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SBIR Phase I: Sensory System for Autonomous Area-Wide Disease and Agriterror Detection and Reporting

SBIR Phase I: Sensory System for Autonomous Area-Wide Disease and Agriterror Detection and Reporting
SBIR 第一阶段:用于自治区范围内疾病和农业错误检测和报告的传感系统
批准号:
0539901
负责人:
Agenor Mafra-Neto
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-01-01 至 2007-03-31

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中文摘要
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英文摘要
This Small Business Innovation Research (SBIR) Phase I research project will demonstrate the feasibility of a novel MEMS (Micro-Electro-Mechanical Systems) technique of electrochemical polymerization of biomolecule-friendly conducting polymers to build functional bioreceptors. This research will address key technical challenges in the fabrication of antibody-functionalized conducting nanowires that are individually addressable and scalable to high-density biosensor arrays. The proof-of-concept will be on the demonstration and characterization of the nanowire application for label-free, real-time, rapid, sensitive and cost-effective detection of multiple pathogens in water based solutions (e.g. insect hemolymph and washes). The resultant nano-sensory-arrays will form the base for the development of small, effective, inexpensive, autonomous and automated pathogen detection devices that are field worthy. These units will permit the unattended processing of large number of field samples, thus increasing the capacity of pathogen and agriterror detection, even in isolated rural areas. This may be a disruptive concept and technology because the majority of instruments currently used to detect and diagnose pathogens are slow, expensive, bulky, require human interference, and are not amenable to unattended autonomous operation, thus only a very small portion of introduced pathogens is actually detected before they cause widespread disease or epidemics. IF successful one impact of the outcome of this project could be the increased efficiency in detection of plant pathogens and agents of disease, allowing for preventative rather than crisis or remedial control actions. Early detection is the only form to overt epidemics, and this system will provide such capability. To date, agricultural pest management techniques lack the data collection technologies needed to improve crop yields. Farmers currently rely on time-consuming, manual pest management methods that often come too late to prevent pest infestations. Present methods entail costly blanket spraying of insecticides on entire farms, which is inefficient, ecologically harmful and conducive to the development of pesticide resistance. In the case of diseases, delays in detection can force entire fields and orchards to be plowed and the farm or the region put under quarantine. The development of this automated system will have repercussions in areas beyond agriculture, such as in early detection and alarm of presence of bio-terrorism agents and monitoring and control of vectors of disease.
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