Optimisation de l’identification et du dénombrement du microphytoplancton avec le système couplé de numérisation et d’analyse d’images FlowCAM – Zoo/PhytoImage (système innovant). Action 9 – Livrable 3. Evolution du matériel de numérisation : prototype FastCAM et perspectives. Rapport final, février 2016

This deliverable contains all development work of the FastCAM, new tool for fast imaging of the phytoplankton, which took place in 2015. It consists of: One report of the FastCAM and its comparison with the FlowCAM presentation: The FlowCAM enables the digitalization of a sample of phytoplankton with X10 and X 4 magnifications. The first allows a better morphological description and therefore a higher taxonomic resolution but with a longer scan time (16 X). Thus, for routine analyses, only scanning at 4 X is possible. A considerable gain would be able to do an acquisition to the magnification 10 X with a time of analysis more short, comparable to 4 X. A fast flow imaging system has therefore developed in this sense. He was called FastCAM. The system is based on the use of a high resolution (2 Megapixels) and high‐speed camera allowing the acquisition to 340 FPS. In this way, it allows to scan 10 mL of sample with a X 10 magnification within 15 min. Comparison of the images with those obtained with the FlowCAM clearly shows a gain to the use of the FastCAM. The outlook now is the establishment of a set of learning for a coupling with Zoo/Phytoimage and the industrial transfer of the system. A slide show presentation of the system showed during a project meeting (on the 4th of November 2015).Ce livrable contient l’ensemble des travaux de développement du FastCAM, nouvel outil de numérisation rapide du phytoplancton, ayant eu lieu en 2015. Il est constitué de deux documents : Un rapport de présentation du FastCAM et de sa comparaison avec le FlowCAM. Le FlowCAM permet la numérisation d’un échantillon de phytoplancton avec des grandissements X10 et X4. Le premier permet une meilleure description morphologique et donc une meilleure résolution taxonomique mais avec un temps d'acquisition environ 16X plus long. Ainsi, pour des analyses en routine, seule une numérisation au X4 est possible. Un gain considérable serait de pouvoir réaliser une acquisition au grandissement 10X avec un temps d'analyse plus court, comparable au 4X. Un système d’imagerie rapide en flux a donc été développé en ce sens. Il a été nommé FastCAM. Le système repose sur l’utilisation d’une caméra rapide haute résolution (2 Megapixels) permettant l’acquisition à 340 images/s. Grâce à cela, il permet de numériser 10 mL d’échantillon avec un grandissement X10 en moins de 15 min. La comparaison des images à celles obtenues avec le FlowCAM en un temps équivalent au X4 montre clairement un gain à l’utilisation du FastCAM. Les perspectives maintenant sont la constitution d’un set d’apprentissage pour un couplage avec le logiciel Zoo/Phytoimage. Un diaporama de présentation du système, présenté lors d’une réunion de projet (4 novembre 2015

The ZooCAM, a new in-flow imaging system for fast onboard counting, sizing and classification of fish eggs and metazooplankton

In this paper we present the ZooCAM, a system designed to digitize and analyse on board large volume samples of preserved and living metazooplankton (i.e. multicellular zooplankton) and fish eggs > 300 µm ESD. The ZooCAM has been specifically designed to overcome the difficulties to analyse zooplankton and fish eggs in the framework of the PELGAS survey, and provide high frequency data. The ZooCAM fish eggs counts were comparable to those done with a dissecting microscope. The ZooCAM enabled the accurate prediction and fast on board validation of staged anchovy and sardine eggs in almost real time after collection. A comparison with the ZooScan, on a more complex zooplanktonic community, provided encouraging results on the agreement between the 2 instruments. ZooCAM and ZooScan enabled the identification of similar communities and produced similar total zooplankton abundances, size distributions, and size spectra slopes, when tested on the same samples. However these results need to be further refined due to the small number of samples used to compare the two instruments. The main ZooCAM drawback resides in a slight but sensible underestimation of abundances and sizes, and therefore individual and community biovolumes. The ZooCAM have been successfully deployed over 4 years, on numerous surveys without suffering any major failure. When used in line with the CUFES it provided high resolution maps of staged fish eggs and zooplanktonic functional groups. Hence the ZooCAM is an appropriate tool for the development of on board, high frequency, high spatial coverage zooplanktonic and ecosystemic studies

Metazoan zooplankton in the Bay of Biscay: 16 years of individual sizes and abundances from the ZooScan and ZooCAM imaging systems

This paper presents two metazoan zooplankton datasets obtained by imaging samples collected on the Bay of Biscay continental shelf in spring during the PELGAS integrated surveys, over the 2004–2019 period. The samples were collected at night, with a WP2 200 µm mesh size fitted with a Hydrobios (back-run stop) mechanical flowmeter, hauled vertically from the sea floor to the surface with a maximum depth set at 100 m when the bathymetry is deeper. The first dataset originates from samples collected from 2004 to 2016, imaged on land with the ZooScan and is composed of 1,153,507 imaged and measured objects. The second dataset originates from samples collected from 2016 to 2019, imaged on board the R/V Thalassa with the ZooCAM and is composed of 702,111 imaged and measured objects. The imaged objects is composed of zooplankton individuals, zooplankton pieces, non-living particles and imaging artefacts, ranging from 300 µm to 3.39 mm Equivalent Spherical Diameter, individually imaged, measured and identified. Each imaged object is geolocated, associated to a station, a survey, a year and other metadata. Each object is described by a set of morphological and grey level based features (8 bits encoding, 0 = black, 255 = white), including size, automatically extracted on each individual image. Each object was taxonomically identified using the web based application Ecotaxa with built-in, random forest and CNN based, semi-automatic sorting tools followed by expert validation or correction. The objects were sorted in 172 taxonomic and morphological groups. Each dataset features a table combining metadata and data, at the individual object granularity, from which one can easily derive quantitative population and communities descriptors such as abundances, mean sizes, biovolumes, biomasses, and size structure. Each object’s individual image is provided along with the data. These two datasets can be used combined together for ecological studies as the two instruments are interoperable, or as training sets for ZooScan and ZooCAM users

Metazoan zooplankton in the Bay of Biscay: a 16-year record of individual sizes and abundances obtained using the ZooScan and ZooCAM imaging systems

International audienceThis paper presents two metazoan zooplankton datasets obtained by imaging samples collected on the Bay of Biscay continental shelf in spring during the PELGAS (PELagique GAScogne) integrated surveys over the 2004–2019 period. The samples were collected at night with a 200 µm mesh-size WP2 net fitted with a Hydrobios (back-run stop) mechanical flowmeter and hauled vertically from the sea floor to the surface, with the maximum depth set at 100 m when the bathymetry was deeper than this. The first dataset originates from samples collected from 2004 to 2016 and imaged on land with the ZooScan and is composed of 1 153 507 imaged and measured objects. The second dataset originates from samples collected from 2016 to 2019 and imaged onboard the R/V Thalassa with the ZooCAM and is composed of 702 111 imaged and measured objects. The imaged objects are composed of zooplankton individuals, zooplankton pieces, non-living particles and imaging artefacts ranging from 300 µm to 3.39 mm in equivalent spherical diameter which were individually imaged, measured and identified. Each imaged object is geolocated and associated with a station, a survey, a year and other metadata. Each object is described by a set of morphological and grey-level-based features (8 bit encoding, 0 = black, 255 = white), including size, that were automatically extracted from each individual image. Each object was taxonomically identified using the web-based application Ecotaxa with built-in random-forest and CNN-based semi-automatic sorting tools, which was followed by expert validation or correction. The objects were sorted into 172 taxonomic and morphological groups. Each dataset features a table combining metadata and data at individual-object granularity from which one can easily derive quantitative population and community descriptors such as abundances, mean sizes, biovolumes, biomasses and size structure. Each object's individual image is provided along with the data. These two datasets can be used in combination for ecological studies, as the two instruments are interoperable, or they can be used as training sets for ZooScan and ZooCAM users. The data presented here are available at the SEANOE dataportal: https://doi.org/10.17882/94052 (ZooScan dataset, Grandremy et al., 2023c) and https://doi.org/10.17882/94040 (ZooCAM dataset, Grandremy et al., 2023d)