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A Study on the Distribution Pattern of Banana Blood Diseases (BDB) and Fusarium Wilt Using Multispectral Aerial Photo and Handheld Spectrometer in Subang-Indonesia
Wikantika, K.; Ghazali, M.F.; Dwivany, F.M.; Susantoro, T.M.; Fajri, L.N.; Sunarwati, D.; Sutanto, A. A Study on the Distribution Pattern of Banana Blood Disease (BBD) and Fusarium Wilt Using Multispectral Aerial Photos and a Handheld Spectrometer in Subang, Indonesia. Diversity2023, 15, 1046.
Wikantika, K.; Ghazali, M.F.; Dwivany, F.M.; Susantoro, T.M.; Fajri, L.N.; Sunarwati, D.; Sutanto, A. A Study on the Distribution Pattern of Banana Blood Disease (BBD) and Fusarium Wilt Using Multispectral Aerial Photos and a Handheld Spectrometer in Subang, Indonesia. Diversity 2023, 15, 1046.
Wikantika, K.; Ghazali, M.F.; Dwivany, F.M.; Susantoro, T.M.; Fajri, L.N.; Sunarwati, D.; Sutanto, A. A Study on the Distribution Pattern of Banana Blood Disease (BBD) and Fusarium Wilt Using Multispectral Aerial Photos and a Handheld Spectrometer in Subang, Indonesia. Diversity2023, 15, 1046.
Wikantika, K.; Ghazali, M.F.; Dwivany, F.M.; Susantoro, T.M.; Fajri, L.N.; Sunarwati, D.; Sutanto, A. A Study on the Distribution Pattern of Banana Blood Disease (BBD) and Fusarium Wilt Using Multispectral Aerial Photos and a Handheld Spectrometer in Subang, Indonesia. Diversity 2023, 15, 1046.
Abstract
Knowledge on the health of banana trees is critical for farmers to profit from banana cultivation. Fusarium wilt and banana blood diseases (BDB), two significant diseases infecting banana trees, are caused by Fusarium oxysporum and Ralstonia syzygii, respectively. They have successfully caused a decline in crop yield as they destroy the trees, starting sequentially from the pseudostem to the fruits. The entire distribution of BDB and Fusarium on a plantation can be understood using advanced geospatial information obtained from multispectral aerial photographs taken using an unmanned aerial vehicle (UAV), combined with the reliable data field of infected trees. Vegetation and soil indices derived from a multispectral aerial photograph, such as normalized difference vegetation index, modified chlorophyll absorption ratio index, normalized difference water index (NDWI) and soil pH, may have to be relied on to explain the precise location of these two diseases. In this study, a random forest algorithm was used to handle a large dataset consisting of two models: the banana diseases multispectral model and the banana diseases spectral model. The results show that the soil indices, soil pH and NDWI are the most important variables for predicting the spatial distribution of these two diseases. Simultaneously, the plantation area affected by BDB is more extensive than that affected by Fusarium, if the variation of planted banana cultivars is not considered.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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