Rubber-tree leaf diseases mapping using close range remote sensing images
Currently, close-range remote sensing method using drone-based platform which payload compact sensor has been used for monitoring and mapping in the agriculture sector at large area. Thus, this study is deployed drone with a compact sensor to identify the rubber tree leaf diseases based on two group...
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Penerbit UTHM
2022
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| author | Rasib, Abd. Wahid Abd. Hamid, Nurmi-Rohayu Mohd. Yaacob, Muhammad Latifi Abd. Ghani, Zarawi Idris, Nurul Hawani Alvin, L. M. S. Hassan, Muhammad Imzan M. Idris, Khairulnizam Dollah, Rozilawati Mohd. Salleh, Anuar Ahmad, Mustaffa Anjang |
| author_facet | Rasib, Abd. Wahid Abd. Hamid, Nurmi-Rohayu Mohd. Yaacob, Muhammad Latifi Abd. Ghani, Zarawi Idris, Nurul Hawani Alvin, L. M. S. Hassan, Muhammad Imzan M. Idris, Khairulnizam Dollah, Rozilawati Mohd. Salleh, Anuar Ahmad, Mustaffa Anjang |
| author_sort | Rasib, Abd. Wahid |
| collection | ePrints |
| description | Currently, close-range remote sensing method using drone-based platform which payload compact sensor has been used for monitoring and mapping in the agriculture sector at large area. Thus, this study is deployed drone with a compact sensor to identify the rubber tree leaf diseases based on two groups of a spectral wavelength which are visible (RGB: 0.4 μm – 0.7 μm) and near infrared (NIR: 0.7μm – 2.0 μm), respectively. Spectral obtained from drone-based platform will be validated using ground observation handheld spectroradiometer. Eight types of rubber tree clones leaf at three different conditions (healthy, unhealthy and severe) were randomly selected within the 9.4-hectare experimental rubber plot, Rubber Research Institute of Malaysia (RRIM), Kota Tinggi, Johor whereby consist RRIM 2000 series, RRIM 3000 series, and PB series, respectively. Based on the result, quantitative analysis shows that the f-value is smaller than Critical-one tail for healthy, unhealthy while for severe the f-value is larger than Critical-one tail. The f-value is 2.887 < 4.283 (healthy), 0.002 < 0.264 (unhealthy) and 1.008 > 0.0526, respectively. Thus, this can be concluded that spectral and estimate is equal at the 0.05 significant levels. While qualitative analysis shows that each rubber clone tree diseases can be distinguished at the near infrared band for healthy, unhealthy, and severe, respectively. |
| first_indexed | 2024-03-05T21:21:17Z |
| format | Article |
| id | utm.eprints-101328 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T21:21:17Z |
| publishDate | 2022 |
| publisher | Penerbit UTHM |
| record_format | dspace |
| spelling | utm.eprints-1013282023-06-08T09:03:40Z http://eprints.utm.my/101328/ Rubber-tree leaf diseases mapping using close range remote sensing images Rasib, Abd. Wahid Abd. Hamid, Nurmi-Rohayu Mohd. Yaacob, Muhammad Latifi Abd. Ghani, Zarawi Idris, Nurul Hawani Alvin, L. M. S. Hassan, Muhammad Imzan M. Idris, Khairulnizam Dollah, Rozilawati Mohd. Salleh, Anuar Ahmad, Mustaffa Anjang G70.39-70.6 Remote sensing Currently, close-range remote sensing method using drone-based platform which payload compact sensor has been used for monitoring and mapping in the agriculture sector at large area. Thus, this study is deployed drone with a compact sensor to identify the rubber tree leaf diseases based on two groups of a spectral wavelength which are visible (RGB: 0.4 μm – 0.7 μm) and near infrared (NIR: 0.7μm – 2.0 μm), respectively. Spectral obtained from drone-based platform will be validated using ground observation handheld spectroradiometer. Eight types of rubber tree clones leaf at three different conditions (healthy, unhealthy and severe) were randomly selected within the 9.4-hectare experimental rubber plot, Rubber Research Institute of Malaysia (RRIM), Kota Tinggi, Johor whereby consist RRIM 2000 series, RRIM 3000 series, and PB series, respectively. Based on the result, quantitative analysis shows that the f-value is smaller than Critical-one tail for healthy, unhealthy while for severe the f-value is larger than Critical-one tail. The f-value is 2.887 < 4.283 (healthy), 0.002 < 0.264 (unhealthy) and 1.008 > 0.0526, respectively. Thus, this can be concluded that spectral and estimate is equal at the 0.05 significant levels. While qualitative analysis shows that each rubber clone tree diseases can be distinguished at the near infrared band for healthy, unhealthy, and severe, respectively. Penerbit UTHM 2022 Article PeerReviewed Rasib, Abd. Wahid and Abd. Hamid, Nurmi-Rohayu and Mohd. Yaacob, Muhammad Latifi and Abd. Ghani, Zarawi and Idris, Nurul Hawani and Alvin, L. M. S. and Hassan, Muhammad Imzan and M. Idris, Khairulnizam and Dollah, Rozilawati and Mohd. Salleh, Anuar and Ahmad, Mustaffa Anjang (2022) Rubber-tree leaf diseases mapping using close range remote sensing images. International Journal of Integrated Engineering, 14 (5). pp. 1-12. ISSN 2229-838X http://dx.doi.org/10.30880/ijie.2022.14.05.001 DOI: 10.30880/ijie.2022.14.05.001 |
| spellingShingle | G70.39-70.6 Remote sensing Rasib, Abd. Wahid Abd. Hamid, Nurmi-Rohayu Mohd. Yaacob, Muhammad Latifi Abd. Ghani, Zarawi Idris, Nurul Hawani Alvin, L. M. S. Hassan, Muhammad Imzan M. Idris, Khairulnizam Dollah, Rozilawati Mohd. Salleh, Anuar Ahmad, Mustaffa Anjang Rubber-tree leaf diseases mapping using close range remote sensing images |
| title | Rubber-tree leaf diseases mapping using close range remote sensing images |
| title_full | Rubber-tree leaf diseases mapping using close range remote sensing images |
| title_fullStr | Rubber-tree leaf diseases mapping using close range remote sensing images |
| title_full_unstemmed | Rubber-tree leaf diseases mapping using close range remote sensing images |
| title_short | Rubber-tree leaf diseases mapping using close range remote sensing images |
| title_sort | rubber tree leaf diseases mapping using close range remote sensing images |
| topic | G70.39-70.6 Remote sensing |
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