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Comprehensive Mosquito Wing Image Repository for Advancing Research on Geometric Morphometric- and AI-Based Identification

Accurate identification of mosquito species is essential for effective vector control and mitigation of mosquito-borne disease outbreaks. Traditional morphological identification requires highly specialized personnel and is time-consuming, while molecular techniques can be cost-effective and depende...

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Bibliographische Detailangaben
Hauptverfasser: Nolte, Kristopher (VerfasserIn) , Agboli, Eric (VerfasserIn) , Garcia, Gabriela Azambuja (VerfasserIn) , Badolo, Athanase (VerfasserIn) , Becker, Norbert (VerfasserIn) , Loc, Do Huy (VerfasserIn) , Dworrak, Tarja Viviane (VerfasserIn) , Eguchi, Jacqueline (VerfasserIn) , Eisenbarth, Albert (VerfasserIn) , de Freitas, Rafael Maciel (VerfasserIn) , Doumna-Ndalembouly, Ange Gatien (VerfasserIn) , Heitmann, Anna (VerfasserIn) , Jansen, Stephanie (VerfasserIn) , Jöst, Artur (VerfasserIn) , Jöst, Hanna (VerfasserIn) , Kiel, Ellen (VerfasserIn) , Meyer, Alexandra (VerfasserIn) , Pfitzner, Wolf-Peter (VerfasserIn) , Saathoff, Joy (VerfasserIn) , Schmidt-Chanasit, Jonas (VerfasserIn) , Sulesco, Tatiana (VerfasserIn) , Tokatlian, Artin (VerfasserIn) , Velavan, Thirumalaisamy P. (VerfasserIn) , Villacañas de Castro, Carmen (VerfasserIn) , Wehmeyer, Magdalena Laura (VerfasserIn) , Zahouli, Julien (VerfasserIn) , Sauer, Felix Gregor (VerfasserIn) , Lühken, Renke (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 29 April 2025
In: Scientific data
Year: 2025, Jahrgang: 12, Heft: 1, Pages: 1-6
ISSN:2052-4463
DOI:10.1038/s41597-025-05043-3
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s41597-025-05043-3
Verlag, kostenfrei, Volltext: https://www.nature.com/articles/s41597-025-05043-3
Volltext
Verfasserangaben:Kristopher Nolte, Eric Agboli, Gabriela Azambuja Garcia, Athanase Badolo, Norbert Becker, Do Huy Loc, Tarja Viviane Dworrak, Jacqueline Eguchi, Albert Eisenbarth, Rafael Maciel de Freitas, Ange Gatien Doumna-Ndalembouly, Anna Heitmann, Stephanie Jansen, Artur Jöst, Hanna Jöst, Ellen Kiel, Alexandra Meyer, Wolf-Peter Pfitzner, Joy Saathoff, Jonas Schmidt-Chanasit, Tatiana Sulesco, Artin Tokatlian, Thirumalaisamy P. Velavan, Carmen Villacañas de Castro, Magdalena Laura Wehmeyer, Julien Zahouli, Felix Gregor Sauer & Renke Lühken
Beschreibung
Zusammenfassung:Accurate identification of mosquito species is essential for effective vector control and mitigation of mosquito-borne disease outbreaks. Traditional morphological identification requires highly specialized personnel and is time-consuming, while molecular techniques can be cost-effective and dependent on comprehensive genetic information. Wing geometric morphometry has emerged as a promising alternative, leveraging detailed geometric measurements of wing shapes and vein patterns to distinguish between species and detect intraspecies variations. This paper presents a curated dataset of 18,104 mosquito wing images, collected from 10,500 mosquito specimens, annotated with extensive meta-information, designed to support research in wing geometric morphometry and the development of machine learning models, ultimately supporting efforts in vector surveillance and research.
Beschreibung:Gesehen am 07.11.2025
Beschreibung:Online Resource
ISSN:2052-4463
DOI:10.1038/s41597-025-05043-3

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