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藻类群落结构扫描成像分析系统—浮标版CytoBuoy

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上海泽泉科技股份有限公司更新时间：2024-04-23 15:51:02

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详细介绍

主要功能
1. 专业分析浮游植物细胞，同时具备传统流式细胞仪经典功能
2. 可以扫描记录各种光学信号（散射、荧光）的动态变化
3. 可实现高频、原位分析水体微生物群落及优势种变化
4. 可在完整的藻类粒径谱范围内对生物量进行线性评估
5. 可直接分析大尺寸范围的浮游藻类、团体结构，可现场分析微囊藻群体结构变化
6. 可调式PMT可根据检测粒径大小调节检测器灵敏度
7. 流动成像技术可对感兴趣感兴趣的聚群进行圈门设定后专门拍照
8. 脉冲信号指纹图谱技术，圈门直观方便，更真实反应细胞形态
9. 水下测量(CytoSub)可在整个真光层分析浮游植物动态
10. 可整合入浮标中或其它载体上进行在线监测，可配合CTD对水体做剖面测量
11.实现实验室远程控制基站式自动在线监测，可实现完全自动检测，无人值守在线监测

测量参数
光学参数：前向散射FWS、侧向散射SWS，荧光散射FLR、 FLY、 FLO
形态参数：能同时获得包括细胞和颗粒形态物理特性（数量、长度、大小、形态、粒度、色素、峰数等）、群体特征、脉冲图谱等在内的9个拓扑学指标及最少45组参数
JD计数：自然水体总颗粒计数，圈门后可集群计数及浓度计算，可实现链状藻单细胞数计数功能
其他测量参数：分析体积、进样速率等

应用领域
1. 海洋生态学与淡水生态学
2. 流域监测与管理
3. 海洋学与湖沼学
4. 有害藻华（HABs）预警
5. 微藻生物技术
6. 河流、水库、湖泊、海洋的监测与管理
7. 监测与管理
8. 水源地、水厂、污水处理厂的水质监测
9. 富营养化研究
10. 藻类环境生物学
11. 水产养殖

选购指南：
一、便携式浮游植物流式细胞仪CytoSense
系统组成：
流式细胞仪分析主机：相干高质量连续固态激光器，标配波长488nm, 可选波长445nm、635nm、640nm、660nm等，最多可配置7个检测器（检测通道含FWS L+R、SWS、YF、RF、OF）。
野外便携式外壳：仪器采用碳素纤维外壳，防溅水设计，更轻便（<15kg）,整机安装于轻质铝质框，带高质量防震垫。包装于便携式航空箱内。
数据分析系统：含便携式笔记本电脑，预装数据采集软件CytoUSB,和数据分析软件CytoClus
批量处理数据分析软件EasyClus : 需购买MatLab软件配合使用
高速流动成像模块：可选。





便携式浮游植物流式细胞仪		Easyclus 粒径分布图		Easyclus 散点图
系统组成：
主机：浅水版Cytosub （水下20米），含CytoSense所有基本配置
浮标模块：包括浮标、太阳能电池板、充电电池、浮标灯、电子系统、无线传输装置和采样管防水连接器等。根据用户需要，也可扩展为易拆卸浮标模块，这样用户可以非常方便的在CytoSense（室内用）和CytoBuoy（在线监测）间转换。
注意：野外在线监测时不仅仅限于以浮标作为平台，其他平台也可，只要可以具备放置CytoSense的空间及供电即可。同时，增加Bacterial staining module，可实现水体异养微生物自动染色和在线分析，可在线检测藻类、细菌、浮游动物及沉积物等颗粒。具体信息请来电咨询。


		CytoBuoy 浮体
CytoBuoy通讯模式：无线通讯


三、水下浮游植物流式细胞仪——CytoSub
主机：台式机CytoSense是防溅水设计，可以在野外使用，但不能水下使用。CytoSense加上一个水下模块（SUB MODULE）就组成了水下式流式细胞仪CytoSub。
水下模块：一个耐受200 m水深压力的防水外壳，阀门和进样环路部分（包括循环泵），电子控制单元，数采，水下连接器和支架。



	Cytosub 主机		CytoSense 与CytoSub 转换
工作模式一：AUV搭载



		利用英国国家海洋中心AutoSub型AUV搭载CytoSub
工作模式二：水下垂直剖面分析


		与CTD结合一起测量
注意：此外，水下型浮游植物流式细胞仪CytoSub可应用于浮标，Ferrybox等监测平台，在垂直剖面不同层位获取浮游植物生物量信息，对研究微囊藻沉浮机制，浮游动物、水文、水质等因素对浮游植物生态位影响提供数据依据。


		CytoSense 检测对象
产地：荷兰 CytoBuoy

参考文献

数据来源： Cytometry , Goolge scholar等，截至2016年，共收集相关文献近100篇。

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

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]

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