| Issue |
E3S Web Conf.
Volume 232, 2021
International Conference on Agribusiness and Rural Development (IConARD 2020)
|
|
|---|---|---|
| Article Number | 03008 | |
| Number of page(s) | 7 | |
| Section | Agricultural Technology | |
| DOI | https://doi.org/10.1051/e3sconf/202123203008 | |
| Published online | 25 January 2021 | |
Evaluating Multispectral Imaging for Assessing Bacterial Leaf Blight Damage in Indonesian Agricultural Insurance
1 Banten Assessment Institute for Agricultural Technology Indonesian Ministry of Agriculture, Ciruas Serang, Banten 42182, Indonesia
2 Center for Environmental Remote Sensing, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba-shi, Chiba 263-8522, Japan
3 Graduate School of Agricultural Science, Tohoku University, 468-1 Aramaki Aza Aoba, Aoba-ku, Sendai, Miyagi 980-8572, Japan
4 Graduate School of Horticulture, Chiba University, 648 Matsudo, Matsudo-shi, Chiba 271-8510, Japan
5 Faculty of Agriculture Udayana University, Jl. P.B Sudirman Denasar Bali
6 Faculty of Agriculture Engineering Udayana University, Jl. P.B Sudirman Denpasar Bali
* Corresponding author: yuti.giamerti@gmail.com
Bacterial Leaf Blight (BLB) is one of the main diseases in Indonesia that causes a 90% reduction in grain weight. Multispectral imaging may be used as a quick and effective method for damage assessment and is expected to utilize on agricultural insurance in Indonesia. Data were collected at the rainy season and dry season 2018 in Farmers rice field at Bali Province. Vegetation indices (NDVI, GNDVI, and VARIred-edge) was analyzed using QGIS 2.18 from multispectral images. Some vegetation index shows positive correlation with SPAD and negative correlation with DSI (%). VARIred-edge has a higher relationship with DSI (R2: 0.8443) than NDVI (R2: 0.8291) and GNDVI (R2: 0.5463) at the average value on each location, but the relation seems to be affected by that relation between SPAD and LAI. Further data and analysis are required.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.