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Big Data Visualization for Black Sigatoka Disease of Bananas and Pathogen–Host Interactions (PHI) of Other Plants

Big Data Visualization for Black Sigatoka Disease of Bananas and Pathogen–Host Interactions (PHI) of Other Plants
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Author(s): Richard S. Segall (Arkansas State University, USA), Soichiro Takahashi (Arkanas State University, USA)and Prasanna Rajbhandari (Arkansas State University, USA)
Copyright: 2024
Volume: 13
Issue: 1
Pages: 22
Source title: International Journal of Applied Research in Bioinformatics (IJARB)
Editor(s)-in-Chief: Heba Mohamed Afify (Biomedical Engineering Department, Cairo University, Egypt)
DOI: 10.4018/IJARB.361940

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Abstract

Black sigatoka is a leaf spot disease affecting banana plants that has caused significant yield reductions of up to 50% (Arman et al., 2023). This research presents data visualizations of 8,761 data points related to black sigatoka in banana plants, encompassing attributes such as time, canopy temperature, and relative humidity. The paper also reviews related work, including the application of data mining to plant studies, the use of deep learning neural networks for plant disease data, and the use of machine learning for predicting crop yields and detecting disease. Additionally, it presents big data visualizations for 20,952 values obtained from the web-accessible Pathogen–Host Interactions database (PHI-base), covering various plant disease categories and providing an epidemiological analysis of prevalent causative agents in specific plant diseases.

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