UPM Institutional Repository

Detecting BSR-infected oil palm seedlings using thermal imaging technique


Mohd Johari, Siti Nurul Afiah and Abdol Lajis, Ghaibulna and Keat, Neoh B. and Ithnin, Nalisha and Bejo, Siti Khairunniza and Daim, Leona Daniela Jeffery and Yap, Yun Ci (2021) Detecting BSR-infected oil palm seedlings using thermal imaging technique. Basrah Journal of Agricultural Sciences, 34 (spec.1). 73 - 80. ISSN 1814-5868; ESSN: 2520-0860


Basal Stem Rot (BSR) is the most destructive disease instigated by a white wood rotting fungus called Ganoderma boninense, which cause great economic setback in oil palm productivity. It attacks the basal stem of oil palm trees, causing them to slowly rot. It also affects the xylem tissues that eventually interrupt water transportation to the upper part of the oil palm, turning the leaves at the frond become yellow. This problem should be prevented during nursery stage by separating between healthy and BSR-infected seedling. Therefore, this study focuses on the potential use of thermal imaging for detecting BSR in oil palm at seedling. Thermal images of oil palm seedling from healthy and BSR-infected were captured and processed to extract several thermal properties of the seedling, i.e., maximum, minimum, mean, and standard deviation of pixel intensity value. These values were then undergone statistical analysis to identify its significant different in differentiating healthy and BSR-infected seedling. Several classification models were tested including Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Support Vector Machine (SVM) and k-Nearest Neighbour (kNN). Principal Component Analysis (PCA) was used to reduce the dimensionality of the dataset. The results demonstrated that the highest accuracy achieved at 80.0 % using SVM (fine gaussian) classification model with PC1 and PC3 as the input parameter. This summarizes the potential of thermal imaging in detecting BSR-infected oil palm trees at seedling stage.

Download File

[img] Text (Abstract)

Download (6kB)

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.37077/25200860.2021.34.sp1.8
Publisher: University of Basrah, College of Agriculture
Keywords: BSR; Oil palm; Thermal imaging; Image processing; Machine learning
Depositing User: Ms. Nuraida Ibrahim
Date Deposited: 11 Jan 2023 07:02
Last Modified: 11 Jan 2023 07:02
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.37077/25200860.2021.34.sp1.8
URI: http://psasir.upm.edu.my/id/eprint/96630
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item