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.project "System based on knowledge engineering for the agroecological management of coffee rust", grant 823-Formation of high-level human capital for the regions-Cauc
