TRsandflies: A Web-Based Software for the Morphometric Identification of Sand Flies in Turkey


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Kavur H.

Journal Of Medical Entomology, vol.58, no.3, pp.1149-1156, 2021 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 58 Issue: 3
  • Publication Date: 2021
  • Doi Number: 10.1093/jme/tjaa275
  • Journal Name: Journal Of Medical Entomology
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Animal Behavior Abstracts, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, EMBASE, Environment Index, Food Science & Technology Abstracts, MEDLINE, Veterinary Science Database
  • Page Numbers: pp.1149-1156
  • Keywords: TRsandflies, sand flies, identification, C#, MYSQL, PHLEBOTOMINE SANDFLIES DIPTERA, PSYCHODIDAE, LEISHMANIASIS
  • Çukurova University Affiliated: Yes

Abstract

Sand flies are vector of several diseases, mostly cutaneous and visceral leishmaniasis (CL and VL). Also, 29 sand fly species have been identified in previous fauna studies carried out in 40 provinces of Turkey. Totally, 24 sand flies species belonging to Phlebotomus (Ph.) (Diptera: Psychodidae) genus have been proven or reported as possible vector species. This study aimed to develop a new software which could contribute  to researchers’ decision making about the identification of sand flies with obtained data from entomological surveys conducted before in Turkey. Developed software called TRsandflies included 35 textbox created with parameters obtained from caught sand flies specimens by the above-mentioned surveys. It also contained 130 photos and distribution maps related to 24 sand flies species. In addition, C# language and MYSQL database were used in the program. TRsandflies had three different forms (pages) allowing the user to compare the specimens and known species. In the species identification trials with three repetitions carried out in the program, except for the specimens belonging to the Transphlebotomus Artemiev & Neronov, 1984 subgenus, morphometric data of all previously collected sand fly species specimens were included. The process of running the morphometric measurement results of predetermined specimens in the program provided us with an accurate prediction rate of 86.66% in male specimens and 71.66% in female specimens. We concluded that the web-based software developed could play an important role in reducing the rate of possible errors that might be encountered by conventional identification methods.