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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| Format: | Thesis |
| Language: | English |
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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 |
| _version_ | 1825736921461030912 |
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| author | Roslee, Nurul Irafatin |
| author_facet | Roslee, Nurul Irafatin |
| author_sort | Roslee, Nurul Irafatin |
| collection | UITM |
| description | 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. |
| first_indexed | 2024-03-06T02:10:12Z |
| format | Thesis |
| id | uitm.eprints-8861 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T02:10:12Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | uitm.eprints-88612020-03-26T04:43:53Z https://ir.uitm.edu.my/id/eprint/28861/ Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee Roslee, Nurul Irafatin Geographic information systems Geometry. Trigonometry. Topology 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. 2020-03-16 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/28861/1/TD_NURUL%20IRAFATIN%20ROSLEE%20AP%20R%2019_5.pdf Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee. (2020) Degree thesis, thesis, Universiti Teknologi Mara Perlis. <http://terminalib.uitm.edu.my/28861.pdf> |
| spellingShingle | Geographic information systems Geometry. Trigonometry. Topology Roslee, Nurul Irafatin Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee |
| title | Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee |
| title_full | Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee |
| title_fullStr | Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee |
| title_full_unstemmed | Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee |
| title_short | Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee |
| title_sort | assesment of oidium disease on rubber leaves by drone based multispectral image nurul irafatin roslee |
| topic | Geographic information systems Geometry. Trigonometry. Topology |
| url | https://ir.uitm.edu.my/id/eprint/28861/1/TD_NURUL%20IRAFATIN%20ROSLEE%20AP%20R%2019_5.pdf |
| work_keys_str_mv | AT rosleenurulirafatin assesmentofoidiumdiseaseonrubberleavesbydronebasedmultispectralimagenurulirafatinroslee |