Rubber leaf blight disease detection using multispectral sensor in rural and urban area / Nur Adrianna Mat Ariffin

Mat Ariffin, Nur Adrianna (2020) Rubber leaf blight disease detection using multispectral sensor in rural and urban area / Nur Adrianna Mat Ariffin. Degree thesis, Universiti Teknologi MARA (UiTM).


Agricultural productivity is the thing that Malaysia highly relies on economically. That is one of the reasons why plant disease identification plays an important role in the field of agriculture because it is basically to have a disease in plants. Detection of plant disease by using a spectroradiometer instrument is helpful because it decreases huge monitoring in huge crop farms and detects the signs of the disease means at very early stages as they occur on plant leaves. The technique used for spectroradiometer detection as well as classification of plant leaf diseases and surveys on different disease classification techniques that can be used for plant leaf disease detection. The specific objective is to identify the spectral signature characteristics of healthy (control) and "unhealthy" or stressed rubber trees due to leaf diseases as causal factors. The spectral reflectance of each infected rubber tree was separated according to the different wavelength and percent reflectance. The spectral signatures of rubber trees being attacked by diseases were characterized by a low reflectance probably due to the low chlorophyll content in the leaves leading to the tree under stress, thus easily separated from the healthy rubber. Results indicated that some groups of infected trees were well separated at the 530 - 650 nm (visible) wavelength reflectance. The spectral reflectance of rubber trees with leaf disease in visible (VIS) wavelength was not consistently separable. However, the spectral reflectance of leaf diseases can be well separated at the near-infrared range region covering from 700 - 850 nm wavelength reflectance for leaf diseases, respectively. The study implies that leaf diseases for rubber trees can only be identified successfully at the NIR range of wavelength from 700 - 850 nm reflectance.


Item Type: Thesis (Degree)
Email / ID Num.
Mat Ariffin, Nur Adrianna
Email / ID Num.
Thesis advisor
Hashim, Nurhanisah
Subjects: Q Science > QA Mathematics > Geometry. Trigonometry. Topology
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Architecture, Planning and Surveying
Programme: Bachelor Surveying Science and Geomatics (Honours)
Keywords: Rubber, agricultural productivity, spectral reflectance
Date: 2020
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