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藻類群落結構掃描成像分析系統—浮標版CytoBuoy
日期:2017-03-27 14:21:35
主要(yao)功能




1. 專業分析浮游植物細(xi)(xi)胞,同時具備傳統流式細(xi)(xi)胞儀經(jing)典功能(neng)1.jpg
2. 可以掃描記(ji)錄各種光學信號(散射(she)、熒光)的動(dong)態(tai)變化
3. 可實(shi)現高(gao)頻(pin)、原位(wei)分析水體微(wei)生物群落及優(you)勢種變化
4. 可(ke)在完整的(de)藻類(lei)粒徑譜范圍(wei)內(nei)對生(sheng)物量進(jin)行線性(xing)評估
5. 可(ke)直接分析(xi)大(da)尺寸范圍的浮游藻(zao)類(lei)、團體結(jie)構,可(ke)現場(chang)分析(xi)微(wei)囊藻(zao)群(qun)體結(jie)構變(bian)化(hua)
6. 可(ke)(ke)調(diao)式PMT可(ke)(ke)根據檢測粒徑大小調(diao)節檢測器靈敏度
7. 流(liu)動成像技術可對感(gan)興(xing)趣感(gan)興(xing)趣的聚群進行圈門設定后專門拍(pai)照
8. 脈(mo)沖信號(hao)指紋圖譜技術(shu),圈門直觀方便,更真實反應細胞(bao)形態(tai)
9. 水下(xia)測(ce)量(liang)(CytoSub)可在整個真光層分析浮游(you)植物動態
10. 可整(zheng)合入浮(fu)標中或其它(ta)載體上進行(xing)在線監測(ce),可配合CTD對水體做剖(pou)面測(ce)量
11.實(shi)(shi)現實(shi)(shi)驗(yan)室遠程控制(zhi)基(ji)站式自動(dong)在(zai)線(xian)監(jian)測(ce),可實(shi)(shi)現完(wan)全自動(dong)檢測(ce),無人值守在(zai)線(xian)監(jian)測(ce)






測量參數(shu)




光學參(can)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(shu):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(ying)用領域




1. 海(hai)洋生態(tai)學與淡水生態(tai)學


2. 流域(yu)監測與管(guan)理


3. 海洋(yang)學與湖沼學


4. 有害(hai)藻華(HABs)預(yu)警


5. 微藻生物技術


6. 河(he)流、水庫、湖泊(bo)、海洋的監(jian)測與管理


7. 監測與管理


8. 水(shui)源地、水(shui)廠(chang)、污水(shui)處(chu)理廠(chang)的水(shui)質監(jian)測


9. 富營養化研究


10. 藻類環境生物學


11. 水(shui)產(chan)養(yang)殖








選購指南(nan):




一、便攜式浮游植物流式細胞儀(yi)CytoSense

系(xi)統組成:



流式細胞儀分(fen)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(yi)器采用碳素纖維外殼,防濺(jian)水(shui)設計,更輕便(<15kg),整(zheng)機安(an)裝(zhuang)于(yu)輕質鋁質框,帶高質量(liang)防震墊。包裝(zhuang)于(yu)便攜(xie)式航(hang)空箱內(nei)。
數據分析系統:含便攜(xie)式(shi)筆記本電腦,預裝(zhuang)數據(ju)采(cai)集軟件CytoUSB,和數據(ju)分析(xi)軟件CytoClus
批量處理數(shu)據(ju)分析軟件EasyClus : 需購(gou)買(mai)MatLab軟件配(pei)合使用
高速流動(dong)成像模塊:可(ke)選(xuan)。

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&nbsp;     便攜式(shi)浮游植物(wu)流式(shi)細胞儀(yi)        &nbsp;          Easyclus 粒徑(jing)分布圖                      Easyclus 散(san)點圖
系(xi)統組成:



主(zhu)機:淺(qian)水(shui)版(ban)Cytosub (水(shui)下20米(mi)),含CytoSense所有(you)基本配置

浮標模塊:包(bao)括浮標、太陽(yang)能電(dian)池板、充電(dian)電(dian)池、浮標燈、電(dian)子系統、無線傳輸裝置和(he)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(bian)的在CytoSense(室內用)和(he)CytoBuoy(在線監測)間轉換。
注意:野外在(zai)線(xian)監測時(shi)不僅(jin)僅(jin)限(xian)于(yu)以浮標作為平(ping)臺,其他平(ping)臺也(ye)可(ke),只要可(ke)以具備放置CytoSense的空(kong)間(jian)及供電即可(ke)。同(tong)時(shi),增加Bacterial staining module,可(ke)實現水(shui)體(ti)異養微生物自動(dong)染色和(he)在(zai)線(xian)分析,可(ke)在(zai)線(xian)檢測藻(zao)類(lei)、細(xi)菌、浮游動(dong)物及沉積物等顆(ke)粒。具體(ti)信(xin)息請來電咨詢。


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                       CytoBuoy 浮(fu)體

CytoBuoy通訊模式:無線通訊



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三、水下浮游植物流式細胞儀——CytoSub 


主機(ji):臺式機CytoSense是防(fang)濺水(shui)(shui)(shui)(shui)設計(ji),可(ke)以在野外使用(yong),但(dan)不能水(shui)(shui)(shui)(shui)下(xia)使用(yong)。CytoSense加上(shang)一個水(shui)(shui)(shui)(shui)下(xia)模塊(SUB MODULE)就(jiu)組成了水(shui)(shui)(shui)(shui)下(xia)式流式細胞(bao)儀CytoSub。
水下模塊(kuai):一個耐受200 m水深壓力的防水外(wai)殼,閥門和(he)進(jin)樣環路部分(包(bao)括循環泵(beng)),電子控制單元,數(shu)采,水下連(lian)接器和(he)支架。

cytosub 主機.jpg7.jpg





        &nbsp;     &nbsp;Cytosub 主(zhu)機               ;          CytoSense CytoSub 轉換
工作(zuo)模(mo)式一(yi):AUV搭載




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利用英國國家海洋(yang)中心AutoSubAUV搭載CytoSub

工作模(mo)式二(er):水下(xia)垂直剖面分析(xi)




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      &nbsp;                      與CTD結(jie)合一起測量

注意:此(ci)外,水下型浮游植(zhi)物流(liu)式細胞儀CytoSub可應(ying)用(yong)于浮標(biao),Ferrybox等監(jian)測平臺,在垂直剖面不同層位獲取浮(fu)游植物生(sheng)物量信息,對(dui)研究(jiu)微囊(nang)藻沉浮(fu)機(ji)制,浮(fu)游動物、水文(wen)、水質等因素對(dui)浮(fu)游植物生(sheng)態位影(ying)響提供數(shu)據依據。

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                          &nbsp;CytoSense 檢測對(dui)象

產(chan)地:荷(he)蘭 CytoBuoy



參考文獻
數據來(lai)源: Cytometry ,  Goolge scholar等,截(jie)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.&nbsp; [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]

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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.&nbsp; [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]







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