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

为了避免在2050年之前出现严重的全球粮食中断，作物产量必须提高。帮助提高作物产量的一种方法是向农民提供有关土壤健康的实时数据，以便他们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。研究人员和农民经常依赖土壤取样方法，这些方法不能代表整个农田的健康状况。该项目将使用由微生物驱动的传感器来测量土壤湿度和土壤养分。这些传感器将使用无线电波检测这些土壤变量，并与传感器及其周围环境的详细数学模型一起提取有关土壤健康的全面信息。微生物为这些传感器发电的速度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情况，而不仅仅是田地中的单个点，从而消除了不断手动土壤采样的需要。因此，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，这项研究将有助于提高作物产量，并确保国家粮食安全到2050年的需求。本提案采用多学科方法创建一个融合传感器，用于土壤微生物活动和土壤水分、多离子氮循环和养分有效性的非点监测。这个项目基于三个想法。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1.0兆赫兹的阻抗光谱传感器（ISS）供电。由于水和各种单离子溶液的电磁介电常数随频率变化不同，适当的信号处理将能够消除土壤水混合物中离子浓度的歧异。这是不可能与普通的土壤电导率传感器。作为一种体积测量方法，ISS改善了点传感器无法充分捕获的土壤变异性问题。对于第二个想法，MFC将感知土壤微生物的活动。不同深度和氧化还原电位的金属阳极将被浸涂一层掺杂酶的保护性聚合物涂层，该涂层将内源性土壤微生物从阳极生物膜中排除，并在发电时产生厌氧条件。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产生的能量将反映土壤微生物代谢传感器附近的土壤碳和营养物质的情况。此外，国际空间站将定期监测MFC的内部特性。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。该模型将根据多频介电常数和MFC输出电流的测量值，产生所需的土壤湿度、离子浓度和微生物活性数据。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，开发关于土壤传感技术和土壤过程的课堂课程。该奖项反映了美国国家科学基金会的法定使命，并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。

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.