Dynamic laser speckle and fuzzy mathematical morphology applied to studies of chemotaxis towards hydrocarbons

The movement of the microorganisms towards a higher concentration of the chemical attractant is called positive chemotaxis and is involved in the efficiency of chemical degradation. Several studies are focused in this field related to genomics, and towards demonstrating chemotactic responses by bact...

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Detalles Bibliográficos
Autores: Nisenbaum, Melina, Bouchet, Agustina, Guzmán, Marcelo Nicolás, González, Jorge Froilán, Sendra, Gonzalo Hernán, Pastore, Juan Ignacio, Trivi, Marcelo Ricardo, Murialdo, Silvia Elena
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2014
País:Argentina
Institución:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
Repositorio:CIC Digital (CICBA)
Idioma:inglés
OAI Identifier:oai:digital.cic.gba.gob.ar:11746/4076
Acceso en línea:https://digital.cic.gba.gob.ar/handle/11746/4076
Access Level:acceso abierto
Palabra clave:Bioquímica y Biología Molecular
dynamic laser speckle
FMM
fuzzy mathematical morphology
Biodegradación Ambiental
Pseudomonas
Hidrocarburos
Ambiente
Quimiotaxis
Descripción
Sumario:The movement of the microorganisms towards a higher concentration of the chemical attractant is called positive chemotaxis and is involved in the efficiency of chemical degradation. Several studies are focused in this field related to genomics, and towards demonstrating chemotactic responses by bacteria, but there is little information related to the activity and morphology of their response. In this work, we use a recently reported dynamic speckle laser method, to process images and to distinguish motile surface patterns per area of colonisation by applying image processing techniques called fuzzy mathematical morphology (FMM). The images of bacterial colonies are usually surfaced, with vague edges and non-homogeneous grey levels. Hence, conventional image processing methods for shape analysis cannot be applied in these cases. In this paper, we propose the application FMM to solve this problem. The approach given was effective to segment, detect and also to describe colonisation patterns.