TACO: An Ontology in Turkish for Identifying and Controlling Plant Pests, Weeds and Diseases

Abstract

While ensuring a more sustainable production, because of reduced chemical usage it is more complicated to control plant pests, diseases and weeds in smart agriculture. For this reason, it is of great importance to detect pests, diseases and weeds at the earliest stage. It is important that both farmers and the artificial intelligence applications developed for agricultural control should be able to detect these organisms and to know the agricultural control methods. Semantic technologies and ontologies provide machine interpretable information and solutions for heterogeneity. This study presents the Turkish Agricultural Control Ontology (TACO), which is built in Turkish and contains information about plant pests, diseases and weeds common in Turkey. The contributions of the study are that it is the first Turkish ontology built in this field and that the methods of agricultural control are included within the scope of the ontology. According to the commonly used ontology evaluation metrics, TACO is predominantly characterized as a deep classification taxonomy. In addition, it was concluded that the classes in the ontology have an evenly distributed and sufficient number of class individuals.