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

这个小企业创新研究（SBIR）第一阶段研究项目将展示一种新型MEMS（微机电系统）技术的可行性，该技术是生物分子友好的导电聚合物的电化学聚合，以构建功能性生物受体。这项研究将解决抗体功能化的导电纳米线，是单独寻址和可扩展的高密度生物传感器阵列的制造中的关键技术挑战。概念验证将是纳米线应用的示范和表征，用于对水基溶液（例如昆虫血淋巴和洗涤液）中的多种病原体进行无标记、实时、快速、灵敏和具有成本效益的检测。由此产生的纳米传感器阵列将成为开发小型，有效，廉价，自主和自动化的病原体检测设备的基础，这些设备具有现场价值。这些单位将允许无人值守地处理大量实地样本，从而提高病原体和农业恐怖主义检测能力，甚至在偏远的农村地区。这可能是一种颠覆性的概念和技术，因为目前用于检测和诊断病原体的大多数仪器速度慢、价格昂贵、体积庞大，需要人为干预，并且不适合无人值守的自主操作，因此只有很小一部分引入的病原体在引起广泛的疾病或流行病之前被实际检测到。如果成功，该项目成果的一个影响可能是提高了检测植物病原体和疾病病原体的效率，从而可以采取预防性而不是危机或补救性控制行动。早期检测是公开流行病的唯一形式，而这一系统将提供这种能力。迄今为止，农业虫害管理技术缺乏提高作物产量所需的数据收集技术。农民目前依赖于耗时的人工虫害管理方法，这些方法往往来得太晚，无法防止虫害。目前的方法需要对整个农场进行昂贵的杀虫剂地毯式喷洒，这是低效的，对生态有害的，并且有助于产生杀虫剂抗性。在疾病的情况下，检测的延误可能迫使整个田地和果园被犁，农场或地区被隔离。这一自动化系统的开发将对农业以外的领域产生影响，例如对生物恐怖主义制剂的早期发现和警报以及对疾病媒介的监测和控制。

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.