TY - JOUR
T1 - Evaluating Multispectral Imaging for Assessing Bacterial Leaf Blight Damage in Indonesian Agricultural Insurance
AU - Giamerti, Yuti
AU - Hongo, Chiharu
AU - Saito, Daiki
AU - Caasi, Oliver
AU - Nur Susilawati, Pepi
AU - Shishido, Masahiro
AU - Sudiarta, I. Putu
AU - Sutrisna Wijaya, I. Made Anom
AU - Homma, Koki
N1 - Publisher Copyright:
© The Authors, published by EDP Sciences, 2021.
PY - 2021/1/25
Y1 - 2021/1/25
N2 - 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.
AB - 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.
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U2 - 10.1051/e3sconf/202123203008
DO - 10.1051/e3sconf/202123203008
M3 - Conference article
AN - SCOPUS:85100433685
SN - 2267-1242
VL - 232
JO - E3S Web of Conferences
JF - E3S Web of Conferences
M1 - 03008
T2 - 2020 International Conference on Agribusiness and Rural Development, IConARD 2020
Y2 - 13 October 2020 through 14 October 2020
ER -