RustOnt: An Ontology to Explain Weather Favorable Conditions of the Coffee Rust

Abstract

Crop disease management in smart agriculture involves applying and using new technologies to reduce the impact of diseases on the quality of products. Coffee rust is a disease that factors such as poor agronomic management activities and climate conditions may favor. Therefore, it is crucial to identify the relationships between these factors and this disease to learn how to face its consequences and build intelligent systems to provide appropriate management or help farmers and experts make decisions accordingly. Nevertheless, there are no studies in the literature that propose ontologies to model these factors and coffee rust. This paper presents a new ontology called RustOnt to help experts more accurately model data, expressions, and samples related to coffee rust and apply it whilst taking into account the geographical location where the ontology is adopted. Consequently, this ontology is crucial for coffee rust monitoring and management by means of smart agriculture systems. RustOnt was successfully evaluated considering quality criteria such as clarity, consistency, modularity, and competence against a set of initial requirements for which it was built.

A Qualitative Dataset for Coffee Bio-Aggressors Detection Based on the Ancestral Knowledge of the Cauca Coffee Farmers in Colombia

“…The most damaging coffee pests are coffee rust (Hemileia vastatrix), Coffee Berry Borer (CBB) (Hypothenemus hampei), and coffee spot (Cercospora coffeicola). These pests cause lesions on leaves and fruits, reducing coffee yields [6,7].…”

“…3200 ha), which are still vulnerable [8]. Coffee rust affects 28.5% of these regions with susceptible varieties [7,9], while coffee berry borer and brown-eye spots affect 5.0% and 4.8%, respectively, of the coffee crops [10]. Furthermore, climatic conditions, cultivation practices, and the local landscape contribute to the outbreaks of these pests [11][12][13].…”

An Ontological Model for the Representation of Vallenato as Cultural Heritage in a Context-Aware System

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