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Technologies Applied in the Field of Early Detection of Coffee Rust Fungus Diseases: A Review

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Aroca Trujillo, Jorge Luis
Pérez Ruiz, Alexander
Abstract (English)
This document systematically reviews the technological methods and computer algorithms used to identify coffee leaf rust. This review is based on the PRISMA methodology used over the Scopus and Web of Science scientific literature databases. Initially, there were 1060 articles related to rust, but after using a few selecting criteria, the number of articles selected to do this review was reduced 47 articles. The papers that were selected cover different methodologies and tools: rust detection in various fields, images used in the detection process and algorithms themselves. The scientific novelty of this review lies in the discussion of relevant issues detected in the selected papers related to the techniques provided to detect and quantify the incidence of CLR. Although the number of papers found that address CLR was lower than expected, this disease affects a vital production plant in Colombia, and it is imperative to expand the knowledge found in these papers by developing new methods to identify it early. The research objectives of this review are to summarize the current status of technological methods and computer algorithms for CLR detection, highlight their strengths and weaknesses, and identify gaps and potential opportunities for future research in this field.
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16 p.
URI: https://repositorio.escuelaing.edu.co/handle/001/3428
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