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

Author:

Wikantika Ketut12,Ghazali Mochamad Firman23ORCID,Dwivany Fenny M.24ORCID,Susantoro Tri Muji25,Yayusman Lissa Fajri2,Sunarwati Diah6,Sutanto Agus7

Affiliation:

1. Department of Geodesy and Geomatics Engineering, Faculty of Earth Sciences and Technology, Bandung Institute of Technology, Bandung 40132, Indonesia

2. Center for Remote Sensing, Bandung Institute of Technology, Bandung 40132, Indonesia

3. Faculty of Engineering, Lampung University, Bandar Lampung 35145, Indonesia

4. School of Life and Sciences and Technology, Bandung Institute of Technology, Bandung 40132, Indonesia

5. Research Center for Remote Sensing—The Research Organization for Aeronautics and Space, Kompleks Cibinong Science Center—BRIN, Jalan Raya Bogor KM. 46, Cibinong 16911, Jawa Barat, Indonesia

6. Badan Standardisasi Instrumen Pertanian, Kementerian Pertanian-Malang 65152, Indonesia

7. Pusat Riset Hortikultura and Perkebunan, National Research and Innovation Agency, Bogor 16915, Indonesia

Abstract

Knowledge of the health of banana trees is critical for farmers in order to profit from banana cultivation. Fusarium wilt and banana blood disease (BBD), two significant diseases that infect banana trees, are caused by Fusarium oxysporum and Ralstonia syzygii, respectively. They have caused a decline in crop yield, as they destroy trees, starting sequentially from the pseudostem to the fruit. The entire distribution of BBD and fusarium on a plantation can be understood using advanced geospatial information obtained from multispectral aerial photographs taken using unmanned aerial vehicles (UAVs) and a reliable data field for infected trees. Vegetation and soil indices derived from multispectral aerial photographs, such as the normalized difference vegetation index, the modified chlorophyll absorption ratio index, the normalized difference water index (NDWI), and soil pH, may have to be relied upon to explain the precise location of these two diseases. This study used a random forest algorithm to handle a large dataset consisting of multispectral and spectral models. 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 BBD is more extensive than that affected by fusarium if variations in planted banana cultivars are not considered.

Funder

Lembaga Pengembangan Ilmu dan Teknologi, Institut Teknologi Bandung

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Agricultural and Biological Sciences (miscellaneous),Ecological Modeling,Ecology

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