Prediction of palm-tree ganoderma affection degree by reflectance spectroscopy: Proposed methodology
The aim of this study was thus to test the relevance of statistical methods to detect the variations in spectral signature of oil-palm trees correlated to Ganoderma disease, a fungus responsible of high loss of yield and trees in palm groves. The objective is too discriminate infected palm trees and to establish a ranking in the degree of infection. Some previous studies (Lanore, 2006; et Brégand, 2007) revealed that it is feasible, but the number of individuals was too small to lead to statistically reliable models; thus, it is still to confirm and validate. More especially, the present study focuses on the possibility of infected palm-tree discrimination in accordance to four sickness degrees: Healthy, Low, Medium and High infection. It will test this potential at several scales: the leaflet, the canopy, and by remote sensing.
| Main Authors: | , , |
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| Format: | monograph biblioteca |
| Language: | eng |
| Published: |
CIRAD
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| Subjects: | H20 - Maladies des plantes, U30 - Méthodes de recherche, Ganoderma, spectrométrie, Elaeis guineensis, http://aims.fao.org/aos/agrovoc/c_15973, http://aims.fao.org/aos/agrovoc/c_7283, http://aims.fao.org/aos/agrovoc/c_2509, http://aims.fao.org/aos/agrovoc/c_7518, |
| Online Access: | http://agritrop.cirad.fr/553387/ http://agritrop.cirad.fr/553387/1/document_553387.pdf |
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| Summary: | The aim of this study was thus to test the relevance of statistical methods to detect the variations in spectral signature of oil-palm trees correlated to Ganoderma disease, a fungus responsible of high loss of yield and trees in palm groves. The objective is too discriminate infected palm trees and to establish a ranking in the degree of infection. Some previous studies (Lanore, 2006; et Brégand, 2007) revealed that it is feasible, but the number of individuals was too small to lead to statistically reliable models; thus, it is still to confirm and validate. More especially, the present study focuses on the possibility of infected palm-tree discrimination in accordance to four sickness degrees: Healthy, Low, Medium and High infection. It will test this potential at several scales: the leaflet, the canopy, and by remote sensing. |
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