主要功能
1. 專業分析浮游植物細胞，同時具備傳統流式細胞儀經典功能
2. 可以掃描記錄各種光學信號（散射、熒光）的動態變化
3. 可實現高頻、原位分析水體微生物群落及優勢種變化
4. 可在完整的藻類粒徑譜范圍內對生物量進行線性評估
5. 可直接分析大尺寸范圍的浮游藻類、團體結構，可現場分析微囊藻群體結構變化
6. 可調式PMT可根據檢測粒徑大小調節檢測器靈敏度
7. 流動成像技術可對感興趣感興趣的聚群進行圈門設定后專門拍照
8. 脈沖信號指紋圖譜技術，圈門直觀方便，更真實反應細胞形態
9. 水下測量(CytoSub)可在整個真光層分析浮游植物動態
10. 可整合入浮標中或其它載體上進行在線監測，可配合CTD對水體做剖面測量
11.實現實驗室遠程控制基站式自動在線監測，可實現完全自動檢測，無人值守在線監測
測量參數
光學參數：前向散射FWS、側向散射SWS，熒光散射FLR、 FLY、 FLO
形態參數：能同時獲得包括細胞和顆粒形態物理特性（數量、長度、大小、形態、粒度、色素、峰數等）、群體特征、脈沖圖譜等在內的9個拓撲學指標及最少45組參數
絕對計數：自然水體總顆粒計數，圈門后可集群計數及濃度計算，可實現鏈狀藻單細胞數計數功能
其他測量參數：分析體積、進樣速率等
應用領域
1. 海洋生態學與淡水生態學
2. 流域監測與管理
3. 海洋學與湖沼學
4. 有害藻華（HABs）預警
5. 微藻生物技術
6. 河流、水庫、湖泊、海洋的監測與管理
7. 監測與管理
8. 水源地、水廠、污水處理廠的水質監測
9. 富營養化研究
10. 藻類環境生物學
11. 水產養殖
選購指南：
一、便攜式浮游植物流式細胞儀CytoSense
系統組成：
流式細胞儀分析主機：相干高質量連續固態激光器，標配波長488nm, 可選波長445nm、635nm、640nm、660nm等，最多可配置7個檢測器（檢測通道含FWS L+R、SWS、YF、RF、OF）。
野外便攜式外殼：儀器采用碳素纖維外殼，防濺水設計，更輕便（<15kg）,整機安裝于輕質鋁質框，帶高質量防震墊。包裝于便攜式航空箱內。
數據分析系統：含便攜式筆記本電腦，預裝數據采集軟件CytoUSB,和數據分析軟件CytoClus
批量處理數據分析軟件EasyClus : 需購買MatLab軟件配合使用
高速流動成像模塊：可選。
便攜式浮游植物流式細胞儀
Easyclus 粒徑分布圖
Easyclus 散點圖
系統組成：
主機：淺水版Cytosub （水下20米），含CytoSense所有基本配置
浮標模塊：包括浮標、太陽能電池板、充電電池、浮標燈、電子系統、無線傳輸裝置和采樣管防水連接器等。根據用戶需要，也可擴展為易拆卸浮標模塊，這樣用戶可以非常方便的在CytoSense（室內用）和CytoBuoy（在線監測）間轉換。
注意：野外在線監測時不僅僅限于以浮標作為平臺，其他平臺也可，只要可以具備放置CytoSense的空間及供電即可。同時，增加Bacterial staining module，可實現水體異養微生物自動染色和在線分析，可在線檢測藻類、細菌、浮游動物及沉積物等顆粒。具體信息請來電咨詢。
CytoBuoy 浮體
CytoBuoy通訊模式：無線通訊
三、水下浮游植物流式細胞儀——CytoSub
主機：臺式機CytoSense是防濺水設計，可以在野外使用，但不能水下使用。CytoSense加上一個水下模塊（SUB MODULE）就組成了水下式流式細胞儀CytoSub。
水下模塊：一個耐受200 m水深壓力的防水外殼，閥門和進樣環路部分（包括循環泵），電子控制單元，數采，水下連接器和支架。
Cytosub 主機 CytoSense 與CytoSub 轉換
工作模式一：AUV搭載
利用英國國家海洋中心AutoSub型AUV搭載CytoSub
工作模式二：水下垂直剖面分析
與CTD結合一起測量
注意：此外，水下型浮游植物流式細胞儀CytoSub可應用于浮標，Ferrybox等監測平臺，在垂直剖面不同層位獲取浮游植物生物量信息，對研究微囊藻沉浮機制，浮游動物、水文、水質等因素對浮游植物生態位影響提供數據依據。
CytoSense 檢測對象
產地：荷蘭 CytoBuoy
參考文獻
數據來源： Cytometry , Goolge scholar等，截至2016年，共收集相關文獻近100篇。
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2. Goran Bakalar & Vinko Tomas, Possibility of Using Flow Cytometry in the Treated Ballast Water Quality Detection, Pomorski zbornik 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. Mansour, I. Leblond al.e: Invited Paper: Wireless Sensor Networks for Ecosystem Monitoring & Port Surveillance. (WSCN 2013)
5. Endymion D. Cooper , Bastian Bentlage al e: Metatranscriptome profiling of a harmful algal bloom.Harmful Algea 37(2014)75-83.
6. SERGIO A. COELHO-SOUZA, FáBIO V. ARAúJO al e: Bacterial and Archaeal Communities 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 phytoplankton 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 diatom 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. Donk V, E., Cerbin S, al e: The effect of a mixotrophic chrysophyte on toxic and colony-forming cyanobacteria. 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 phytoplankton assemblages in Mediterranean coastal waters recorded with an automated submerged flow cytometer. J Plankton Res 2008, 30:1027-1040. [Cytosub]
17. Thyssen, T. M, Garcia N, al. e: Sub meso scale phytoplankton distribution in the north east Atlantic surface waters determined with an automated flow cytometer. Biogeosciences Discuss 2008, 5:2471-2503. [Cytosub]
18. Dubelaar, J. GB, Casotti R, al. e: Phytoplankton and their analysis by flow cytometry. Flow Cytometry with Plant Cells 2007:287-322. [CytoBuoy]
19. Takabayashi, M., Lew K, al e: The effect of nutrient availability and temperature on chain length of the diatom, 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. Dubelaar, J. GB, Geerders PJF: Innovative technologies to monitor plankton dynamics. Sea Technol 2004, 45:15-21. [CytoSub]
22. Dubelaar, J. GB, Geerders PJF, al. e: High frequency monitoring reveals phytoplankton dynamics. J Environ Monit 2004, 6:946-952. [Cytosense]
23 Cunninghama, A., McKeea D, al e: Fine-scale variability in phytoplankton community 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. Dubelaar, J. GB, Jonker RR: Flow cytometry as a tool for the study of phytoplankton. Scientia Marina 2000, 64. [CytoBuoy]
26. Jonker R, Droben R, Tarran G, Medlin L, Wilkins M, Garcla L, zabala L, boddy l: Automated identification and characterisation of microbial populations using flow cytometry: the AIMS project. scientia marina 2000, 64:225-234. [Cyto]
27. Woodd-Walker, S. R, Gallienne CP, al e: A test model for optical plankton counter (OPC) coincidence 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 phytoplankton. Water SciTechnol 1995, 32:177-182. [Cytosense]
31. Jonker, R. R, G. B. J. Dubelaar, al. e: The European Optical Plankton Analyser: A high dynamic range flow cytometer. Scientia Marina 1994.
32. Dubelaar, G. B. J., A. Groenewegen ea: Optical plankton analyser: 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 analyser: A flow cytometer for plankton analysis, I: Design considerations. Cytometry 1989, 10:522-528. [OPA]
藻類群落結構掃描成像分析系統—浮標版CytoBuoy由上海澤泉科技股份有限公司
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