A dataset of sandfly (Phlebotomus papatasi, Phlebotomus alexandri, and Phlebotomus sergenti) genital and pharyngeal imagesMendeley Data

• Published in: Data in Brief
• Main Authors: Mohammad Fraiwan, Rami Mukbel, Dania Kanaan
• Format: Article
• Language: English
• Published: Elsevier 2024-12-01
• Subjects: Artificial intelligence; Sexing; Sandfly; Classification; Taxonomy; Entomology
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352340924009934

Sandflies serve as carriers for numerous tropical diseases, including leishmaniasis, bartonellosis, and sandfly fever. Furthermore, sandflies are species-specific when it comes to transmitting corresponding pathogen species. Hence, accurate classification and identification of sandfly species and gender are essential for various purposes such as disease monitoring and control, population management, research and development, and epidemiological investigations. Most of the sexing and taxonomy keys are based on internal morphological features, which may lead to errors due to some features being missed by the naked eye. In this paper, we describe the process we used to collect and prepare samples of three sandfly species (Ph. alexandri, Ph. papatasi, and Ph. sergenti). The dataset described in this article contains two images per sample, representing the pharynx in the head and the genitalia in the abdomen. The dataset is organized into male and female categories for each of the three species. The sex and species were determined manually by two specialists. This dataset can be used to develop automated methods for sex identification and taxonomy. Additionally, it can be used to train students in speciation and taxonomy. To the best of our knowledge, this is the first publicly available dataset of images of this kind.