Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing

This studies focuses on the relationships between the reflectance spectra of oil palm leaves and their deficiencies in nitrogen and different minerals (P, K, Mg, Fe). The aim of this work is to develop tools for nutritive stress detection based on remote sensing. A data base was constituted in Indonesia on oil palm trees showing apparent deficiencies and on others grown in trials balancing N and P on one side and K and Mg on the other side. Measurements were done at the leaflet level, providing with a mean reflectance for the leaf in the visible and near-infrared domain (400-900 nm). In parallel, chemical analysis of the leaflets were achieved to provide with the mean concentrations of the different constituents of the leaf. 48 spectral indexes were selected to describe the more exhaustively the spectral features, or found in the literature as efficient parameters to detect nutrition stresses. Statistical analysis was achieved in two different ways: one to establish a predictive model for the chemical concentrations of N, P, K, Mg and Fe in the leaf and one to discriminate these five main classes of deficiencies observed in the fields. None of these approaches led to a significant result, as errors are very high and much above the stress detection threshold or the expected level of discrimination. Possible causes of noise are analysed and perspective to improve the analysis are given.

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Main Authors: Lelong, Camille, Lanore, Mathieu, Caliman, Jean-Pierre
Format: conference_item biblioteca
Language:eng
Published: Universitat de Valencia
Subjects:U30 - Méthodes de recherche, F61 - Physiologie végétale - Nutrition, Elaeis guineensis, télédétection, stress, nutrition des plantes, http://aims.fao.org/aos/agrovoc/c_2509, http://aims.fao.org/aos/agrovoc/c_6498, http://aims.fao.org/aos/agrovoc/c_7452, http://aims.fao.org/aos/agrovoc/c_16379,
Online Access:http://agritrop.cirad.fr/539313/
http://agritrop.cirad.fr/539313/1/document_539313.pdf
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spelling dig-cirad-fr-5393132024-01-28T15:13:26Z http://agritrop.cirad.fr/539313/ http://agritrop.cirad.fr/539313/ Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing. Lelong Camille, Lanore Mathieu, Caliman Jean-Pierre. 2006. In : Second recent advances in quantitative remote sensing (RAQRS'II), Auditori de Torrent, Spain, 25-29 September 2006. Sobrino José A. (ed.). Universidad de Valencia. Valence : Universitat de Valencia, 147-152. ISBN 978-84-370-6533-5 International Symposium on Recent Advances in Quantitative Remote Sensing. 2, Valence, Espagne, 25 Septembre 2006/29 Septembre 2006. Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing Lelong, Camille Lanore, Mathieu Caliman, Jean-Pierre eng 2006 Universitat de Valencia Second recent advances in quantitative remote sensing (RAQRS'II), Auditori de Torrent, Spain, 25-29 September 2006 U30 - Méthodes de recherche F61 - Physiologie végétale - Nutrition Elaeis guineensis télédétection stress nutrition des plantes http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_7452 http://aims.fao.org/aos/agrovoc/c_16379 This studies focuses on the relationships between the reflectance spectra of oil palm leaves and their deficiencies in nitrogen and different minerals (P, K, Mg, Fe). The aim of this work is to develop tools for nutritive stress detection based on remote sensing. A data base was constituted in Indonesia on oil palm trees showing apparent deficiencies and on others grown in trials balancing N and P on one side and K and Mg on the other side. Measurements were done at the leaflet level, providing with a mean reflectance for the leaf in the visible and near-infrared domain (400-900 nm). In parallel, chemical analysis of the leaflets were achieved to provide with the mean concentrations of the different constituents of the leaf. 48 spectral indexes were selected to describe the more exhaustively the spectral features, or found in the literature as efficient parameters to detect nutrition stresses. Statistical analysis was achieved in two different ways: one to establish a predictive model for the chemical concentrations of N, P, K, Mg and Fe in the leaf and one to discriminate these five main classes of deficiencies observed in the fields. None of these approaches led to a significant result, as errors are very high and much above the stress detection threshold or the expected level of discrimination. Possible causes of noise are analysed and perspective to improve the analysis are given. conference_item info:eu-repo/semantics/conferenceObject Conference info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/539313/1/document_539313.pdf application/pdf Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html http://catalogue-bibliotheques.cirad.fr/cgi-bin/koha/opac-detail.pl?biblionumber=197612 http://catalogue-bibliotheques.cirad.fr/cgi-bin/koha/opac-detail.pl?biblionumber=200757
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic U30 - Méthodes de recherche
F61 - Physiologie végétale - Nutrition
Elaeis guineensis
télédétection
stress
nutrition des plantes
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_7452
http://aims.fao.org/aos/agrovoc/c_16379
U30 - Méthodes de recherche
F61 - Physiologie végétale - Nutrition
Elaeis guineensis
télédétection
stress
nutrition des plantes
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_7452
http://aims.fao.org/aos/agrovoc/c_16379
spellingShingle U30 - Méthodes de recherche
F61 - Physiologie végétale - Nutrition
Elaeis guineensis
télédétection
stress
nutrition des plantes
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_7452
http://aims.fao.org/aos/agrovoc/c_16379
U30 - Méthodes de recherche
F61 - Physiologie végétale - Nutrition
Elaeis guineensis
télédétection
stress
nutrition des plantes
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_7452
http://aims.fao.org/aos/agrovoc/c_16379
Lelong, Camille
Lanore, Mathieu
Caliman, Jean-Pierre
Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing
description This studies focuses on the relationships between the reflectance spectra of oil palm leaves and their deficiencies in nitrogen and different minerals (P, K, Mg, Fe). The aim of this work is to develop tools for nutritive stress detection based on remote sensing. A data base was constituted in Indonesia on oil palm trees showing apparent deficiencies and on others grown in trials balancing N and P on one side and K and Mg on the other side. Measurements were done at the leaflet level, providing with a mean reflectance for the leaf in the visible and near-infrared domain (400-900 nm). In parallel, chemical analysis of the leaflets were achieved to provide with the mean concentrations of the different constituents of the leaf. 48 spectral indexes were selected to describe the more exhaustively the spectral features, or found in the literature as efficient parameters to detect nutrition stresses. Statistical analysis was achieved in two different ways: one to establish a predictive model for the chemical concentrations of N, P, K, Mg and Fe in the leaf and one to discriminate these five main classes of deficiencies observed in the fields. None of these approaches led to a significant result, as errors are very high and much above the stress detection threshold or the expected level of discrimination. Possible causes of noise are analysed and perspective to improve the analysis are given.
format conference_item
topic_facet U30 - Méthodes de recherche
F61 - Physiologie végétale - Nutrition
Elaeis guineensis
télédétection
stress
nutrition des plantes
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_7452
http://aims.fao.org/aos/agrovoc/c_16379
author Lelong, Camille
Lanore, Mathieu
Caliman, Jean-Pierre
author_facet Lelong, Camille
Lanore, Mathieu
Caliman, Jean-Pierre
author_sort Lelong, Camille
title Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing
title_short Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing
title_full Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing
title_fullStr Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing
title_full_unstemmed Evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing
title_sort evaluation of hyperspectral remote sensing relevance to estimate oil palm trees nutrition status remote sensing
publisher Universitat de Valencia
url http://agritrop.cirad.fr/539313/
http://agritrop.cirad.fr/539313/1/document_539313.pdf
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