Technologies Applied in the Field of Early Detection of Coffee Rust Fungus Diseases: A Review - Aroca Trujillo, Jorge Luis; Pérez Ruiz, Alexander (My University, 2023)
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.

本文系统地回顾了用于识别咖啡叶锈病的技术方法和计算机算法。本综述基于斯科普斯和科学网 科学文献数据库中使用的棱镜方法。最初，有1060篇与锈相关的文章，但在使用一些选择标准后 ，选择进行本次审查的文章数量减少了47篇。入选的论文涵盖了不同的方法和工具：各个领域的 锈迹检测、检测过程中使用的图像以及算法本身。本综述的科学新颖性在于对所选论文中检测到 的与检测和量化CLR发生率的技术相关的相关问题进行了讨论。尽管发现解决CLR的论文数量低 于预期，但这种疾病影响着哥伦比亚的一个重要生产工厂，因此必须通过开发新的方法来及早识 别它，从而扩大这些论文中发现的知识。本综述的研究目的是总结CLR检测的技术方法和计算机 算法的现状，突出其优缺点，并找出该领域未来研究的差距和潜在机会。 关键词：咖啡锈； 裁剪图像； 算法； 检测； 分类
Digital
Keywords: Roya del cafeto; Coffee leaf rust; Tecnología agrícola; Sistemas agrícolas; Agricultural systems; coffee rust; crop images; algorithms; detection; classification