SBIR Phase I: Cost-effective, portable and fast platform for automated characterization of aquatic microorganisms and other particles for aquaculture, public health and marine res

SBIR 第一阶段：经济高效、便携式和快速的平台，用于自动表征水产养殖、公共卫生和海洋资源中的水生微生物和其他颗粒

• 批准号: 1843093
• 负责人: Maxim Batalin
• 金额: $ 22.49万
• 依托单位: LUCENDI, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-01 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1843093&HistoricalAwards=false
• 关键词: SBIR; Phase; Cost; effective; portable

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a cost-effective high-performance platform to monitor and characterize phytoplankton and other microorganisms in water. Some of these aquatic microorganisms may be toxic or even fatal resulting in significant public health concerns (such as recent "red tide" events in Florida, USA) and drastic economic consequences (i.e. deadly effects of harmful algal blooms on the aquaculture industry). The current state of the art in monitoring technology includes laborious and expensive manual sample collection and evaluation using a benchtop microscope or optical digital imaging system. In contrast, the proposed platform will be transformative by enabling low-cost, portable and fast monitoring and automated characterization of aquatic microorganisms. Therefore, this platform will revolutionize monitoring of aquatic microorganisms and, being low cost, it will enable a much wider application of the technology to other markets. Some of these future applications include more efficient biofuels research and development (via algae monitoring), marine biology science and education, general monitoring of particles and pathogens at the water treatment facilities, production algae monitoring. Therefore, the potential societal impact and commercial potential of the proposed technology is transformative.The proposed project aims to develop and evaluate a portable, rapid, durable and environmentally-stable imaging flow-cytometry technology that will automatically monitor microorganisms, such as phytoplankton and pathogens present in the flowing water, and will be capable of specific classification. Existing optics-based flow-cytometry solutions are expensive and not durable for field use. Unlike lab-based flow cytometers or hand-held assays, the proposed system will not rely on reagents or labeling, and therefore will not need an expert/professional, and will keep the evaluated water unchanged. Thus, it can be installed for continual unattended operation and will be much more cost-effective per test due to elimination of an expert's time, costly reagents and fluorophores. Furthermore, the proposed system will also be integrated with a machine learning engine capable of automated identification of microorganisms as well as other micro-objects of interest. Finally, the proposed system will be evaluated on pre-collected samples of local coastal ocean water to determine the presence of three example types of phytoplankton microorganisms and to provide statistical distribution of all of the detected micro-objects. Therefore, the proposed system will be transformative and provide an innovative and unique capability to expediently survey samples of water and automatically characterize identified micro objects.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该小企业创新研究 (SBIR) 第一阶段项目的更广泛影响/商业潜力是开发一个具有成本效益的高性能平台，用于监测和表征水中的浮游植物和其他微生物。其中一些水生微生物可能有毒甚至致命，导致严重的公共卫生问题（例如美国佛罗里达州最近的“赤潮”事件）和严重的经济后果（即有害藻华对水产养殖业的致命影响）。目前最先进的监测技术包括使用台式显微镜或光学数字成像系统进行费力且昂贵的手动样本收集和评估。相比之下，所提出的平台将通过实现水生微生物的低成本、便携式和快速监测和自动表征来实现变革。因此，该平台将彻底改变水生微生物的监测，并且成本低廉，将使该技术能够更广泛地应用于其他市场。其中一些未来的应用包括更高效的生物燃料研究和开发（通过藻类监测）、海洋生物学科学和教育、水处理设施中颗粒和病原体的一般监测、生产藻类监测。因此，该技术的潜在社会影响和商业潜力是变革性的。该项目旨在开发和评估一种便携式、快速、耐用和环境稳定的成像流式细胞术技术，该技术将自动监测浮游植物和病原体等微生物存在于流动的水中，并且能够进行特定的分类。现有的基于光学的流式细胞术解决方案价格昂贵且不适合现场使用。与基于实验室的流式细胞仪或手持式测定不同，所提出的系统不依赖试剂或标签，因此不需要专家/专业人员，并且将保持评估的水不变。因此，它可以安装用于连续无人值守的操作，并且由于消除了专家的时间、昂贵的试剂和荧光团，因此每次测试都更具成本效益。此外，所提出的系统还将与能够自动识别微生物以及其他感兴趣的微观物体的机器学习引擎集成。最后，将根据预先收集的当地沿海海水样本对所提出的系统进行评估，以确定浮游植物微生物的三种示例类型的存在，并提供所有检测到的微生物的统计分布。因此，所提出的系统将具有变革性，并提供一种创新和独特的能力，可以方便地调查水样并自动表征已识别的微观物体。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的评估进行评估，被认为值得支持。影响审查标准。