EAGER SitS: Sustainable Biosensor Integration for Precision Management of Agricultural Soils

EAGER SitS：可持续生物传感器集成，用于农业土壤的精确管理

• 批准号: 1841613
• 负责人: Stephen Welch
• 金额: $ 30万
• 依托单位: Kansas State University
• 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: 2019-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1841613&HistoricalAwards=false
• 关键词: EAGER; SitS; Sustainable; Biosensor; Integration

To avoid major global food disruptions by 2050, crop productions rates must improve. One way to help improve crop production rates is to provide farmers with real-time data on soil health so they can make better-informed agricultural decisions, particularly during the growing season. Soil data is crucial, but extremely difficult to obtain. Researchers and farmers often rely of soil sampling methods that are not representative of overall field health. This project will use sensors powered by microbes to measure soil moisture and soil nutrients. These sensors will detect these soil variables using radio waves, and, along with detailed mathematical models of the sensors and their surroundings, extract comprehensive information on soil health. The rate at which the microbes generate power for these sensors will also provide data on soil activity. More importantly, the radio waves used for measurement will sense overall conditions rather than just single points in a field, thus eliminating the need for constant manual soil sampling. This unique combination of sensors and mathematical models will thus collect hard to obtain soil information that can help farmers make more informed decisions about agricultural practices. If successful, this research could help improve crop production rates and ensure the Nation's food security through 2050 demands.This proposal uses multidisciplinary methods to create a fused sensor for soil microbial activity and non-point monitoring of soil moisture, multi-ion nitrogen cycling, and nutrient availability. The project is based on three ideas. The first idea is to use subsurface microbial fuel cells (MFCs) to power an impedance spectroscopy sensor (ISS) operating from 0.04 to 1.0 megahertz. Because water and various single-ion solutions have electromagnetic permittivities that differentially vary with frequency, appropriate signal processing will be able to disambiguate ionic concentrations in the soil water mixture. This is not possible with normal soil conductivity sensors. As a bulk volumetric measurement, ISS ameliorates the problem of soil variability that cannot be adequately captured by point sensors. For the second idea, the MFC will sense soil microbial activity. Metal anodes at different depths and redox potentials will be dip-coated with a protective polymer coating doped with enzymes that exclude endogenous soil microbes from the anode biofilm and create anaerobic conditions at the point of power generation. In these anaerobic conditions, organic acids will be produced to fuel the MFC. At each point in time, the power generated by the MFC will reflect the soil microbes as they metabolize soil carbon and nutrients near the sensor. In addition, the ISS will periodically monitor internal properties of the MFC. For the third idea, the project will develop a continuous-time, partial differential equation model linking soil solute movement, thermal dynamics, soil chemical kinetics, electrical redox processes, microbial activity, and basic root/shoot growth. This model will yield the desired data on soil moisture, ionic concentrations, and microbial activity based on the measured values of multi-frequency permittivities and the MFC output currents. In addition to this research, the principle investigators will collaborate with the local Manhattan Sunset Zoo and Manhattan high school teachers to develop classroom lessons on soil sensing technologies and soil processes.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.

为了避免到2050年全球粮食出现重大中断，农作物产量必须提高。帮助提高作物生产率的一种方法是为农民提供有关土壤健康的实时数据，以便他们能够做出更明智的农业决策，特别是在生长季节。土壤数据至关重要，但极难获得。研究人员和农民往往依赖于土壤采样方法，而这些方法并不能代表整体的农田健康状况。该项目将使用由微生物驱动的传感器来测量土壤水分和土壤养分。这些传感器将利用无线电波检测这些土壤变量，并沿着传感器及其周围环境的详细数学模型，提取关于土壤健康的全面信息。 微生物为这些传感器发电的速率也将提供土壤活动的数据。更重要的是，用于测量的无线电波将感知整体状况，而不仅仅是田地中的单个点，从而消除了持续手动土壤采样的需要。 这种传感器和数学模型的独特组合将收集难以获得的土壤信息，帮助农民对农业实践做出更明智的决定。如果成功，该研究将有助于提高作物产量，确保2050年前的国家粮食安全。该提案采用多学科方法，创建用于土壤微生物活性和非点监测土壤水分，多离子氮循环和养分有效性的融合传感器。该项目基于三个想法。第一个想法是使用地下微生物燃料电池（MFC）为工作频率为0.04至1.0兆赫的阻抗谱传感器（ISS）供电。由于水和各种单离子溶液具有随频率不同而变化的电磁兼容性，因此适当的信号处理将能够消除土壤水混合物中的离子浓度。这对于普通的土壤电导率传感器是不可能的。作为一个散装体积测量，国际空间站改善了土壤变异性的问题，不能充分捕捉点传感器。 对于第二个想法，MFC将感测土壤微生物活性。不同深度和氧化还原电位的金属阳极将浸涂有掺杂有酶的保护性聚合物涂层，该酶将内源性土壤微生物从阳极生物膜中排除并在发电点处产生厌氧条件。在这些厌氧条件下，将产生有机酸来为MFC提供燃料。在每个时间点，MFC产生的功率将反映土壤微生物在传感器附近代谢土壤碳和养分的情况。此外，ISS将定期监测MFC的内部属性。对于第三个想法，该项目将开发一个连续时间的偏微分方程模型，将土壤溶质运动、热动力学、土壤化学动力学、电氧化还原过程、微生物活动和基本根/芽生长联系起来。该模型将产生所需的数据，土壤水分，离子浓度，和微生物活性的基础上的多频电阻率和MFC输出电流的测量值。除了这项研究之外，主要研究人员还将与当地的曼哈顿日落动物园和曼哈顿高中教师合作，开发土壤传感技术和土壤过程的课堂课程。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。