Colony counting/plankton analysis combined instrument

M600colony counting/Plankton analysis combined instrumentIt's Xunshu TechnologyLaunched to the market in 2020Multi functional biological monitoring device, setAutomated colony counting on petri dishes, intelligent identification and counting of planktonic organisms, and microscopic cell analysisAll in one. Provide intelligent image analysis tools for biological monitoring of water environment.

Plate colony count

lLight source control of "digital studio"

A professionally designed petri dish sample chamber that can accommodate culture dishesFog diffuse reflection lighting, floating dark field lighting, color transparent backlight lighting, ultraviolet excitation lightingTake extraordinary scientific grade exquisite photos.

The light source controller adopts a hidden suction door design, with6-way lighting selection switch, 4-channel stepless brightness adjustment, dual channel color temperature adjustment, 5-way color background selection.

l Suspended dark field illumination

The floating dark field is composed of dark field contour light and black background. Soft whiteLEDContour light provides uniform illumination to the colonies from the center to the edge of the petri dish, and the light almost penetrates the culture medium, forming bright colored colonies against a black background. The colonies form a high contrast with the culture medium, which can clearly outline the contours of the colonies.

lIntelligent colony counting on petri dishes

Seven quick statistics buttons, simple and easy to use,Simply rotate the mouse wheel to achieve continuous parameter changes and easily obtain the best statistical results.

Eight complex statistical algorithms adapted to the diversity and complexity of the agar plate, such as multiple adhesions, uneven culture medium, coexistence of impurities and colonies, pigment diffusion, and close proximity of colonies to the culture base color……

Total colony count determination

Nutritional agar, common bacterial colony characteristics: small colonies, neat edges, smooth surface, mostly round or oval shaped

Total coliform filter membrane count

Crystal Purple Neutral Red Bile Salt Agar（VRBA）Colony characteristics: purple red, with red bile salt precipitation rings around the colony, diameter0.5 mm左右

Count of heat-resistant coliform bacteria filter membrane

Bacterial metabolites and indicatorsTTC undergoes redox reaction, resulting in small bacterial colonies that appear red in color

Plankton analysis

lRich plankton database

Phytoplankton Database Covering seven major water systems in ChinaCommon freshwater algae in 28 key lakes and reservoirs, as well as common marine algae around the East China Sea, Yellow Sea, Bohai Sea, and South China Sea. Establish a four level search system consisting of "phylum," "order," "genus," and "species," with a focus on editing and categorizing introductions of planktonic algae, highlighting the characteristics of different phyla of planktonic plants, and enablingForm, structure, reproduction, ecology stick out a mile.

The zooplankton database consists of protozoa such as flagellates, protozoan carnivorous insects, protozoan ciliates, rotifers, branchiopods, copepods, etcComposed of 24 major categories, displayed in both Chinese and Latin, accompanied by written introductions, hand drawn illustrations, and numerous microscopic photographs of planktonic animals.

lMulti mode intelligent search and identification

Multidimensional progressive similarity algae searchadoptMachine DeepFace technology uses convolutional neural networks to extract deep features from any image. It can quickly and accurately detect the contours of unknown algal cells, extract feature information, match big data, and find the group of algae with the closest morphology from tens of thousands of image libraries, while prioritizing the display of common algae.

Easy to confuse algae identification:Users can select 2, 4, 6 or more algae with similar morphology, and quickly compare them on the same interface. Through typical combination feature maps and summary text, they can quickly grasp the key differences between them and guide themselves to observe the differentiated detailed features.

Morphological retrieval of "typical combination association"Based on morphological similarity and gradient, select real typical algal cell images, combine and classify them, and combine the structural characteristics of cells or populations, such as flagella, pigment bodies, patterns, gelatinous covers, etc., to achieve accurate and fast morphological retrieval.

lClassification and counting of plankton, automatic sorting of dominant species

Plankton process counting: continuous acquisition200 field of view images, edit the counting table, click to mark different species, automatically accumulate the same genus and species in multiple fields, classify and count different species, accumulate the total number, automatically sort dominant species, and analyze the proportion of dominant groups.

The statistical information of plankton is stored in electronic records to ensure the integrity of the data, which helps to standardize and paperless environmental monitoring, greatly improving work efficiency and in line with the development trend of laboratory testing. The statistical data is sorted by dominant species, including: total count, single-cell volume, percentage, algal density, abundance, dominance, total algal volumeShannon index, species evenness index, carbon biomass, nitrogen biomass, total carbon biomass.

lAutomatic counting of single-cell microalgae

Contains seven image segmentation algorithmsDynamic automatic counting "is suitable for rapid determination of cell concentration in pure cultured energy algae, medicinal or edible microalgae.

The image shows the automatic segmentation and counting of Chlamydomonas reinhardtii

Microscopic observation, measurement, and analysis of cells

The system provides specialized microscopic analysis tools with functions such as dynamic microscopic observation, automatic cell counting, automatic morphological classification measurement, image processing, biomass calculation, etc., which can be used for the analysis of activated sludge biological phases.M600 is equipped with two microscope cameras for different purposes，20 million pixel large area array (1 inch) scientific grade color digital camera used for large field of view observation under visible light; High sensitivity cameras are used forJia Di flagellate、CryptosporidiumFluorescence imaging analysis.

Main functions and technical indicators

1Colony digital imaging

1. lighting system

ØFully enclosed steel aluminum alloy chassis（32 × 34 × 46cm): Precise and sturdy, ensuring light tightness

ØFlat dish sample compartment: aluminum alloy frame, pull-down partition window, eliminates environmental stray light interference, blocks UV leakage, and prevents dust from entering

ØLingtong backlight illumination:High density whiteLEDArray to form uniform and bright white transmitted light, ensuring uniform illumination at the edges and center of the culture dish

ØCompound floating dark field illumination:white lightLEDCompared to blue lightLED interweavingHybrid, broadband retroreflection, forming a blue background in the universe

ØMisty diffuse reflection lighting

a)96 LED arrays and nano reflective materials form an embedded fog light system, 360 ° continuous diffuse reflection highlights the color and texture of bacterial colonies, eliminating light spots and halos formed by refraction in glass culture dishes.

b)Color temperature variation range:3100K－5800KIllumination range50-7000 Lux

c)LEDlifespan≧20000 hr

ØUV light source:254nm is used for cavity disinfection and UV mutagenesis

ØLight source controller

a)Invisible suction control panel,5-way lighting selection switch, 4-channel stepless brightness adjustment, dual channel color temperature adjustment

b)Free switching and selection of single mode lighting or combined mode lighting

2. digital imaging

ØStandard definition industrial fixed focus lens:8mm、 3.0 mega-pixel、1/2＂TheDistortion<1％TheF1.4～F32TheC-Mount

ØProfessional typeCMOS camera:chip size1/2.4＂；CMOSPhysical pixels8.5 million,3328x2548； Single pixel rulerinch1.67x1.67µm

IIColony counting module

1. Rapid colony counting

ØRoller parameter adjustment statistics（4 types: homogeneous petri dish, uneven background, small bacterial colonies, colored background

ØOne click response statistics（3 types: monochrome statistics, mold statistics, and trans statistics

2. Advanced colony statistics

ØDynamic adjustment statistics: The statistical results can be dynamically adjusted and corrected to quickly obtain the best statistical effect.

ØDeviation estimation statistics: suitable for situations with multiple and complex colony colors.

ØLevel set multi model algorithm: search operation, obtain the best image segmentation effect, adapt to background changes in the culture medium

ØSpecific colony statistics: Identify specific colonies based on their color, size, and contour characteristics

ØTrans statistics: suitable for extremely complex colony types and uniform culture medium background

ØRemoval of miscellaneous bacteria and impurities: Automatic removal of miscellaneous bacteria and impurities based on differences in morphology, size, and color

3. Basic colony counting function

ØType of petri dish: pouring, coating, membrane filtration3M paper sheet

ØWhole dish colony count: Count the total number of colonies and count them according to25 size classification display

ØRegion selection statistics: You can choose circular, rectangular, or arbitrarily delineated regions for statistics

ØMulti domain parallel statistics: synchronous statistics of multiple regions at once; multi-regionHollow out statistics

ØDiameter classification statistics: Set the diameter range and count specific sizes of colonies

ØMouse click statistics: Quickly mark and add colonies, suitable for counting colonies at the edge of culture dishes

ØColony adhesion segmentation: Automatically segment colonies that adhere to each other, and users can choose to segment or not segment chain colonies

4. Grid filter membrane and3M test piece

ØBlack solid line grid, one click statistics

Ø3M total bacterial count test piece, 3M test piece: one click statistics

Ø3M coliform test strip, 3M Escherichia coli/coliform rapid test strip: one click statistics+manual selection

5. advanced tools

ØGrid cleaning: eliminate background interference in the filter membrane grid

ØManual counting correction: adding or deleting colonies

ØExclude contaminated areas: Use the mouse to outline any contaminated area and automatically remove the bacterial count from the contaminated area

ØBackground text elimination: automatically eliminates marker interference

ØArtificial adhesion segmentation: manually segmenting multiple adhesive colonies

ØAutomatic parameter conversion: Input the diameter of the culture dish and sample dilution to achieve automatic conversion

ØText and graphic annotation: various drawing tools and embedded Chinese and English text

6. Calibration and Measurement

ØInstrument calibration: The instrument comes with built-in calibration and manual correction calibration

ØOne click rapid measurement: One click determination of large bacterial colonies, suitable for single colony analysis of fungi and actinomycetes

ØAutomatic measurement of the entire dish: analysis of the equivalent diameter, area, length, circumference, and roundness of the entire dish colony

ØMulti directional ruler measurement, manual precise measurement: length, angle, radian, area, arc, arbitrary curve

IIIData Security and Management

ØMultiple architectures of "management, operation, and review" are established, with separate functions and permissions to ensure data security, integrity, and authenticity

ØSingle dish data recording: measured colony count, area converted colony count, dilution converted colony count, morphological parameters of each colony, size grading statistics, regional statistics

ØElectronic data recording: sample source, number, dilution, petri dish image, recognition effect, count value, statistical tools used, parameter settings, correction status

ØAutomatic storage of electronic data orPrint and output in PDF or Excel format

4Microscopic imaging of plankton

ØLarge array scientific research grade color digital camera：SONY 1Inch imageCMOSsensor；20 million pixels;G light sensitivity462mv with 1/30s；FPS/Resolution：：15@5440x3648；50@2736x1824；60@1824 ×1216； time of exposure:0.1ms~15s；USB3.0

ØHigh sensitivity research grade color digital camera:SONY 1/1.2'CMOSsensor；8.3 million pixels;G light sensitivity2188mv with 1/30s

Ømicroscopic imaging：Real time dynamic observation and rapid capture of ultra large field of view microscopy images, batch image saving

Ø3D depth fusion:Quickly fuse different focal planes to solve the problem of local blurring caused by different liquid layers of algal cell distribution, and obtain panoramic deep and high-definition images of algal cells

ØSuper vision stitching:Multi view horizontal and vertical automatic splicing

5Plankton database

1. Algae Expert Database

ØComposed of exquisite color micrographs, hand drawn images, and textual introductions, it forms freshwater and marine algae reservoirs; Covering seven major water systems in ChinaFreshwater algae from 28 key lakes and reservoirs, as well as marine algae around the East China Sea, Yellow Sea, Bohai Sea, and South China Sea.

2. Zooplankton database

ØFrom protozoan flagellates, protozoan carnivorous insects, protozoan ciliates, rotifers, branchiopods, copepods, etcComposed of 24 major categories, displayed in both Chinese and Latin, accompanied by written introductions, hand drawn illustrations, and numerous microscopic photographs of planktonic animals.

VIPlankton identification

1. Intelligent identification of algae--Quick Search Module

ØMultidimensional progressive similarity algae search:Automatic and intelligent algae cell pattern recognition tool,3-5 seconds to achieve: detecting unknown algal cell contours, extracting feature information, matching big data, accurately identifying possible algae with similar morphology, and synchronously displaying the most similar common algae through the "priority selection" option.

ØIdentification of easily confused algae:Design a method for inexperienced experimenters to screen multiple algae that are easily confused due to their similar morphology, and quickly compare them on the same interface. Through typical feature puzzles and summary text, quickly grasp the key differences.

ØMorphological retrieval of "typical combination association":By using graphic language, combining associations, and incorporating structural features of cells or populations, precise and efficient morphological retrieval can be achieved. Equipped with features such as multiple selection, freshwater and ocean storage, and easy browsing, beginners can quickly master them.

ØFourth level taxonomic search:Featuring exquisite color micrographs, hand drawn images, and textual introductions Forming freshwater and marine algae reservoirs; pressExpand the search at four levels: door, order, genus, and species.

ØColumn Editing:Name and classification status of phytoplankton Form, structure, reproductive ecology It's clear at a glance.

ØGeneral query:Keyword search (based on the feature words in the algal cell text description); Common algae queries (algal blooms, red tides, toxic algae); Name query (Chinese name, Latin name)

2. Assisted identification of planktonic animals

ØSearch by Chinese or Latin name

ØSelect the category and genus, and display all planktonic animals under that category

7Plankton Counting and Analysis

1. Process based counting of planktonic organisms

ØClassification and statistics of plankton: Various organisms are marked with color circles of different colors and sizes, clicked by category, and automatically accumulated for counting

ØAutomatic classification and recognition of floating algae: achieved in one go through artificial intelligence learningAutomatic classification, recognition, and counting of 200 view specific algae.

ØAlgae Total Count Statistics: Automatically accumulate the total number of various organisms in the sample, automatically sort dominant species, sort by phylum, and analyze the percentage of dominant community composition

Øautomatic calculation: Algae densitybiomass、Shannon-Wiener indexspeciesUniformity indexAdvantage and abundance

ØGel population analysis: automatic recognition and counting of daughter cells in the population, especially suitable for counting analysis of Microcystis aeruginosa

ØChain like body analysis: used to estimate the number of daughter cells in a single filament or chain like body

2. Automatic counting of single-cell microalgae

ØDynamic automatic counting:Seven segmentation algorithms adapted to changes in single-cell microalgae and imaging backgrounds

ØMulti functional cell counting: Based on a universal, multi-channel, and color matching segmentation algorithm, cells of specific colors, sizes, and contours can be selected for automatic counting or reverse exclusion of cells and impurities.

3. Measurement and biomass analysis

ØMicroscopic measurement: can choose between transparent and opaqueTwo types of rulers, or directly click the mouse to draw lines to measure biological cells

ØBiomass analysis: automatically calculate biomass based on mathematical models of plankton morphology

8image processing

ØAdaptive Enhancement: Resolution Enhancement Processing to Highlight Microscopic Features of Algae Cells

ØImage adjustment: Image brightness, contrast, saturationRGBThree color arbitrary adjustment, conversion of grayscale and negative phase diagrams

ØImage compensation: Various mathematical methods such as linear compensation, logarithmic compensation, Bell compensation, etc. are used to compensate for the distorted parts of the image, making the image clearer

ØImage sharpening: By enhancing the high-frequency components of the image, the edges of algae become clearer

ØImage smoothing: Through image smoothing processing, the background of the image is made uniform

ØImage filtering: Gaussian filtering, low-pass filtering, median filtering, etc6Various filtering methods effectively improve image clarity

ØEdge detection: Two detection methods, three operators combined with multiple detection options to extract algal contours more accurately

ØMorphological processing: Nonlinear mathematical morphological processing such as corrosion, expansion, opening, and closing

9Experimental data security

ØMulti account hierarchical management, administrators and experimenters have different permissions to avoid tampering with experimental data

ØElectronic record keeping method is used to save the database and ensure the integrity of the data

ØDatabase: Automatically save each batch of micrographs, statistical identification, and statistical data

ØAnnotation: Any text or size annotation can be made on the captured images of planktonic cells

ØReport editing and printing: providing report writing templates, text input, and print preview

ØData export: export statistical data and images toEXCELorPDF file

10Instrument specifications and configuration

ØM600 colony count/Plankton analysis analyzer mainframe1platform

ØColony analysis software, algae analysis softwareMIC analysis software, zooplankton analysis software

ØLenovo all-in-one computer:Dual core four threadCPU/4G memory/1T hard drive/23 'high-definition screen, Windows 10 system

ØMicroscopic photography research grade color camera2 of them

ØUser optional: microscope and camera adapter