Sensors for Characterization of Phytoplankton Size and Taxonomic Composition Using Spectral Fluorescence Signatures and Imaging Multivariate Optical Computing

使用光谱荧光特征和成像多元光学计算表征浮游植物大小和分类组成的传感器

• 批准号: 0958831
• 负责人: Tammi Richardson
• 金额: $ 108.95万
• 依托单位: University South Carolina Research Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-15 至 2014-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0958831&HistoricalAwards=false
• 关键词: Sensors; Characterization; Phytoplankton; Size; Taxonomic

The PI's request funding take what they learned in the NSF funded demonstration project and develop a new field instrument for in situ measurement of phytoplankton abundance, size and taxonomic composition. The proposed instrument will be compact, inexpensive and will require low power. It will be suitable for broad deployment on fixed platforms or on mobile observing vehicles such as gliders or tethered or autonomous underwater vehicles. The technological basis, "imaging multivariate optical computing (IMOC)", uses multivariate discrimination of unique components of a cell's fluorescence excitation spectra to create interference filters (Multivariate Optical Elements, or "MOEs") that code for different phytoplankton species. Target phytoplankton cells are excited with a light source filtered through a rotating series of MOEs. The fluorescence response produces a classifying bar code in the image. Information on phytoplankton size is acquired by the instrument's use of imaging in a "streak camera" mode. Together, these will provide sufficient morphological and spectral analysis for classification and quantification. In this next phase of the research they will: 1) field test of the shipboard instrument using natural phytoplankton populations, 2) continue production of interference filters for a wider range of phytoplankton taxa (for which we have already identified discriminant functions), and 3) acquire fluorescence excitation spectra that capture a wider range of variability in ambient light, macronutrient, and micronutrient environment.Risk: an instrument that is successful in the simple lab environment may not be capable of discriminating amongst phytoplankton taxa in the more complex natural environment, or operations may be too difficult to allow commercialization.Reward: If successful, this instrument would revolutionize our ability to study the base of the ocean food web, with affordable sensors available for all ocean moorings, gliders and AUVs. Such in-situ observations would be transformative for ecosystem studies in coastal and open ocean settingsBroader Impacts: This instrument has potential applications in both biological and chemical oceanography. Outside the societal benefits, the broader educational impacts of this work include the training of two undergraduate students, three graduate students, one postdoctoral fellow, and community outreach lectures. The undergraduates will be chosen on a competitive basis as part of the University of South Carolina Marine Science Program's Summer Undergraduate Research Assistant Program. Students will have a major role in the project work-load and would be provided with cross-discipline training opportunities.

PI的请求资金采取了他们在NSF资助的示范项目中学到的东西，并开发了一种新的现场仪器，用于现场测量浮游植物的丰度、大小和分类组成。拟议的仪器将是紧凑的，廉价的，将需要低功率。它将适合于在固定平台或移动的观测载具上广泛部署，如滑翔机或系留或自主水下载具。技术基础“成像多元光学计算（IMOC）"使用细胞荧光激发光谱的独特组分的多元辨别来创建对不同浮游植物物种编码的干涉滤光片（多元光学元件，或“MOE”）。目标浮游植物细胞用通过旋转的一系列MOE过滤的光源激发。荧光响应在图像中产生分类条形码。关于浮游植物大小的信息是通过仪器使用“条纹相机”模式的成像获得的。总之，这些将提供足够的形态和光谱分析的分类和量化。在下一阶段的研究中，他们将：1）使用天然浮游植物种群对船上仪器进行现场测试，2）继续生产用于更广泛浮游植物分类群的干扰滤波器（我们已经确定了判别函数），以及3）获取荧光激发光谱，其捕获环境光、常量营养素和微量营养素环境中更广泛的变化。在简单的实验室环境中取得成功的仪器可能无法在更复杂的自然环境中区分浮游植物分类群，或者操作可能太困难而无法商业化。奖励：如果成功，该仪器将彻底改变我们研究海洋食物网基础的能力，为所有海洋系泊设备、滑翔机和自动潜水器提供价格实惠的传感器。这种现场观测将对沿海和开阔海洋环境的生态系统研究产生变革性影响。 该仪器在生物海洋学和化学海洋学中具有潜在的应用价值。在社会效益之外，这项工作更广泛的教育影响包括培训两名本科生，三名研究生，一名博士后研究员和社区外展讲座。本科生将在竞争的基础上选择作为南卡罗来纳州海洋科学计划的夏季本科生研究助理计划的一部分。学生将在项目工作量中发挥重要作用，并将提供跨学科培训机会。