RESUMEN
Oenanthe L. is a taxonomically complex genus, several species of which have long been used as vegetables and traditional medicines in East Asia. In order to clarify the taxonomic status of Oenanthe accessions and provide baseline data for the sustainable use of its genetic resources, we examined sequence variations in the internal transcribed spacer (ITS) region of Oenanthe accessions collected from a wide geographical area in China and its neighboring countries. For comparison, ITS sequences in GenBank for almost all currently reported species of Oenanthe were also included in our analyses. Both phylogenetic tree construction methods (Bayesian inference and maximum likelihood) revealed that the accessions tended to cluster into two groups, which were closely related to O. mildbraedii and O. sarmentosa. However, these two species have never been recorded in China or its neighboring countries. Therefore, it seems probable that in our sampled locations, Oenanthe accessions have been given an incorrect name, such as O. javanica. Future studies should carefully check the morphological characteristics of other Oenanthe species and sequence their ITS regions in order to clarify the taxonomic status of the genus.
Asunto(s)
ADN Espaciador Ribosómico/genética , Oenanthe/genética , Filogenia , Animales , China , Clasificación , Variación Genética , Oenanthe/clasificación , Análisis de Secuencia de ADN , Especificidad de la EspecieRESUMEN
Detection involves locating all candidate regions of interest (objects) in a scene independent of the object class with object distortions and contrast differences, etc., present. It is one of the most formidable problems in automatic target recognition, since it involves analysis of every local scene region. We consider new detection algorithms and the fusion of their outputs to reduce the probability of false alarm P(FA) while maintaining high probability of detection P(D). Emphasis is given to detecting obscured targets in infrared imagery.