CytoBuoy field monitoring phytoplankton flow cytometer - Freshwater Ecological Monitoring - Robotics and AI,Phenotype and modern biological breeding,Ecological environment-Zealquest Scientific Technology Co., Ltd.

Main functions
1. Professionally analyze phytoplankton cells, and also has the classic functions of traditional flow cytometry
2. It can scan and record the dynamic changes of various optical signals (scattering, fluorescence)
3. High frequency and in-situ analysis of changes in water microbial communities and dominant species can be achieved
4. Biomass can be linearly evaluated within the complete algae particle size spectrum
5. The structure of phytoplankton algae and group in large sizes can be directly analyzed, and the changes in the microcystis population structure can be analyzed on-site.
6. Adjustable PMT can adjust the detector sensitivity according to the size of the detection particle size
7. Mobile imaging technology can set up circles and take photos after specializing in groupings.
8. The original pulse signal fingerprinting technology is intuitive and convenient for circle gates, and it is more realistic in response to cell morphology.
9. Underwater measurement (CytoSub) can analyze phytoplankton dynamics throughout the eutrophication layer
10. It can be integrated into the float or on other carriers for online monitoring, and can be used to perform cross-sectional measurement of water bodies with CTD.
11. Realize laboratory remote control base station automatic online monitoring, which can achieve full automatic detection and unattended online monitoring

Measurement parameters
Optical parameters:Forward scattering FWS, side scattering SWS, fluorescence scattering FLR, FLY, FLO
Morphological parameters:It can obtain 9 topological indicators and at least 45 sets of parameters including physical characteristics of cell and particle morphology (quantity, length, size, morphology, particle size, pigment, peak number, etc.), population characteristics, pulse map, etc.
Absolute Count:The total particle count of natural water bodies can be counted in clusters and concentration calculation after the circle gate, which can realize the counting function of single cell counting of chain algae
Other measurement parameters:Analyze volume, injection rate, etc.

Application areas
1. Marine ecology and freshwater ecology
2. Watershed monitoring and management
3. Oceanography and Lake Science
4. Early warning of harmful algae blooms (HABs)
5. Microalgae Biotechnology
6. Monitoring and management of rivers, reservoirs, lakes and oceans
7. Monitoring and Management
8. Water quality monitoring of water sources, water plants, and sewage treatment plants
9. Eutrophication Research
10. Algae Environmental Biology
11. Aquaculture

Purchase Guide:
1. Portable phytoplankton flow cytometry CytoSense
System composition:
Flow cytometry analysis host:Coherent high-quality continuous solid-state laser, standard wavelength 488nm, optional wavelength 445nm, 635nm, 640nm, 660nm, etc.,Up to 7 detectors can be configured (the detection channel includes FWS L+R, SWS, YF, RF, OF).
Wild portable case:The instrument adopts a carbon fiber shell, which is splash-proof and is lighter (<15kg). The whole machine is installed in a lightweight aluminum frame with high-quality shock-proof pad.Packed in a portable air box.
Data analysis system:Includes portable laptop, pre-installed data acquisition software CytoUSB, and data analysis software CytoClus
EasyClus batch processing data analysis software: Need to purchase MatLab software to use
High-speed flow imaging module:Optional.





Portable phytoplankton flow cytometer		Easyclus particle size distribution diagram		Easyclus scatter plot
System composition:
Host:Shallow water version of Cytosub (20 meters underwater), including all basic configurations of CytoSense
Float module:Including floats, solar panels, rechargeable batteries, float lamps, electronic systems, wireless transmission devices and sampling tube waterproof connectors, etc.According to user needs, it can also be expanded to easily disassembled float modules, so that users can easily convert between CytoSense (indoor use) and CytoBuoy (online monitoring).
Note: In the field online monitoring, it is not limited to using floats as a platform, but other platforms are also available, as long as they can have space to place CytoSense and power supply.At the same time, adding Bacterial staining module can realize automatic staining and online analysis of heterotrophic microorganisms in water, and can detect particles such as algae, bacteria, zooplankton and sediments online.For specific information, please call us for consultation.


		CytoBuoy Float
CytoBuoy communication mode: wireless communication


3. Underwater phytoplankton flow cytometry——CytoSub
Host:The desktop CytoSense is a splash-resistant design that can be used in the wild, but not underwater.CytoSense and an underwater module (SUB MODULE) form the underwater flow cytometer CytoSub.
Underwater module: A waterproof housing that withstands a 200 m water depth pressure, valve and injection loop section (including circulation pump), electronic control unit, digital feed, underwater connector and bracket.



	CY to BHost		CY to senseandCY to subConvert
Working mode 1: AUV equipped



		Utilize the UK National Oceanic Centreauto subtypeA UVEquippedCY to sub
Working mode 2: Underwater vertical profile analysis


		andCT DCombined to measure
Note: In addition, underwater phytoplankton flow cytometryCY to subCan be applied to floats,ferry boxThe monitoring platforms also obtain phytoplankton biomass information at different levels of the vertical profile, providing a data basis for studying the ups and downs of microcysticus, and the impact of factors such as zooplankton, hydrology, and water quality on the phytoplankton ecological niche.


		CY to senseDetect objects
Origin: NetherlandsCY to buoy

References

Data source: Cytometry, Goolge scholar, etc. As of 2016, nearly 100 related documents have been collected.

1.Simon Bonato a, Elsa Breton , al e: Spatio-temporal patterns in physitoplankton assembly ininshore–offshore gradients using flow cytometry: A case study in the eastern English Channel, Journal of Marine Systems 2016,76-83.[CytoSense]

2.goranb Kararan & Vin koto, possibility of using flow CY tome try int and treated balllast water quality detection, pom or ski live broadcast can you watch 51 (2016), 43-55

3.Quan Zhou, Wei Chen, al e: A flow cytometer based protocol for quantitative analysis of bloom-forming cyanobacteria (Microcystis) in lake sediments, Journal of Environmental Sciences 2012, 24(9) 1709–1716

4.A. man soul, i. LE blond AL.Oh: invited paper: wireless sensor networks for ecosystem monitoring & port survey. (WS cn 2013)

5.Endymion D. Cooper , Bastian bent rag ale: meta transcript o profiling of ah harmonious al bloom.harmful A two A 37 (2014) 75-83.

6.SERGIO A. COELHO-SOUZA, FÁBIO V. ARAÚJO al e: Bacterial and Archaeal Community Variability Associated with Upwelling and Anthropogenic Pressures in the Protection Area of Arraial do Cabo (Cabo Frio region - RJ). Anais da Academia Brasileira de Ciências (2015)87(3):1737-1750

7. Malkassian, A., D. Nerini, al. e: Functional analysis and classification of physitoplankton based on data from an automated flow cytometer. Cytometry Part A 2011, 94A:263-275. [Cytosense]

8. Thyssen, M., B. Beker, al. e: Phytoplankton distribution during two contrasted summers in a Mediterranean harbour: combining automated submersible flow cytometry with conventional techniques. Environmental Monitoring and Assessment 2011, 173:1-16.

9. Thyssen, M., Denis M: Temporal and Spatial High-Frequency Monitoring of Phytoplankton by Automated Flow Cytometry and Pulse-Shape Analysis. Springer Netherlands 2011:293-298.

10. Vidoudez, C., J. C. Nejstgaard, al. e: Dynamics of Dissolved and Particulate Polyunsaturated Aldehydes in Mesocosms Inoculated with Different Densities of the Diatom Skeletonema marinoi. Marine Drugs 2011, 9: 345-358.

11. Hansen, B. W., H. H. Jakobsen, al. e: Swimming behavior and prey retention of the polychaete larvae Polydora ciliata. Journal of Experimental Biology 2010:3237-3246.

12. Pereira GC, Figuiredo ARd, Jabor PM, Ebecken1 NFF: Assessing the ecological status of plankton in Anjos Bay: a flowcytometry approach. Biogeosciences Discuss 2010, 7:6243–6264. [cytobuoy]

13. Barofsky, A., Simonelli P, al e: Growth phase of the diagnosis Skeletonema marinoi influences the metabolic profile of the cells and the selective feeding of the copepod Calanus spp. J Plankton Res 2009, 32:263-272. [CytoBuoy]

14. Don kV, E., CER Bin S, ale: the effect of Ami XO trophic C Sophy special on toxic and colony-forming as o bacteria. freshwater biology 2009, 54:1843-1855.

15. Pereira, C. G, Granato A, al. e: Virioplankton Abundance in Trophic Gradients of an Upwelling Field. Brazilian Journal of Microbiology 2009, 40:857-865. [CytoBuoy]

16. Thyssen, M., Mathieu D, al. e: Short-term variation of physitoplankton assembly in Mediterranean coastal waters recorded with an automated submerged flow cylinder. J Plankton Res 2008, 30:1027-1040. [Cytosub]

17. Thyssen, T. M, Garcia N, al. e: Sub meso scale physitoplankton distribution in the north east Atlantic surface waters determined with an automated flow cylinder. Biogeosciences Discuss 2008, 5:2471-2503. [Cytosub]

18. dub Ela AR, J. GB, CAS Ott IR, Ali. Oh: physitoplankton and their analysis by flow member Tom E try. flow CY tome try with plant cells 2007:287-322. [CY to buoy]

19. Takabayashi, M., Lew K, al e: The effect of nutrient availability and temperature on chain length of the diagnosis, Skeletonema costatum. J Plankton Res 2006, 28:831-840. [CytoSense]

20. Takabayashi, M., Wilkerson FP, al. e: Response Of Glutamine Synthetase Gene Transcription And Enzyme Activity To External Nitrogen Sources In The Diatom Skeletonema Costatum (Bacillariophyceae). J Phycol 2005, 41:84-94. [Cytobuoy]

21. dub Ela AR, J. GB, gee RD and SP JF: innovative technologies to monitor plankton dynamics. sea Technol 2004, 45:15-21. [CY to sub]

22. dub Ela AR, J. GB, gee RD and SP JF, Alibaba. Oh: high frequency monitoring reveals physitoplankton dynamics. J environment Mon IT 2004, 6:946-952. [CY to sense]

23 Cunninghama, A., McKeea D, al e: Fine-scale variability in physics structure and inherent optical properties measured from an autonomous underwater vehicle. J Mar Syst 2003, 43:51-59.

24. Dubelaar, J. GB, Gerritzen PL: CytoBuoy: a step forward towards using flow cytometry in operational oceanography. Sci Mar (Barc) 2000, 64:255-265. [CytoBuoy]

25. dub Ela AR, J. GB, Jon Kerr R: flow members Tom E try ASA tool fort and study of physitoplankton. SCI Ent Tia Marina 2000, 64. [CY to buoy]

26. Jonker R, Droben R, Tarran G, Medlin L, Wilkins M, Garcla L, zabala L, bodydy l: Automated identification and characterization of microbial populations using flow cytometry: the AIMS project. scientistia marina 2000, 64:225-234. [Cyto]

27. Woodd-Walker, S. R, Gallienne CP, al e: A test model for optical plankton counter (OPC) conflict and a comparison of OPC-derived and conventional measures of plankton abundance. J Plankton Res 2000, 22:473-483.

28. Dubelaar, J. GB, Gerritzen PL, al e: Design and first results of CytoBuoy: A wireless flow cytometer for in situ analysis of marine and fresh waters. Cytometry 1999, 37:247-254. [CytoBuoy]

29. Wilkins, F. M, Boddy L, al e: Identification of Phytoplankton from Flow Cytometry Data by Using Radial Basis Function Neural Networks." Appl Environ Microbiol 1999, 65:4404-4410.

30. Jonker, R. R, Meulemans JT, al e: Flow cytometry: A powerful tool in analysis of biomass distributions in physitoplankton. Water SciTechnol 1995, 32:177-182. [Cytosense]

31. Jon Guest, R. R, G. B. J. Dub Ela AR, Ali. Oh: the European optical plankton Ana Louise: A high dynamic range flow to meter. SCI Entia Marina 1994.

32. Dubelaar, G. B. J., A. Groenewegen ea: Optical plankton analyzer: a flow cytometer for plankton analysis, II: Specifications. Cytometry 1989, 10:529-539. [OPA]

33. Peeters, J. C. H., G. B. J. Dubelaar, al e: Optical plankton analyzer: A flow cytometer for plankton analysis, I: Design considerations. Cytometry 1989, 10:522-528. [OPA]