INVARIANT CORRELATION WITH SPECIES-SPECIFIC COMPOSITE FILTERS FOR THE RECOGNITION OF TRICHODINIDS (CILIOPHORA: PERITRICHIDA) PARASITIZING OREOCHROMIS NILOTICUS (LINNAEUS, 1758) BASED ON MORPHOLOGICAL METHODS

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Trichodinids are the most common ectoparasites of both freshwater and marine fishes. Their generic identification is relatively easy, while the specific diagnosis is laborious due to the high intraspecific variability of some species. Four species of the genus Trichodina from the skin and fins of Or...

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Detalles Bibliográficos
Autores: Rodríguez-Santiago, Maria Amparo, Álvarez-Borrego, Josué, Fajer-Ávila, Emma Josefina, Iannacone Oliver, José Alberto, Fernandez-Martínez, Cynthia Nayeli
Formato: artículo
Fecha de Publicación:2021
Institución:Universidad Nacional Federico Villarreal
Repositorio:Revistas - Universidad Nacional Federico Villarreal
Lenguaje:español
OAI Identifier:oai:ojs2.revistas.unfv.edu.pe:article/1223
Enlace del recurso:https://revistas.unfv.edu.pe/NH/article/view/1223
Nivel de acceso:acceso abierto
Materia:Trichodina
Oreochromis niloticus
taxonomy
automatic systems
invariant correlation
taxonomía
sistemas automáticos
correlación invariante
Descripción
Sumario:Trichodinids are the most common ectoparasites of both freshwater and marine fishes. Their generic identification is relatively easy, while the specific diagnosis is laborious due to the high intraspecific variability of some species. Four species of the genus Trichodina from the skin and fins of Oreochromis niloticus (Linnaeus, 1758) Egyptian black variety were identified by means of morphological methods and the use of digital correlation invariant to position, rotation and scale by species specific composite filters. Trichodina magna Van As Bassson, 1989 and Trichodina nigra Lom, 1961 represent new records of host and geographic location, while Trichodina centrostrigata Van As, Basson & Van As, 1998 and Trichodina heterodentata Duncan, 1977, have already been reported for O. niloticus in Mexico. The automatic identification of the four species studied was done through the development and application of a mathematical algorithm within a recognition process of objects (invariant digital correlation), based on the frequency contents of the parasite species. This algorithm essential characteristic is its use to recognize the object in spite of the fact that its location level has changes of position, rotation and scale.
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