Cargando…
An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of Paragorgia arborea in Relation to Hydrographic Conditions
Imaging technologies are being deployed on cabled observatory networks worldwide. They allow for the monitoring of the biological activity of deep-sea organisms on temporal scales that were never attained before. In this paper, we customized Convolutional Neural Network image processing to track beh...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662914/ https://www.ncbi.nlm.nih.gov/pubmed/33158174 http://dx.doi.org/10.3390/s20216281 |
_version_ | 1783609505392623616 |
---|---|
author | Zuazo, Ander Grinyó, Jordi López-Vázquez, Vanesa Rodríguez, Erik Costa, Corrado Ortenzi, Luciano Flögel, Sascha Valencia, Javier Marini, Simone Zhang, Guosong Wehde, Henning Aguzzi, Jacopo |
author_facet | Zuazo, Ander Grinyó, Jordi López-Vázquez, Vanesa Rodríguez, Erik Costa, Corrado Ortenzi, Luciano Flögel, Sascha Valencia, Javier Marini, Simone Zhang, Guosong Wehde, Henning Aguzzi, Jacopo |
author_sort | Zuazo, Ander |
collection | PubMed |
description | Imaging technologies are being deployed on cabled observatory networks worldwide. They allow for the monitoring of the biological activity of deep-sea organisms on temporal scales that were never attained before. In this paper, we customized Convolutional Neural Network image processing to track behavioral activities in an iconic conservation deep-sea species—the bubblegum coral Paragorgia arborea—in response to ambient oceanographic conditions at the Lofoten-Vesterålen observatory. Images and concomitant oceanographic data were taken hourly from February to June 2018. We considered coral activity in terms of bloated, semi-bloated and non-bloated surfaces, as proxy for polyp filtering, retraction and transient activity, respectively. A test accuracy of 90.47% was obtained. Chronobiology-oriented statistics and advanced Artificial Neural Network (ANN) multivariate regression modeling proved that a daily coral filtering rhythm occurs within one major dusk phase, being independent from tides. Polyp activity, in particular extrusion, increased from March to June, and was able to cope with an increase in chlorophyll concentration, indicating the existence of seasonality. Our study shows that it is possible to establish a model for the development of automated pipelines that are able to extract biological information from times series of images. These are helpful to obtain multidisciplinary information from cabled observatory infrastructures. |
format | Online Article Text |
id | pubmed-7662914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76629142020-11-14 An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of Paragorgia arborea in Relation to Hydrographic Conditions Zuazo, Ander Grinyó, Jordi López-Vázquez, Vanesa Rodríguez, Erik Costa, Corrado Ortenzi, Luciano Flögel, Sascha Valencia, Javier Marini, Simone Zhang, Guosong Wehde, Henning Aguzzi, Jacopo Sensors (Basel) Article Imaging technologies are being deployed on cabled observatory networks worldwide. They allow for the monitoring of the biological activity of deep-sea organisms on temporal scales that were never attained before. In this paper, we customized Convolutional Neural Network image processing to track behavioral activities in an iconic conservation deep-sea species—the bubblegum coral Paragorgia arborea—in response to ambient oceanographic conditions at the Lofoten-Vesterålen observatory. Images and concomitant oceanographic data were taken hourly from February to June 2018. We considered coral activity in terms of bloated, semi-bloated and non-bloated surfaces, as proxy for polyp filtering, retraction and transient activity, respectively. A test accuracy of 90.47% was obtained. Chronobiology-oriented statistics and advanced Artificial Neural Network (ANN) multivariate regression modeling proved that a daily coral filtering rhythm occurs within one major dusk phase, being independent from tides. Polyp activity, in particular extrusion, increased from March to June, and was able to cope with an increase in chlorophyll concentration, indicating the existence of seasonality. Our study shows that it is possible to establish a model for the development of automated pipelines that are able to extract biological information from times series of images. These are helpful to obtain multidisciplinary information from cabled observatory infrastructures. MDPI 2020-11-04 /pmc/articles/PMC7662914/ /pubmed/33158174 http://dx.doi.org/10.3390/s20216281 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zuazo, Ander Grinyó, Jordi López-Vázquez, Vanesa Rodríguez, Erik Costa, Corrado Ortenzi, Luciano Flögel, Sascha Valencia, Javier Marini, Simone Zhang, Guosong Wehde, Henning Aguzzi, Jacopo An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of Paragorgia arborea in Relation to Hydrographic Conditions |
title | An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of Paragorgia arborea in Relation to Hydrographic Conditions |
title_full | An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of Paragorgia arborea in Relation to Hydrographic Conditions |
title_fullStr | An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of Paragorgia arborea in Relation to Hydrographic Conditions |
title_full_unstemmed | An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of Paragorgia arborea in Relation to Hydrographic Conditions |
title_short | An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of Paragorgia arborea in Relation to Hydrographic Conditions |
title_sort | automated pipeline for image processing and data treatment to track activity rhythms of paragorgia arborea in relation to hydrographic conditions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662914/ https://www.ncbi.nlm.nih.gov/pubmed/33158174 http://dx.doi.org/10.3390/s20216281 |
work_keys_str_mv | AT zuazoander anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT grinyojordi anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT lopezvazquezvanesa anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT rodriguezerik anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT costacorrado anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT ortenziluciano anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT flogelsascha anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT valenciajavier anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT marinisimone anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT zhangguosong anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT wehdehenning anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT aguzzijacopo anautomatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT zuazoander automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT grinyojordi automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT lopezvazquezvanesa automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT rodriguezerik automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT costacorrado automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT ortenziluciano automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT flogelsascha automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT valenciajavier automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT marinisimone automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT zhangguosong automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT wehdehenning automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions AT aguzzijacopo automatedpipelineforimageprocessinganddatatreatmenttotrackactivityrhythmsofparagorgiaarboreainrelationtohydrographicconditions |