Chapter 14 - Artificial intelligence-based detection and counting of olive fruit flies: A comprehensive survey

Abstract

The olive fruit fly is considered a major threat for olive fruits and may cause damage to up to 100% of the harvested fruit. Olive fruit fly control falls under the generic topic of integrated pest management (IPM). Identifying the presence and the count of the olive fruit fly in time allows IPM to infer the best treatment strategy to be followed to prevent the pest from damaging the crop. This not only protects the crop yield but also increases the quality of the olive crop and, consequently, the quality of the resulting products, such as olive oil. In this chapter, we present a comprehensive survey of the literature of pest recognition technologies with emphasis on the detection and counting of the olive fruit fly using artificial intelligence techniques. We broadly classify existing pest recognition and counting techniques into manual, semiautomatic, and automatic detection and counting. We further categorize the automatic detection and counting based on the used technology into machine learning-based, deep learning-based, image processing-based, optoacoustic spectrum-based, and hyperspectral spectroscopy-based schemes.