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New Insights into Geometric Morphometry Applied to Fish Scales for Species Identification

Authors :
Francesca Traverso
Stefano Aicardi
Matteo Bozzo
Matteo Zinni
Andrea Amaroli
Loris Galli
Simona Candiani
Stefano Vanin
Sara Ferrando
Source :
Animals, Vol 14, Iss 7, p 1090 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The possibility of quick and cheap recognition of a fish species from a single dermal scale would be interesting in a wide range of contexts. The methods of geometric morphometry appear to be quite promising, although wide studies comparing different approaches are lacking. We aimed to apply two methods of geometric morphometry, landmark-based and outline-based, on a dataset of scales from five different teleost species: Danio rerio, Dicentrarchus labrax, Mullus surmuletus, Sardina pilchardus, and Sparus aurata. For the landmark-based method the R library “geomorph” was used. Some issues about landmark selection and positioning were addressed and, for the first time on fish scales, an approach with both landmarks and semilandmarks was set up. For the outline-based method the R library “Momocs” was used. Despite the relatively low number of scales analyzed (from 11 to 81 for each species), both methods achieved quite good clustering of all the species. In particular, the landmark-based method used here gave generally higher R2 values in testing species clustering than the outline-based method, but it failed to distinguish between a few couples of species; on the other hand, the outline-based method seemed to catch the differences among all the couples except one. Larger datasets have the potential to achieve better results with outline-based geometric morphometry. This latter method, being free from the problem of recognizing and positioning landmarks, is also the most suitable for being automatized in future applications.

Details

Language :
English
ISSN :
20762615
Volume :
14
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Animals
Publication Type :
Academic Journal
Accession number :
edsdoj.847d619bbbe04475a95342cdb19f741e
Document Type :
article
Full Text :
https://doi.org/10.3390/ani14071090