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BananaLSD: A banana leaf images dataset for classification of banana leaf diseases using machine learning

2023; Elsevier BV; Volume: 50; Linguagem: Inglês

10.1016/j.dib.2023.109608

2352-3409

Shifat E. Arman, Md. Abdullahil Baki Bhuiyan, Hasan Muhammad Abdullah, Shariful Islam, T Chowdhury, Md. Arban Hossain,

Phytoplasmas and Hemiptera pathogens

Bananas, one of the most widely consumed fruits globally, are highly susceptible to various leaf spot diseases, leading to significant economic losses in banana production. In this article, we present the Banana Leaf Spot Diseases (BananaLSD) dataset, an extensive collection of images showcasing three prevalent diseases affecting banana leaves: Sigatoka, Cordana, and Pestalotiopsis. The dataset was used to develop the BananaSqueezeNet model [1]. The BananaLSD dataset contains 937 images of banana leaves collected from banana fields, which were then further augmented to generate another 1600 images. The images were acquired using three smartphone cameras in diverse real-world conditions. The dataset has potential for reuse in the development of machine learning models that can help farmers identify symptoms early. It can be useful for researchers working on leaf spot diseases and serve as motivation for further researches.