC, Aleksandra PERČIN, Ivan STUPNIŠEK
Format: Article
Language:English
Published: Czech Academy of Agricultural Sciences 2018-06-01
Series:Plant, Soil and Environment
Subjects:
Online Access:https://pse.agriculturejournals.cz/artkey/pse-201806-0005_visible-and-near-infrared-reflectance-spectroscopy-for-field-scale-assessment-of-stagnosols-properties.php
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author Ivana ŠESTAK
Milan MESIĆ
Željka ZGORELEC
Aleksandra PERČIN
Ivan STUPNIŠEK
author_facet Ivana ŠESTAK
Milan MESIĆ
Željka ZGORELEC
Aleksandra PERČIN
Ivan STUPNIŠEK
author_sort Ivana ŠESTAK
collection DOAJ
description Spectral data contain information on soil organic and mineral composition, which can be useful for soil quality monitoring. The objective of research was to evaluate hyperspectral visible and near infrared reflectance (VNIR) spectroscopy for field-scale prediction of soil properties and assessment of factors affecting soil spectra. Two hundred soil samples taken from the experiment field (soil depth: 30 cm; sampling grid: 15 × 15 m) were scanned using portable spectroradiometer (350-1050 nm) to identify spectral differences of soil treated with ten different rates of mineral nitrogen (N) fertilizer (0-300 kg N/ha). Principal component analysis revealed distinction between higher- and lower-N level treatments conditioned by differences in soil pH, texture and soil organic matter (SOM) composition. Partial least square regression resulted in very strong correlation and low root mean square error (RMSE) between predicted and measured values for the calibration (C) and validation (V) dataset, respectively (SOM, %: RC2 = 0.75 and RV2 = 0.74; RMSEC = 0.334 and RMSEV = 0.346; soil pH: RC2 = 0.78 and RV2 = 0.62; RMSEC = 0.448 and RMSEV = 0.591). Results indicated that hyperspectral VNIR spectroscopy is an efficient method for measurement of soil functional attributes within precision farming framework.
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spelling doaj.art-720ff639eaae42b3a3d51c71e310befd2023-02-23T03:46:39ZengCzech Academy of Agricultural SciencesPlant, Soil and Environment1214-11781805-93682018-06-0164627628210.17221/220/2018-PSEpse-201806-0005Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols propertiesIvana ŠESTAKMilan MESIĆ0Željka ZGORELEC1Aleksandra PERČIN2Ivan STUPNIŠEK3Department of General Agronomy, Faculty of Agriculture, University of Zagreb, Zagreb, CroatiaDepartment of General Agronomy, Faculty of Agriculture, University of Zagreb, Zagreb, CroatiaDepartment of General Agronomy, Faculty of Agriculture, University of Zagreb, Zagreb, CroatiaDepartment of General Agronomy, Faculty of Agriculture, University of Zagreb, Zagreb, CroatiaSpectral data contain information on soil organic and mineral composition, which can be useful for soil quality monitoring. The objective of research was to evaluate hyperspectral visible and near infrared reflectance (VNIR) spectroscopy for field-scale prediction of soil properties and assessment of factors affecting soil spectra. Two hundred soil samples taken from the experiment field (soil depth: 30 cm; sampling grid: 15 × 15 m) were scanned using portable spectroradiometer (350-1050 nm) to identify spectral differences of soil treated with ten different rates of mineral nitrogen (N) fertilizer (0-300 kg N/ha). Principal component analysis revealed distinction between higher- and lower-N level treatments conditioned by differences in soil pH, texture and soil organic matter (SOM) composition. Partial least square regression resulted in very strong correlation and low root mean square error (RMSE) between predicted and measured values for the calibration (C) and validation (V) dataset, respectively (SOM, %: RC2 = 0.75 and RV2 = 0.74; RMSEC = 0.334 and RMSEV = 0.346; soil pH: RC2 = 0.78 and RV2 = 0.62; RMSEC = 0.448 and RMSEV = 0.591). Results indicated that hyperspectral VNIR spectroscopy is an efficient method for measurement of soil functional attributes within precision farming framework.https://pse.agriculturejournals.cz/artkey/pse-201806-0005_visible-and-near-infrared-reflectance-spectroscopy-for-field-scale-assessment-of-stagnosols-properties.phpnitrogen fertilizationremote sensingnon-destructive methodclimatic conditionsoil texturelinear calibration
spellingShingle Ivana ŠESTAK
Milan MESIĆ
Željka ZGORELEC
Aleksandra PERČIN
Ivan STUPNIŠEK
Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols properties
Plant, Soil and Environment
nitrogen fertilization
remote sensing
non-destructive method
climatic condition
soil texture
linear calibration
title Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols properties
title_full Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols properties
title_fullStr Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols properties
title_full_unstemmed Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols properties
title_short Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols properties
title_sort visible and near infrared reflectance spectroscopy for field scale assessment of stagnosols properties
topic nitrogen fertilization
remote sensing
non-destructive method
climatic condition
soil texture
linear calibration
url https://pse.agriculturejournals.cz/artkey/pse-201806-0005_visible-and-near-infrared-reflectance-spectroscopy-for-field-scale-assessment-of-stagnosols-properties.php
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