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Basal Stem Rot (BSR) detection using iextural inalysis of Unmanned Aerial Vehicle (UAV) image

Basal Stem Rot (BSR) disease is one of the most destructive diseases affecting oil palm plantation in Malaysia. The first critical step for a successful control of BSR is its detection and diagnosis. This study presents a new approach of high spatial resolution aerial Red, Green, Blue (RGB) image fo...

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Main Authors: Bejo, Siti Khairunniza, Jaleni, M., Husin, M. E., Khosrokhani, Maryam, Muharam, Farrah Melissa, Abu Seman, Idris, Anuar, Mohamad Izzuddin
Format: Article
Language:English
English
Published: Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia 2018
Online Access:http://psasir.upm.edu.my/id/eprint/53274/1/Methods%20of%20reducing%20the%20fate%20and%20transport%20of%20nutrients%20from%20agricultural%20fields.pdf
http://psasir.upm.edu.my/id/eprint/53274/7/Basal%20Stem%20Rot%20%28BSR%29%20detection%20using%20iextural%20inalysis%20of%20Unmanned%20Aerial%20Vehicle%20%28UAV%29%20image.pdf
http://psasir.upm.edu.my/id/eprint/53274/
http://eproceedings.chemistry.utm.my/index.php/FYP/index
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spelling my.upm.eprints.532742019-05-09T05:56:26Z http://psasir.upm.edu.my/id/eprint/53274/ Basal Stem Rot (BSR) detection using iextural inalysis of Unmanned Aerial Vehicle (UAV) image Bejo, Siti Khairunniza Jaleni, M. Husin, M. E. Khosrokhani, Maryam Muharam, Farrah Melissa Abu Seman, Idris Anuar, Mohamad Izzuddin Basal Stem Rot (BSR) disease is one of the most destructive diseases affecting oil palm plantation in Malaysia. The first critical step for a successful control of BSR is its detection and diagnosis. This study presents a new approach of high spatial resolution aerial Red, Green, Blue (RGB) image for BSR detection using a low-altitude remote sensing Unmanned Aerial Vehicle (UAV) platform. The co-occurrence measures for textural analysis were performed to the RGB band to determine the best parameter for BSR detection. Descriptive statistical as well as One way ANOVA were executed to indicate which bands are giving significant level (p<0.05). Apparently, the test gave three significant properties which are Correlation taken from R, G and B band. The developed conditional statement of detection was tested for distinguishing between healthy and BSR-infected trees. Total accuracy acquired for healthy trees was 86.21% whereas for BSR-infected trees was 75.00%. Hence, average accuracy assessment was 80.61%. Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia 2018-10 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/53274/1/Methods%20of%20reducing%20the%20fate%20and%20transport%20of%20nutrients%20from%20agricultural%20fields.pdf text en http://psasir.upm.edu.my/id/eprint/53274/7/Basal%20Stem%20Rot%20%28BSR%29%20detection%20using%20iextural%20inalysis%20of%20Unmanned%20Aerial%20Vehicle%20%28UAV%29%20image.pdf Bejo, Siti Khairunniza and Jaleni, M. and Husin, M. E. and Khosrokhani, Maryam and Muharam, Farrah Melissa and Abu Seman, Idris and Anuar, Mohamad Izzuddin (2018) Basal Stem Rot (BSR) detection using iextural inalysis of Unmanned Aerial Vehicle (UAV) image. eProceedings Chemistry, 3 (1). pp. 1186-1197. ISSN 2550-1453 http://eproceedings.chemistry.utm.my/index.php/FYP/index
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Basal Stem Rot (BSR) disease is one of the most destructive diseases affecting oil palm plantation in Malaysia. The first critical step for a successful control of BSR is its detection and diagnosis. This study presents a new approach of high spatial resolution aerial Red, Green, Blue (RGB) image for BSR detection using a low-altitude remote sensing Unmanned Aerial Vehicle (UAV) platform. The co-occurrence measures for textural analysis were performed to the RGB band to determine the best parameter for BSR detection. Descriptive statistical as well as One way ANOVA were executed to indicate which bands are giving significant level (p<0.05). Apparently, the test gave three significant properties which are Correlation taken from R, G and B band. The developed conditional statement of detection was tested for distinguishing between healthy and BSR-infected trees. Total accuracy acquired for healthy trees was 86.21% whereas for BSR-infected trees was 75.00%. Hence, average accuracy assessment was 80.61%.
format Article
author Bejo, Siti Khairunniza
Jaleni, M.
Husin, M. E.
Khosrokhani, Maryam
Muharam, Farrah Melissa
Abu Seman, Idris
Anuar, Mohamad Izzuddin
spellingShingle Bejo, Siti Khairunniza
Jaleni, M.
Husin, M. E.
Khosrokhani, Maryam
Muharam, Farrah Melissa
Abu Seman, Idris
Anuar, Mohamad Izzuddin
Basal Stem Rot (BSR) detection using iextural inalysis of Unmanned Aerial Vehicle (UAV) image
author_facet Bejo, Siti Khairunniza
Jaleni, M.
Husin, M. E.
Khosrokhani, Maryam
Muharam, Farrah Melissa
Abu Seman, Idris
Anuar, Mohamad Izzuddin
author_sort Bejo, Siti Khairunniza
title Basal Stem Rot (BSR) detection using iextural inalysis of Unmanned Aerial Vehicle (UAV) image
title_short Basal Stem Rot (BSR) detection using iextural inalysis of Unmanned Aerial Vehicle (UAV) image
title_full Basal Stem Rot (BSR) detection using iextural inalysis of Unmanned Aerial Vehicle (UAV) image
title_fullStr Basal Stem Rot (BSR) detection using iextural inalysis of Unmanned Aerial Vehicle (UAV) image
title_full_unstemmed Basal Stem Rot (BSR) detection using iextural inalysis of Unmanned Aerial Vehicle (UAV) image
title_sort basal stem rot (bsr) detection using iextural inalysis of unmanned aerial vehicle (uav) image
publisher Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/53274/1/Methods%20of%20reducing%20the%20fate%20and%20transport%20of%20nutrients%20from%20agricultural%20fields.pdf
http://psasir.upm.edu.my/id/eprint/53274/7/Basal%20Stem%20Rot%20%28BSR%29%20detection%20using%20iextural%20inalysis%20of%20Unmanned%20Aerial%20Vehicle%20%28UAV%29%20image.pdf
http://psasir.upm.edu.my/id/eprint/53274/
http://eproceedings.chemistry.utm.my/index.php/FYP/index
_version_ 1643835359105122304
score 13.211869

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