Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee
Oidium Leaf Disease is one of the most infected rubber leaf disease in Malaysia. A severe outbreak of this disease may cause an annual yield loss with 20% decrement of latex production in a rubber plantation. Recent technology using unmanned aerial vehicle (UAV) has potential to provide cost effecti...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2020
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| Online Access: | https://ir.uitm.edu.my/id/eprint/28861/1/TD_NURUL%20IRAFATIN%20ROSLEE%20AP%20R%2019_5.pdf |
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| Summary: | Oidium Leaf Disease is one of the most infected rubber leaf disease in Malaysia. A severe outbreak of this disease may cause an annual yield loss with 20% decrement of latex production in a rubber plantation. Recent technology using unmanned aerial vehicle (UAV) has potential to provide cost effective data acquisition for the estimation of rubber leaf disease such as Oidium Disease. The UAV is able to facilitate spatially and allow temporal flexible data acquisition using a compact camera payload. Thus, the aim of this study is to assess drone-based multispectral images for Oidium disease on rubber leaves using spectroradiometer. This study is carried out at Experimental Rubber Plot, Research Station Malaysian Rubber Board, Kota Tinggi, Johor. The map of Oidium Disease severity index level is generated by using Support Vector Machine (SVM) Classification. From the severity index level in the map, Oidium Disease was identified by low absorption of light at the red band (0.02) and medium absorption at near-infrared band (0.32). The level of absorption from the results indicates that the leaves have less chlorophyll since it was very severely infected with Oidium Disease. The finding of this study shows that low-cost remote sensing technology which deploys the UAV and digital compact camera is potentially can be used to determine the condition of rubber tree caused by leaves disease. |
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