SBIR Phase II: Low-cost in-planta nitrate sensor

SBIR 第二阶段：低成本植物内硝酸盐传感器

• 批准号: 2155110
• 负责人: Xinran Wang
• 金额: $ 99.87万
• 依托单位: ENGENIOUSAG, LLC
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2155110&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Low; cost

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to provide farmers with a low-cost plant sensor for direct, instantaneous measurement of nitrate-nitrogen (N) levels in crop sap. Widespread adoption of the sensor could support cost-effective and improved N fertilizer management, which may increase farmers’ productivity and profitability. Low-cost, instantaneous nitrate testing readouts from plant stalks will provide more actionable information to guide farmers’ fertilization decisions than current methods to test N levels in soil (e.g., collect soil samples, ship them to lab, and then wait ~1 week for lab analysis). The improvements in fertilizer-management decisions, enabled by more accessible and more actionable data, have the potential to reduce total N fertilizer applications in the US by some 2 million tons annually. This large reduction in N fertilizer applications would decrease the energy footprint of agriculture, reduce emissions of nitrous oxide, a greenhouse gas 300 times as potent as carbon dioxide, and improve water quality through reductions in N runoff, improving ecosystem services and human health through improved rural water quality and the reduction in hypoxic dead zones. The proposed project represents an innovation in the function and application of an in planta nitrate sensor. The project goals are to: i) improve the sensor for reliable deployment in field measurements; ii) conduct research in farmers’ fields to develop predictive models that input nitrate levels from sensor measurements of corn stalks and other data to output N fertilization recommendations; and iii) build a lab-based multi-probe nitrate sensor that extends the work to other crops in the existing plant and soil testing market. Anticipated results are that the data from the sensors will be used to build predictive models that output optimum N fertilization recommendations that will outperform conventional models. The accomplishment of this goal will lead to the commercialization of rugged low-cost sensors that provide rapid measurements of plant sap nitrate. This ability will make it possible to provide farmers with low-cost fertilizer recommendations based on data-driven, predictive modeling of N demand.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.

这个小企业创新研究（SBIR）第二阶段项目的更广泛的影响/商业潜力是为农民提供一种低成本的植物传感器，用于直接，即时测量作物汁液中的硝酸盐氮（N）水平。传感器的广泛采用可以支持具有成本效益和改进的氮肥管理，这可能会提高农民的生产力和盈利能力。与目前测试土壤中氮含量的方法相比，来自植物秸秆的低成本、瞬时硝酸盐测试读数将提供更多可操作的信息来指导农民的施肥决策（例如，收集土壤样本，将其运送到实验室，然后等待约1周进行实验室分析）。通过更容易获得和更具可操作性的数据，肥料管理决策的改进有可能每年减少美国约200万吨的氮肥施用量。氮肥施用量的大幅减少将减少农业的能源足迹，减少一氧化二氮的排放，一种温室气体是二氧化碳的300倍，并通过减少氮径流来改善水质，通过改善农村水质和减少缺氧死区来改善生态系统服务和人类健康。 该项目代表了植物硝酸盐传感器的功能和应用的创新。该项目的目标是：i）改进传感器，以可靠地部署在田间测量中; ii）在农民的田地中进行研究，以开发预测模型，该模型从玉米秸秆的传感器测量和其他数据中输入硝酸盐水平，以输出氮肥施肥建议;以及iii）建立基于实验室的多探针硝酸盐传感器，将工作扩展到现有植物和土壤测试市场中的其他作物。预计结果是，来自传感器的数据将用于建立预测模型，输出最佳氮肥施肥建议，将优于传统模型。这一目标的实现将导致坚固的低成本传感器的商业化，提供快速测量植物汁液硝酸盐。该奖项反映了NSF的法定使命，通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。