Dataset: ZooProcess and Ecotaxa Output for Zooplankton Mediated Aggregates
Deployment: AE2306

View Data: For data, See Dataset Metadata Page: https://osprey.bco-dmo.org/dataset/931883

Principal Investigator:

Amy Maas (Bermuda Institute of Ocean Sciences, BIOS)

Co-Principal Investigator:

Leocadio Blanco-Bercial (Bermuda Institute of Ocean Sciences, BIOS)

Technician:

Hannah Gossner (Bermuda Institute of Ocean Sciences, BIOS)

BCO-DMO Data Manager:

Amber D. York (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Project:

Collaborative Research: Zooplankton mediation of particle formation in the Sargasso Sea (Zooplankton Mediation)

Version:

Deployment Synonyms:

BATS 10402

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Description

Methods & Sampling

Dataset acquisition description

One pair of 1m2 MOCNESS (Multiple Open Closing Nets with Environmental Sensor System) tows were performed during each cruise- one during the day, and one at night (MOCNESS, Wiebe et al, 1985). Nets with 150um mesh were used to better capture the smaller midwater zooplankton community in the region. Eight nets were fired in sequence along the upcast to capture spatially discrete zooplankton samples between 600m and the surface. While nets one, two, and three consistently targeted depths of 600-500m, 500m-400m, and 400-300m, depths for nets four through eight varied based on hydrographic features including the thermocline, deep chlorophyll maximum, and oxygen minimum zone (Maas et al, 2014, Steinberg et al, 2008). Once onboard, samples were split in two using a Motoda splitter (Motoda, 1959) with half preserved with sodium tetraborate buffered 4% formalin in seawater to be scanned with a ZooSCAN (Gorsky et al, 2010) and half placed in 95% undenatured ethanol for metabarcoding.

A representative subsample of the formalin-preserved zooplankton community from each net were imaged using a ZooSCAN ver. 4 at either 4,800 dpi or 2,400 dpi (following the methods in: Gorsky et al., 2010, Vandromme et al., 2012 as detailed in Maas et al. 2021). The change in resolution partway through the project was a result of recommendations from Hydroptic and loss of software support for 4800dpi imaging. In order to better represent all size classes in the images, the original sample was divided into three size categories. All individuals larger than 2 cm were selected by eye and scanned separately from all the others (fraction "d1"). The remainder of the sample was sieved through a 1-mm mesh sieve, and both size fractions were individually scanned ("d2" >1000um, "d3" 153-1000um). From these smaller size fractions, at least 1500 particles were scanned after subsampling using a Motoda splitter (Motoda, 1959), requiring generation of two separate scans for both size classes. This resulted in a total of five images per net.

ZooSCAN Image names:

Image names include: cruise#_mocnessID_net#_sizefraction_ and _a|b if a replicate and end in _raw_1.tif

Multiple images of the same size fraction were sometimes taken to obtain a sufficient number of particles. These replicates are named a or b. If there is no replicate they don’t have a letter in the image name. An a and b scan were always done for size classes d2 and d3. This was important because the split size is for the sum of a+b (e.g. if a is ¼ and b is ¼, the acq_sub_part will be 0.5).

Example of image names:

ae2112_m22_n4_d3_a_raw_1.tif [a replicate]
ae2112_m22_n4_d3_b_raw_1.tif [b replicate]
ae2204_m27_n5_d1_raw_1.tif [no replicate]

This dataset contains the "object_id" (the particle identifier) which is constructed the same way as the image name except it as an additional _# at the end. This additional number in the object_id is added by the ZooProcess software (Hydroptic, 2016).
e.g.
object_id: ae1614_m3_n1_d2_a_1_100
image_name: ae1614_m3_n1_d2_a_1.tif

Particle names:

Names for particles follow the pattern "CruiseID_MocnessID_NetNumber_ScanFraction" followed by "_1_XXX", with "1" being automatically added by the software to indicate no duplicates of that scan and "XXX" being the unique particle number within that scan.

Parameter (column name) nomenclature and data origin:
* (see the "Parameters" section which contains all column information for the ecotaxa output table)

Parameters (column names) beginning with "object" include basic identifying metadata input by the user as well as all particle measurement data generated by ZooProcess. Any parameters beginning with "object_annotation" parameters are added by Ecotaxa. Parameters that begin with "sample" are sampling metadata input by the user during the scanning process. "Process" parameters describe the software and assumptions or corrections input during the data processing. "Acq" describes the portion of the sample scanned (input by user) and provides some summary data about the scanned image.

Interpreting acq_sub_part

For this project, the acq sub part is the fraction of the individual scan only. "A" and "B" scans of the same fraction can be statistically combined for analysis (e.g. d2_a and d2_b from the same net can be combined by adding the sub parts to create just a "d2" group).

Instruments:

The Multiple Opening/Closing Net and Environmental Sensing System or MOCNESS is a family of net systems based on the Tucker Trawl principle. There are currently 8 different sizes of MOCNESS in existence which are designed for capture of different size ranges of zooplankton and micro-nekton. Each system is designated according to the size of the net mouth opening and in two cases, the number of nets it carries. The original MOCNESS (Wiebe et al, 1976) was a redesigned and improved version of a system described by Frost and McCrone (1974)(from MOCNESS manual). The MOCNESS used in this experiment is a 1m2 (mouth size) rigged with nine 150um mesh nets. One is flown open on the downcast to balance the net (Net 0- contents preserved but not analyzed), and the other eight (Net 1-8) are triggered on the upcast at desired depths. This particular MOCNESS was originally manufactured by Biological Environmental Sensor Systems (BESS), but was refit with new electronics from SIO/STS in 2017 (Net Interface Unit, Net Angle Sensor) to allow it to interface with Seabird instruments (SBE9Plus CTD, SBE3S Temperature, SBE4C Conductivity, SBE11 Deck Box).

The ZooSCAN (CNRS patent) system makes use of scanner technology with custom lighting and a watertight scanning chamber into which liquid zooplankton samples can be placed. The scanner recovers a high-resolution, digital image and the sample can be recovered without damage. These digital images can then be investigated by computer processing. While the resolution of the digitized zooplankton images is lower than the image obtained using a binocular microscope, this technique has proven to be more than adequate for large sample sets. Identification of species is done by automatic comparison of the image (vignette) of each individual animal in the scanned image with a library data set which may be built by the investigator for each individual survey or imported from a previous survey. The latest machine learning algorithm allows high recognition levels even if we recommend complementary manual sorting to achieve a high number of taxonomic groups. Scans for this dataset performed with a ZooSCAN (Hydroptic, HYDROPTIC_V4) running with Vuescan (version 9.5.24) and ZooProcess (version 8.22, ImageJ macro suite).

Data Processing Description

Dataset Processing Description

Scans were processed using ZooProcess (version 8.22, ImageJ macro suite). The "Convert and process from RAW" function was used to separate particles into individual vignettes and generate a suite of measurements for each particle. "Doubles" (vignettes containing more than one particle) were manually separated in the software and reprocessed.

Example vignettes (see Supplemental files for example image download):
Example copepod vignette Example ostracod vignette Example pteropod vignette

Processed scans and their corresponding metadata were then uploaded to Ecotaxa (Picheral et al, https://ecotaxa.obs-vlfr.fr/), where a training set was created using manually classified images from this project as well as existing validated images from other projects in the Sargasso Sea. Classification categories were chosen based on taxon of interest, identification level in previous projects, and known limitations of the software. Generally, broader level taxonomic groups are used. Identification of all particles was predicted, then manually validated.

Data versioning

The ecotaxa data included in this dataset version are "Ecotaxa Export version 1.0."

The ecotaxa export file will be updated in a versioned manner as validation of identification is completed. Ecotaxa output versions are as follows:

Version 1: No identifications, predicted or validated
Version 2: All identifications predicted
Version 3: All identifications validated

More information about this dataset deployment

Funding

Award Number	Funding Source
OCE-2023372	NSF Division of Ocean Sciences
OCE-2023621	NSF Division of Ocean Sciences

Instruments

MOCNESS1

Supplied Name: 1m MOCNESS

Supplied Description:

Instrument Type

Generic Name: MOCNESS1

Acronym: MOC1

Community Identifier: http://vocab.nerc.ac.uk/collection/L22/current/NETT0097/

Generic Description:

The Multiple Opening/Closing Net and Environmental Sensing System or MOCNESS is a family of net systems based on the Tucker Trawl principle. The MOCNESS-1 carries nine 1-m2 nets usually of 335 micrometer mesh and is intended for use with the macrozooplankton. All nets are black to reduce contrast with the background. A motor/toggle release assembly is mounted on the top portion of the frame and stainless steel cables with swaged fittings are used to attach the net bar to the toggle release. A stepping motor in a pressure compensated case filled with oil turns the escapement crankshaft of the toggle release which sequentially releases the nets to an open then closed position on command from the surface. -- from the MOCNESS Operations Manual (1999 + 2003).

ZooSCAN

Supplied Name: ZooSCAN ver. 4

Supplied Description:

http://www.hydroptic.com/index.php/public/Page/product_item/ZOOSCAN

Scans for this dataset performed with a ZooSCAN (Hydroptic, HYDROPTIC_V4) running with Vuescan (version 9.5.24) and ZooProcess (version 8.22, ImageJ macro suite).

Instrument Type

Generic Name: ZooSCAN

Generic Description:

Description excerpt from Hydroptic website
http://www.hydroptic.com/index.php/public/Page/product_item/ZOOSCAN

The ZooSCAN (CNRS patent) system makes use of scanner technology with custom lighting and a watertight scanning chamber into which liquid zooplankton samples can be placed. The scanner recovers a high-resolution, digitial image and the sample can be recovered without damage. These digital images can then be investigated by computer processing. While the resolution of the digitized zooplankton images is lower than the image obtained using a binocular microscope this technique has proved to be more than adequate for large sample sets. Identification of species is done by automatic comparison of the image (vignette) of each individual animal in the scanned image with a library data set which may be built by the investigator for each individual survey or imported from a previous survey. The latest machine learning algorithm allows high recognition levels even if we recommend complementary manual sorting to achieve a high number of taxonomic groups.

Parameters

Supplied Name	Supplied description	Supplied Units	Standard Name
object_id	Particle identification number. Typically cruiseID_mocnessID_net#_taxonomy_image#. [Source: User]	unitless	individual
object_lat_start	Starting latitude of sample collection. [Source: User]	Decimal degrees	lat
object_lon_start	Starting longitude of sample collection. [Source: User]	Decimal degrees	lon
object_date	Date of sample collection. Local time zone (ADT/AST). Source: User]	unitless	date_local
object_time	Start time of sample collection. Local time zone (ADT/AST). [Source: User]	unitless	time_local
object_ISO_DateTime_UTC	Datetime with timezone (start time of sample collection). Format ISO 8601, Time Zone UTC. [Source: User]	unitless	ISO_DateTime_UTC
object_link	URL to Villefranche sur mer Quantitative Imaging Platform which hosts manuals summarizing image capture and upload. Autogenerated by software. [Source: Zooprocess]	unitless	external_link
object_depth_min	Minimum depth of sample collection (Zmin, shallowest net depth). [Source: User]	Meters	depth_n
object_depth_max	Maximum depth of sample collection (Zmax, deepest net depth). [Source: User]	Meters	depth_n
object_lat_end	Ending latitude of sample collection. [Source: User]	Decimal degrees	lat
object_lon_end	Ending longitude of sample collection. [Source: User]	Decimal degrees	lon
object_area	Surface area of the object. [Source: Zooprocess]	Square pixels	surface_area
object_mean	Average grey value within the object. Pixel intensity value 0-255 (8 bit greyscale image).	pixel intensity	no_bcodmo_term
object_stddev	Standard deviation of the grey value used to generate the mean grey value. Pixel intensity value 0-255 (8 bit greyscale image).	pixel intensity	no_bcodmo_term
object_mode	Modal grey value within the object. Pixel intensity value 0-255 (8 bit greyscale image).	pixel intensity	no_bcodmo_term
object_min	Minimum grey value within the object (0=black). Pixel intensity value 0-255 (8 bit greyscale image).	pixel intensity	no_bcodmo_term
object_max	Maximum grey value within the object (255=white). Pixel intensity value 0-255 (8 bit greyscale image).	pixel intensity	max_grey_level
object_x	X position of the center of gravity of the object within the vignette. [Source: Zooprocess]	Pixels	x_pixel_unit
object_y	Y position of the center of gravity of the object within the vignette. [Source: Zooprocess]	Pixels	y_pixel_unit
object_xm	X position of the center of gravity of the object's grey levels within the vignette. [Source: Zooprocess]	Pixels	x_pixel_unit
object_ym	Y position of the center of gravity of the object's grey levels within the vignette. [Source: Zooprocess]	Pixels	y_pixel_unit
object_perim	Length of the outside boundary (perimeter) of the object. [Source: Zooprocess]	Pixels	image_analysis
object_bx	X coordinate of the top left point of the smallest rectangle enclosing the object within the whole scan image. [Source: Zooprocess]	Pixels	x_coordinate
object_by	Y coordinate of the top left point of the smallest rectangle enclosing the object within the whole scan image. [Source: Zooprocess]	Pixels	y_coordinate
object_width	Width of the smallest rectangle enclosing the object. [Source: Zooprocess]	Pixels	width
object_height	Height of the smallest rectangle enclosing the object. [Source: Zooprocess]	Pixels	height
object_major	Primary axis of the best fitting ellipse for the object. [Source: Zooprocess]	Pixels	image_analysis
object_minor	Secondary axis of the best fitting ellipse for the object. [Source: Zooprocess]	Pixels	image_analysis
object_angle	Angle between the primary axis and a line parallel to the x-axis of the image. [Source: Zooprocess]	Decimal degrees	no_bcodmo_term
object_circ	Circularity. (4piArea)/Perim^2. A value of 1 indicates a perfect circle, a value approaching 0 indicates an increasingly elongated polygon. . [Source: Zooprocess]	unitless	image_analysis
object_feret	Maximum ferret diameter, i.e. the longest distance between any two points along the object boundary. [Source: Zooprocess]	Pixels	feret_diameter
object_intden	Integrated density. The sum of the grey values of the pixels in the object (i.e. = Area*Mean). . [Source: Zooprocess]	unitless	no_bcodmo_term
object_median	Median grey value within the object. Pixel intensity value 0-255 (8 bit greyscale image). [Source: Zooprocess]	pixel intensity	image_analysis
object_skew	Skewness (third order moment about the mean) of the histogram of the grey level values. [Source: Zooprocess]	unitless	no_bcodmo_term
object_kurt	Kurtosis (fourth order moment about the mean) of the histogram of grey level values. [Source: Zooprocess]	unitless	no_bcodmo_term
object_perc_area	Percentage of object's surface area that is comprised of holes, defined as the background grey level. [Source: Zooprocess]	Percentage	no_bcodmo_term
object_xstart	X coordinate of the top left point of the image within the scan. [Source: Zooprocess]	Pixels	x_coordinate
object_ystart	Y coordinate of the top left point of the image within the scan. [Source: Zooprocess]	Pixels	y_coordinate
object_area_exc	Surface area of the object excluding holes (=Area*(1-(%area/100)). [Source: Zooprocess]	Square pixels	no_bcodmo_term
object_fractal	Fractal dimension of the object boundary (Berube and Jebrak, 1999). [Source: Zooprocess]	unitless	no_bcodmo_term
object_skelarea	Surface area of skeleton in pixels. In a binary image, the skeleton is obtained by repeatedly removing pixels from the edges of objects until they are reduced to the width of a single pixel. (Berube and Jebrak, 1999). [Source: Zooprocess]	Pixels	surface_area
object_slope	Slope of the grey level normalized cumulative histogram. [Source: Zooprocess]	unitless	no_bcodmo_term
object_histcum1	Grey level at 25% of the normalized cumulative histogram of grey levels. [Source: Zooprocess]	pixel intensity	no_bcodmo_term
object_histcum2	Grey level at 50% of the normalized cumulative histogram of grey levels. [Source: Zooprocess]	pixel intensity	no_bcodmo_term
object_histcum3	Grey level at 75% of the normalized cumulative histogram of grey levels. [Source: Zooprocess]	pixel intensity	no_bcodmo_term
object_xmg5	X position of the center of gravity of the object using a gamma value of 5. [Source: Zooprocess]	Pixels	no_bcodmo_term
object_ymg5	Y position of the center of gravity of the object using a gamma value of 5. [Source: Zooprocess]	Pixels	no_bcodmo_term
object_nb1	Number of remaining objects in the image after thresholding on level Histcum 1. [Source: Zooprocess]	unitless	no_bcodmo_term
object_nb2	Number of remaining objects in the image after thresholding on level Histcum 2. [Source: Zooprocess]	unitless	no_bcodmo_term
object_nb3	Number of remaining objects in the image after thresholding on level Histcum 3. [Source: Zooprocess]	unitless	no_bcodmo_term
object_compentropy	always set to 0, measurement no longer perfomed in Zooprocess. [Source: Zooprocess]	unitless	no_bcodmo_term
object_compmean	always set to 0, measurement no longer perfomed in Zooprocess. [Source: Zooprocess]	unitless	no_bcodmo_term
object_compslope	always set to 0, measurement no longer perfomed in Zooprocess. [Source: Zooprocess]	unitless	no_bcodmo_term
object_compm1	always set to 0, measurement no longer perfomed in Zooprocess. [Source: Zooprocess]	unitless	no_bcodmo_term
object_compm2	always set to 0, measurement no longer perfomed in Zooprocess. [Source: Zooprocess]	unitless	no_bcodmo_term
object_compm3	always set to 0, measurement no longer perfomed in Zooprocess. [Source: Zooprocess]	unitless	no_bcodmo_term
object_symetrieh	Bilateral horizonal symmetry index (Romagnan et al 2016). [Source: Zooprocess]	unitless	no_bcodmo_term
object_symetriev	Bilateral vertical symmetry index (Romagnan et al 2016). [Source: Zooprocess]	unitless	no_bcodmo_term
object_symetriehc	Symmetry of the object in relation to the horizontal axis after thresholding the grey level at Histcum 1 value. [Source: Zooprocess]	unitless	no_bcodmo_term
object_symetrievc	Symmetry of the object in relation to the vertical axis after thresholding at grey level Histcum 1 value. [Source: Zooprocess]	unitless	no_bcodmo_term
object_convperim	The perimeter of the smallest polygon within which all points of the object fit. [Source: Zooprocess]	Pixels	no_bcodmo_term
object_convarea	The area of the smallest polygon within which all points of the object fit. [Source: Zooprocess]	Pixels	no_bcodmo_term
object_fcons	Measure of contrast based on the texture feature descriptor (Amadasun and King, 1989). [Source: Zooprocess]	unitless	no_bcodmo_term
object_thickr	Thickness ratio; relationship between the maximum thickness of an object and the average thickness of the object excluding the maximum. . [Source: Zooprocess]	unitless	no_bcodmo_term
object_tag	Old variable which is no longer used (0 or 1; 1 if duplicate "tagged" object). [Source: Zooprocess]	unitless	no_bcodmo_term
object_esd	Equivalent spherical diameter. Sqrt(area/?). [Source: Zooprocess]	Pixels	ESD
object_elongation	Elongation index. Major axis/minor axis. [Source: Zooprocess]	unitless	image_analysis
object_range	Range of grey values (0-255). [Source: Zooprocess]	pixel intensity	image_analysis
object_meanpos	Relative position of the mean grey. (Mean grey- Max grey)/(Mean grey-Min grey). [Source: Zooprocess]	unitless	no_bcodmo_term
object_centroids	Difference between the mass and the grey-level object's centroids. Square root ((objGreyX - objX)^2 + (objGreyY - objY)^2). [Source: Zooprocess]	Pixels	no_bcodmo_term
object_cv	Coefficient of variation of grey values. 100*(stddev/mean). [Source: Zooprocess]	unitless	no_bcodmo_term
object_sr	Index of variation of grey values. 100*(stddev/max-min)). [Source: Zooprocess]	unitless	no_bcodmo_term
object_perimareaexc	Index of relative complexity of the perimeter. perimeter/area_exc. [Source: Zooprocess]	unitless	no_bcodmo_term
object_feretareaexc	Alternate elongation index. feret/area_exc. [Source: Zooprocess]	unitless	no_bcodmo_term
object_perimferet	Index of relative complexity of the perimeter. perim/feret. [Source: Zooprocess]	unitless	no_bcodmo_term
object_perimmajor	Alternate index of relative complexity of the perimeter. perim/major. [Source: Zooprocess]	unitless	no_bcodmo_term
object_circex	Circularity of the object excluding white pixels. (4pi(?)area_exc)/perimeter^2. [Source: Zooprocess]	unitless	no_bcodmo_term
object_cdexc	Distance between the mass and the grey-level object's centroids. (centroid^2)/area_exc. [Source: Zooprocess]	Pixels	no_bcodmo_term
sample_id	Name of sample (scan) from which the object originates (image_name without .tif extension). [Source: User]	unitless	sample
sample_dataportal_descriptor	Optional descriptor. [Source: User]	unitless	sample_descrip
sample_scan_operator	Initials of the individual who performed the scan. [Source: User]	unitless	person
sample_ship	Research vessel (if applicable) where sample was taken. [Source: User]	unitless	ship
sample_program	Research program (if applicable) under which sample was taken. [Source: User]	unitless	project
sample_stationid	Station identifier (if applicable) at which sample was taken. [Source: User]	unitless	station
sample_bottomdepth	Recorded depth of the seafloor at the start of the tow. [Source: User]	Meters	depth
sample_ctdrosettefilename	Associated CTD file name (if applicable). [Source: User]	unitless	file_name
sample_other_ref	Optional other reference notes. [Source: User]	unitless	comment
sample_tow_nb	Number of tows, if more than one, combined to create sample. [Source: User]	Count	site_descrip
sample_tow_type	Type of tow profile used to collect sample. 1= oblique, 2 = horizontal, 3=vertical, 0= Other sampling method. [Source: User]	unitless	sample_type
sample_net_type	Type of net used to collect the sample (e.g. MOCNESS, Reeve, Tucker, etc). [Source: User]	unitless	sample_type
sample_net_mesh	Mesh size of the net used to collect the sample. [Source: User]	Microns	net_mesh
sample_net_surf	Area of net mouth. [Source: User]	Meters squared	sample_type
sample_zmax	Maximum depth of tow or net for this sample. [Source: User]	Meters	depth
sample_zmin	Minimum depth of tow or net for this sample. [Source: User]	Meters	depth
sample_tot_vol	Total volume of water filtered while capturing this sample. [Source: User]	Meters cubed	vol_filt
sample_comment	Optional comment on this sample. [Source: User]	unitless	comment
sample_tot_vol_qc	Quality flag for how volume of this tow or net was acquired. 1= RECORDED volume (flowmeter), 2= Calculated volume (using the mean volumne of other nets, 3= Estimated volume (net area * tow distance) . [Source: User]	unitless	q_flag
sample_depth_qc	Quality flag for how the depth of this tow or net was acquired. 1= Measured by a depth sensor, 2= Calculated from cable length and angle, 3= Estimated from cable length. [Source: User]	unitless	q_flag
sample_sample_qc	Quality flag for condition of the sample at time of scanning. Set of four digits defined below.; First digit is sample airtightness. 1=OK, 2=NOK (not ok); Second digit is sample richness. 1= Normal richness, 2=Very rich sample, 3=No plankton (almost) in sample; Third digit is sample condition. 1= Good condition , 2 = Dryed (no remaining liquid), 3= Rotton (loss of fixative); Fourth digit is disturbing elements. 1=No disturbing elements, 2=One of few large objects present in jar, 3=SOUP (phytoplankton, organic matter, clay/mud/mineral); . [Source: User]	unitless	q_flag
sample_barcode	Barcode number assigned to sample if applicable. [Source: User]	unitless	sample
sample_duration	Duration of the sampling tow. [Source: User]	Minutes	time_elapsed
sample_ship_speed	Average ship speed during tow. [Source: User]	Knots	speed
sample_cable_length	Maximum cable out during tow (m). [Source: User]	Meters	sample_descrip
sample_cable_angle	Angle of the net cable during the tow (degrees from vertical). [Source: User]	Degrees	sample_descrip
sample_cable_speed	Speed of the winch payout/retrival during the tow. [Source: User]	Meters per minute	sample_descrip
sample_nb_jar	Number of the jar containing the sample. [Source: User]	unitless	sample_descrip
sample_open	Undefined. [Source: User]	unitless	no_bcodmo_term
process_id	Process identifier. "zooprocess" and then the sample ID. [Source: Zooprocess]	unitless	sample
process_date	Date the scan was performed. Local time zone (ADT/AST). [Source: Zooprocess]	unitless	date_local
process_time	Time the scan was performed. Local time zone (ADT/AST). [Source: Zooprocess].	unitless	time_local
process_img_software_version	Version of zooprocess software utilized. [Source: Zooprocess]	unitless	sample_descrip
process_img_resolution	Resolution of the scan. [Source: Zooprocess]	Dpi	sample_descrip
process_img_od_grey	Parameter not used- always nan. [Source: Zooprocess]	unitless	no_bcodmo_term
process_img_od_std	Parameter not used- always 0. [Source: Zooprocess]	unitless	no_bcodmo_term
process_img_background_img	Image name of background scan used. [Source: Zooprocess]	unitless	file_name
process_particle_version	Version of zooprocess software used to process particles. [Source: Zooprocess]	unitless	sample_descrip
process_particle_threshold	8 bit coded grey level value to separate the objects from the background. [Source: Zooprocess]	pixel intensity	no_bcodmo_term
process_particle_pixel_size_mm	The number of pixels per millimeter with this dpi. [Source: Zooprocess]	Pixels per millimeter	no_bcodmo_term
process_particle_min_size_mm	Minimum size particle included in vignette extraction. [Source: Zooprocess]	Millimeters	no_bcodmo_term
process_particle_max_size_mm	Maximum size particle included in vignette extraction. [Source: Zooprocess]	Millimeters	no_bcodmo_term
process_particle_sep_mask	Whether or not to include a separation mask created during separation of touching vignettes. [Source: Zooprocess]	unitless	no_bcodmo_term
process_particle_bw_ratio	ratio of pixels from the image that are above the threshold value (i.e; objects of image noise). [Source: Zooprocess]	unitless	no_bcodmo_term
process_software	Software name, version, and date used to process this sample. [Source: Zooprocess]	unitless	sample_descrip
acq_id	Name of the fraction or replicate being imaged (format fraction_cruise_mocness_net). [Source: Zooprocess]	unitless	sample_descrip
acq_instrument	Type of instrument used to take original image (e.g. Zooscan, UVP, etc). [Source: User]	unitless	instrument
acq_min_mesh	The minimum mesh size/minimum hypothetical particle size of the fraction being imaged. [Source: User]	Microns	sample_descrip
acq_max_mesh	The maximum mesh size/maximum hypothetical particle size of the fraction being imaged. [Source: User]	Microns	sample_descrip
acq_sub_part	Portion of the sample in this image- denominator of the ratio (e.g. 1/64 will read "64"). [Source: User]	Integer	sample_descrip
acq_sub_method	Method or splitter type used to subsample (e.g. Motoda, folsom). [Source: User]	unitless	sample_descrip
acq_hardware	Hardware used to image the sample including version number (Zooscan model). [Source: Zooprocess]	unitless	inst_model
acq_software	Software used to take the image- Vuescan version number. [Source: Zooprocess]	unitless	sample_descrip
acq_author	Initials of individual who took the image. [Source: Zooprocess]	unitless	person
acq_imgtype	Type of image (e.g. zooscan, UVP). . [Source: Zooprocess]	unitless	sample_descrip
acq_scan_date	Date that the scan was performed. Local time zone (ADT/AST). [Source: Zooprocess]	unitless	date_local
acq_scan_time	Time the scan was performed. Local time zone (ADT/AST). [Source: Zooprocess]	unitless	time_local
acq_quality	Parameter not used- always nan. [Source: Zooprocess]	unitless	no_bcodmo_term
acq_bitpixel	Flag- Vuescan coding of the grey resolution for the raw image. [Source: Zooprocess]	unitless	flag
acq_greyfrom	Flag- The green channel of image from the scanner sensor is converted in grey by Vuescan for the image saving and processing. [Source: Zooprocess]	unitless	flag
acq_scan_resolution	Flag- Vuescan coding of the resolution, utilized by Zooprocess to compute the pixel size and image resolution in dpi. [Source: Zooprocess]	unitless	flag
acq_rotation	Flag- The raw image from the scanner is rotated before being saved. [Source: Zooprocess]	unitless	flag
acq_miror	Flag- The raw image from the scanner is mirrored before being saved. [Source: Zooprocess]	unitless	flag
acq_xsize	Horizontal size of the scan. [Source: Zooprocess]	Pixels	sample_descrip
acq_ysize	Vertical size of the scan. [Source: Zooprocess]	Pixels	sample_descrip
acq_xoffset	Scan frame X offset, from scanner factory calibration. [Source: Zooprocess]	Pixels	sample_descrip
acq_yoffset	Scan frame Y offset, from scanner factory calibration. [Source: Zooprocess]	Pixels	sample_descrip
acq_lut_color_balance	Indicates that the raw image normalisation will be done by Zooprocess. [Source: Zooprocess]	unitless	sample_descrip
acq_lut_filter	If there is a filter in the acquisition LUT (all should be "no"). [Source: Zooprocess]	unitless	sample_descrip
acq_lut_min	Minimum 16 bit coded grey level utilized for the 16 to 8 bit raw image conversion/normalisation by Zooprocess. [Source: Zooprocess]	pixel intensity	sample_descrip
acq_lut_max	Maximum 16 bit coded grey level utilized for the 16 to 8 bit raw image conversion/normalisation by Zooprocess. [Source: Zooprocess]	pixel intensity	sample_descrip
acq_lut_odrange	Optical Density range for the 16 to 8 bit raw image conversion/normalisation by Zooprocess (always 1.8). [Source: Zooprocess]	unitless	image_analysis
acq_lut_ratio	ratio applied to the acq_lut_max value for the 16 to 8 bit raw image conversion/normalisation by Zooprocess (always 1.15). [Source: Zooprocess]	unitless	sample_descrip
acq_lut_16b_median	Measured median grey level of the raw image. [Source: Zooprocess]	pixel intensity	sample_descrip

Database

Contribute Data

Dataset: ZooProcess and Ecotaxa Output for Zooplankton Mediated Aggregates
Deployment: AE2306

Dataset acquisition description

Dataset Processing Description

Database

Contribute Data

Dataset: ZooProcess and Ecotaxa Output for Zooplankton Mediated AggregatesDeployment: AE2306

Dataset acquisition description

Dataset Processing Description

Dataset: ZooProcess and Ecotaxa Output for Zooplankton Mediated Aggregates
Deployment: AE2306