In-Situ Classification of Bloom-Forming Phytoplankton by Imaging Multivariate Optical Computing (IMOC)

通过成像多元光学计算 (IMOC) 对水华形成的浮游植物进行原位分类

• 批准号: 0623400
• 负责人: Timothy Shaw
• 金额: $ 51.45万
• 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: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0623400&HistoricalAwards=false
• 关键词: Situ; Classification; Bloom; Forming; Phytoplankton

The PIs propose to develop a simple system for the in situ identification and detection of three major phytoplankton bloom species in real time. The system will be based on simultaneous analysis of their size and their fluorescence excitation spectral characteristics using a new method called imaging multivariate optical computing (IMOC). This method will produce an optical "bar code" to discriminate between phytoplankton taxa. IMOC works by imaging through an optical filter uniquely designed for spectral analysis for a specific application such as phytoplankton discrimination. It requires that the investigators develop a database of phytoplankton fluorescence excitation spectra under varying growth conditions and employ canonical discriminant analysis to identify one or more discriminant functions to identify phytoplankton taxa. The PIs will use IMOC to combine instant spectroscopic analysis with a streak-camera-type microscopic imaging system to provide real-time or near-real-time classification. The method is ideal for field deployable instrumentation, making it an ideal addition to ocean observing platforms.Broader ImpactsIdentification of marine phytoplankton is a critical area in biological oceanography. Successful implementation of this research could go far towards lowering the ambiguities in the identification of marine phytoplankton, which could easily be automated for use from buoys and other remote platforms. An educational outreach program will be pursued through an existing program ("Rising Tide") that links high school teachers and undergraduate interns in summer research projects. Interns from South Carolina HBCU institutions would be targeted for this experience. Commercial development/private sector partnerships with academia would likely result from a successful project.

公众投资促进局建议发展一个简单的系统，以便在现场实时识别和检测三个主要的浮游植物水华物种。该系统将基于使用一种名为成像多变量光学计算(IMOC)的新方法同时分析它们的大小和荧光激发光谱特性。这种方法将产生一个光学“条形码”来区分浮游植物类群。IMOC的工作原理是通过专为特定应用(如浮游植物识别)的光谱分析而设计的滤光片进行成像。它要求研究人员建立不同生长条件下浮游植物荧光激发光谱的数据库，并使用典型判别分析来确定一个或多个判别函数，以识别浮游植物类群。PI将使用IMOC将即时光谱分析与条纹相机类型的显微成像系统相结合，以提供实时或接近实时的分类。这种方法是野外可部署仪器的理想选择，使其成为海洋观测平台的理想补充。广泛的影响海洋浮游植物的识别是生物海洋学中的一个关键领域。这项研究的成功实施可以大大减少海洋浮游植物识别的模糊性，浮游植物的识别可以很容易地从浮标和其他远程平台上使用。一项教育外展计划将通过现有的计划(“崛起的浪潮”)进行，该计划将高中教师和本科生在暑期研究项目中联系起来。来自南卡罗来纳州HBCU机构的实习生将成为这种体验的目标。一个成功的项目很可能会导致商业发展/私营部门与学术界的伙伴关系。