EAGER SitS: Bury and Forget Nitrogen Sensors Coupled With Remote Sensing for Soil Health

EAGER SitS：埋藏并忘记氮传感器与遥感相结合的土壤健康

• 批准号: 1841649
• 负责人: Jonathan Claussen
• 金额: $ 15万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1841649&HistoricalAwards=false
• 关键词: EAGER; SitS; Bury; Forget; Nitrogen

Excess fertilizer application from farm fields results in nitrogen runoff which causes major drinking water contamination as well as commercial fishing and tourism industry decline. Therefore, it is vitally important to have accurate predictive nitrogen soil models that can help farmers reduce fertilizer use by knowing exactly what type of fertilizer to use and precisely when and where in a field to apply. However, the accuracy of these soil models is lacking because soil nitrogen concentration data acquired at numerous points within a field is currently cost prohibitive and technically challenging. This research will create low-cost sensors that can electrically transmit soil nitrogen levels (ammonium and nitrate ion concentration levels) from various soil depths and locations to a central hub so that data can be transmitted through the internet and analyzed remotely. Sensors that can be fitted with low-cost data transmission electronics will be made of low-cost graphene (carbon) that is disposable and can be created using scalable manufacturing protocols. The completed sensors will be tested in the soils surrounding tomato plants to acquire high resolution spatial and temporal nitrogen data for improving soil nitrogen models that can be utilized by farmers. The objective of this project is to develop bury-and-forget nitrogen sensors coupled with remote sensing technologies for real-time analysis of soil health. The sensors will be developed with flexible graphene electrodes functionalized with ionophore membranes for sensing of ammonium and nitrate ions in soils using laser inscribing and inkjet printing techniques (Aim 1). A network of these sensors will be developed using commercial Bluetooth-based mesh network modules for sensor power, computing, and communications (Aim 2). This project will elucidate the sensor depth and broadcast frequency that is capable/needed for successful in-soil nitrogen monitoring using a bucket brigade approach. This sensor network will be merged with existing crop models developed and challenged with in-field relevant conditions using a model tomato system in a testbed facility (Aim 3). The testbed facility will be used for collecting high resolution nitrogen sensor data from the soil coupled with monitoring of the Normalized Difference Vegetation Index of the plants as benchmarks to integrate remote sensing and real-time field measurements. The proposed project will lead to new: 1) wireless nitrogen sensors (both labile and mobile); 2) knowledge of spatiotemporal dynamics of soil nitrogen coupled with above ground plant physiology; 3) knowledge of scaling micro/nanosensor subsurface soil data, long-duration signal acquisition/curation, and pinpointing the maximum wireless data transmission depth in soil; and 4) best management practices for coupling soil sensor results to current field-scale tools such as remote sensing. The project will be the first to connect in-situ nanosensors, remote sensing, and crop modeling for the same sample, therein establishing a platform for improving understanding of soil biogeochemistry, sensor networks, and fundamental spatiotemporal scaling principles. This project will facilitate rapid studies for improving empirical model parameters (crop coefficients), as well as to validate assumptions in remote sensing (links between yellowing leaves and nutrient stress) and in-situ soil sensors (nutrient fate and transport). In addition to testing the developed sensor systems, this project will establish strategies and best practices for the development, testing, and deployment of soil nutrient sensors that can be reproduced anywhere for sensor testing and/or hypothesis testing, leading to improved models and observation networks to manage soil health. Such sensor networks and resultant models are expected to lead to precision agriculture where fertilizers are spread onto specific locations of the field in a metered fashion only when needed.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.

农田过量施肥导致氮流失，造成严重的饮用水污染以及商业渔业和旅游业的衰退。因此，具有准确的预测性氮土壤模型至关重要，可以帮助农民通过确切地知道使用哪种类型的肥料以及在田间何时何地施用来减少肥料的使用。 然而，这些土壤模型的准确性是缺乏的，因为土壤氮浓度数据采集在许多点内的领域是目前成本高昂，技术上具有挑战性。 这项研究将创建低成本的传感器，可以将土壤氮水平（铵离子和硝酸根离子浓度水平）从不同的土壤深度和位置传输到中央枢纽，以便数据可以通过互联网传输并进行远程分析。 可以安装低成本数据传输电子设备的传感器将由低成本的石墨烯（碳）制成，这种石墨烯是一次性的，可以使用可扩展的制造协议来制造。 完成的传感器将在番茄植物周围的土壤中进行测试，以获得高分辨率的空间和时间氮数据，用于改进农民可以利用的土壤氮模型。 该项目的目标是开发“埋后即忘”式氮传感器，并结合遥感技术，对土壤健康状况进行实时分析。该传感器将开发与柔性石墨烯电极功能化与离子载体膜感测铵和硝酸根离子在土壤中使用激光刻和喷墨打印技术（目标1）。这些传感器的网络将使用商用的基于蓝牙的网状网络模块开发，用于传感器供电、计算和通信（目标2）。该项目将阐明传感器深度和广播频率，能够/需要成功的土壤氮监测使用水桶旅的方法。该传感器网络将与现有的作物模型合并，并在试验台设施中使用番茄模型系统在田间相关条件下进行挑战（目标3）。该试验台设施将用于从土壤中收集高分辨率氮传感器数据，同时监测植物的归一化植被指数，作为基准，将遥感和实时实地测量结合起来。拟议的项目将导致新的：1）无线氮传感器（不稳定的和移动的）; 2）土壤氮的时空动态与地上植物生理学相结合的知识; 3）缩放微/纳米传感器地下土壤数据、长时间信号采集/管理以及精确定位土壤中的最大无线数据传输深度的知识; 4）将土壤传感器结果与当前实地尺度工具（如遥感）相结合的最佳管理实践。该项目将是第一个将原位纳米传感器，遥感和作物建模连接到同一样本的项目，从而建立一个平台，以提高对土壤地球化学，传感器网络和基本时空尺度原理的理解。 该项目将促进快速研究，以改进经验模型参数（作物系数），并验证遥感（变黄的叶子与养分压力之间的联系）和现场土壤传感器（养分归宿和迁移）中的假设。除了测试开发的传感器系统，该项目将建立战略和最佳实践的开发，测试和部署土壤养分传感器，可以复制任何地方的传感器测试和/或假设检验，导致改进的模型和观测网络来管理土壤健康。这样的传感器网络和由此产生的模型预计将导致精确农业，其中肥料仅在需要时以计量方式散布到田间的特定位置。该奖项反映了NSF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。

项目成果

Laser-Induced Graphene Electrochemical Immunosensors for Rapid and Label-Free Monitoring of Salmonella enterica in Chicken Broth

• DOI: 10.1021/acssensors.9b02345
• 发表时间: 2020-07-24
• 期刊: ACS SENSORS
• 影响因子: 8.9
• 作者: Soares, Raquel R. A.;Hjort, Robert G.;Gomes, Carmen L.
• 通讯作者: Gomes, Carmen L.

Enhanced electrochemical biosensor and supercapacitor with 3D porous architectured graphene via salt impregnated inkjet maskless lithography

• DOI: 10.1039/c8nh00377g
• 发表时间: 2019-04
• 期刊: Nanoscale Horizons
• 影响因子: 9.7
• 作者: John Hondred;Igor L. Medintz;J. Claussen

Stamped multilayer graphene laminates for disposable in-field electrodes: application to electrochemical sensing of hydrogen peroxide and glucose

• DOI: 10.1007/s00604-019-3639-7
• 发表时间: 2019-07
• 期刊: Microchimica Acta
• 影响因子: 5.7
• 作者: Loreen R Stromberg;John Hondred;Delaney Sanborn;Deyny L Mendivelso-Pérez;S. Ramesh;I. Rivero;Josh Kogot;Emily A. Smith;C. Gomes;J. Claussen

Electrochemical Sensing of Neonicotinoids Using Laser-Induced Graphene

• DOI: 10.1021/acssensors.1c01082
• 发表时间: 2021-08-09
• 期刊: ACS SENSORS
• 影响因子: 8.9
• 作者: Johnson, Zachary T.;Williams, Kelli;Claussen, Jonathan C.
• 通讯作者: Claussen, Jonathan C.

Laser-induced graphene electrodes for electrochemical ion sensing, pesticide monitoring, and water splitting

• DOI: 10.1007/s00216-021-03519-w
• 发表时间: 2021-09
• 期刊: Analytical and Bioanalytical Chemistry
• 影响因子: 4.3
• 作者: I. Kucherenko;Bolin Chen;Zachary T. Johnson;Alexander Wilkins;Delaney Sanborn;Natalie Figueroa-Félix