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

Wikantika, Ketut and Ghazali, Mochamad Firman and Dwivany, Fenny M. and Susantoro, Tri Muji and Yayusman, Lissa Fajri and Sunarwati, Diah and Sutanto, Agus (2023) 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, 15 (10). p. 1046. ISSN 1424-2818

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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.

Item Type: Article
Uncontrolled Keywords: banana diseases; banana blood disease (BBD); fusarium wilt; random forest; spatial distribution; multispectral images; spectral analysis
Subjects: Agriculture & Food > Agronomy, Horticulture, & Plant Pathology
Depositing User: Maria Regina
Date Deposited: 14 Dec 2025 18:53
Last Modified: 14 Dec 2025 18:53
URI: https://karya.brin.go.id/id/eprint/56344

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