Agricultural recommendation system for crop protection

Abstract

Pests in crops produce important economic loses all around the world. To deal with them without damaging people or the environment, governments have established strict legislation and norms describing the products and procedures of use. However, since these norms frequently change to reflect scientific and technological advances, it is needed to perform a frequent review of affected norms in order to update pest related information systems. This is not an easy task because they are usually human-oriented, so intensive manual labour is required. To facilitate the use of this information, this work proposes the construction of a recommendation system that facilitates the identification of pests and the selection of suitable treatments. The core of this system is an ontology that models the interactions between crops, pests and treatments.

Recommendation Systems: Algorithms, Challenges, Metrics, and Business Opportunities

“…The authors used an ensemble classifier to suggest crops and evaluated their system using response time and accuracy measures. The issue of pests in crops was addressed and tackled in [74], where the researchers developed a RS that identifies the pests and recommends suitable treatments. In [75], the authors developed a web collaborative-based RS to answer the farmers' inquiries and update them with recent agriculture trends.…”

Extending ONTAgri with Service-Oriented Architecture towards Precision Farming Application

“…Recommendation, decision, and semantic search systems are also developed to overcome the issue of ontology. In [19], the authors proposed the recommendation system based on an ontology model to describe the outbreaks that pests produce to crops and the approved ways to treat and facilitate them. Pests, crops, and their treatment ontologies (PCT-O) are also discussed in this research work, which is an extension of the disease triangle.…”

Review and Trend Analysis of Knowledge Graphs for Crop Pest and Diseases

“…Questions and answers in the field of crop diseases and insect pests are no longer limited to knowledge matching, but also involve determining accurate answers after understanding deeper questions [84]. Lacasta et al [85] combined the strategy of pesticide application, knowledge map, and intelligent question-and-answer to accurately recommend pest and disease application program. In other fields, Chen et al [86] proposed the design and development of an intelligent question answering system for agrotechnical knowledge based on a knowledge atlas, which showed the interrelation of agrotechnical knowledge related to questions through knowledge cards, atlases, and related links; additionally, it improved the knowledge acquisition and enhanced the interactivity.…”