The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings

Field spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress and disease. The objective of this study was to develop spectral indices for detection of Ganoderma disease in oil palm seedlings. The reflectance spectra of oil palm seedlings from thr...

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Main Authors: Anuar, Mohamad Izzuddin, Abu Seman, Idris, Mohd Noor, Nisfariza, Abd Aziz, Nordiana, Mohd Shafri, Helmi Zulhaidi, Bahrom, Ezzati
Format: Article
Language:English
Published: Taylor & Francis 2017
Online Access:http://psasir.upm.edu.my/id/eprint/64743/1/The%20development%20of%20spectral%20indices%20for%20early%20detection%20of%20Ganoderma%20disease%20in%20oil%20palm%20seedlings.pdf
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author Anuar, Mohamad Izzuddin
Abu Seman, Idris
Mohd Noor, Nisfariza
Abd Aziz, Nordiana
Mohd Shafri, Helmi Zulhaidi
Bahrom, Ezzati
author_facet Anuar, Mohamad Izzuddin
Abu Seman, Idris
Mohd Noor, Nisfariza
Abd Aziz, Nordiana
Mohd Shafri, Helmi Zulhaidi
Bahrom, Ezzati
author_sort Anuar, Mohamad Izzuddin
collection UPM
description Field spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress and disease. The objective of this study was to develop spectral indices for detection of Ganoderma disease in oil palm seedlings. The reflectance spectra of oil palm seedlings from three levels of Ganoderma disease severity were acquired using a spectroradiometer. Denoizing and data transformation using first derivative analysis was conducted on the original reflectance spectra. Then, comparative statistical analysis was used to select significant wavelength from transformed data. Wavelength pairs of spectral indices were selected using optimum index factor. The spectral indices were produced using the wavelength ratios and a modified simple ratio method. The relationship analysis between spectral indices and total leaf chlorophyll (TLC) was conducted using regression technique. The results suggested that six spectral indices are suitable for the early detection of Ganoderma disease in oil palm seedlings. Final results after regression with TLC showed that Ratio 3 is the best spectral index for the early detection of Ganoderma infection in oil palm seedlings. For future works, this can be used for the development of robust spectral indices for Ganoderma disease detection in young and mature oil palm using airborne hyperspectral imaging.
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spelling upm.eprints-647432018-08-14T07:09:58Z http://psasir.upm.edu.my/id/eprint/64743/ The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings Anuar, Mohamad Izzuddin Abu Seman, Idris Mohd Noor, Nisfariza Abd Aziz, Nordiana Mohd Shafri, Helmi Zulhaidi Bahrom, Ezzati Field spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress and disease. The objective of this study was to develop spectral indices for detection of Ganoderma disease in oil palm seedlings. The reflectance spectra of oil palm seedlings from three levels of Ganoderma disease severity were acquired using a spectroradiometer. Denoizing and data transformation using first derivative analysis was conducted on the original reflectance spectra. Then, comparative statistical analysis was used to select significant wavelength from transformed data. Wavelength pairs of spectral indices were selected using optimum index factor. The spectral indices were produced using the wavelength ratios and a modified simple ratio method. The relationship analysis between spectral indices and total leaf chlorophyll (TLC) was conducted using regression technique. The results suggested that six spectral indices are suitable for the early detection of Ganoderma disease in oil palm seedlings. Final results after regression with TLC showed that Ratio 3 is the best spectral index for the early detection of Ganoderma infection in oil palm seedlings. For future works, this can be used for the development of robust spectral indices for Ganoderma disease detection in young and mature oil palm using airborne hyperspectral imaging. Taylor & Francis 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/64743/1/The%20development%20of%20spectral%20indices%20for%20early%20detection%20of%20Ganoderma%20disease%20in%20oil%20palm%20seedlings.pdf Anuar, Mohamad Izzuddin and Abu Seman, Idris and Mohd Noor, Nisfariza and Abd Aziz, Nordiana and Mohd Shafri, Helmi Zulhaidi and Bahrom, Ezzati (2017) The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings. International Journal of Remote Sensing, 38 (23). pp. 6505-6527. ISSN 0143-1161; ESSN: 1366-5901 https://www.tandfonline.com/doi/abs/10.1080/01431161.2017.1335908 10.1080/01431161.2017.1335908
spellingShingle Anuar, Mohamad Izzuddin
Abu Seman, Idris
Mohd Noor, Nisfariza
Abd Aziz, Nordiana
Mohd Shafri, Helmi Zulhaidi
Bahrom, Ezzati
The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings
title The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings
title_full The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings
title_fullStr The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings
title_full_unstemmed The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings
title_short The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings
title_sort development of spectral indices for early detection of ganoderma disease in oil palm seedlings
url http://psasir.upm.edu.my/id/eprint/64743/1/The%20development%20of%20spectral%20indices%20for%20early%20detection%20of%20Ganoderma%20disease%20in%20oil%20palm%20seedlings.pdf
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