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.

农田过量施用化肥会导致氮径流，导致严重的饮用水污染以及商业渔业和旅游业的衰退。因此，拥有准确的预测氮土壤模型至关重要，该模型可以通过准确了解要使用的肥料类型以及在田间施用的时间和地点来帮助农民减少肥料的使用。 然而，这些土壤模型缺乏准确性，因为在田地内多个点获取土壤氮浓度数据目前成本高昂且技术上具有挑战性。 这项研究将创建低成本传感器，可以将不同土壤深度和位置的土壤氮水平（铵和硝酸根离子浓度水平）电传输到中央枢纽，以便可以通过互联网传输数据并进行远程分析。 配备低成本数据传输电子设备的传感器将由一次性的低成本石墨烯（碳）制成，并且可以使用可扩展的制造协议来创建。 完成的传感器将在番茄植株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，以改进可供农民使用的土壤氮模型。 该项目的目标是开发埋藏式氮传感器与遥感技术相结合，用于实时分析土壤健康状况。这些传感器将采用柔性石墨烯电极开发，该电极采用离子载体膜进行功能化，用于使用激光刻划和喷墨打印技术感测土壤中的铵离子和硝酸根离子（目标 1）。这些传感器的网络将使用基于蓝牙的商用网状网络模块来开发，用于传感器电源、计算和通信（目标 2）。该项目将阐明使用桶队方法成功进行土壤氮监测所需的传感器深度和广播频率。该传感器网络将与开发的现有作物模型合并，并在试验台设施中使用模型番茄系统应对田间相关条件的挑战（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，并监测植物的归一化植被指数，作为集成遥感和实时现场测量的基准。拟议的项目将带来新的：1）无线氮传感器（不稳定和移动）； 2）土壤氮时空动态与地上植物生理学的知识； 3）了解缩放微/纳米传感器地下土壤数据、长时间信号采集/管理以及确定土壤中最大无线数据传输深度； 4) 将土壤传感器结果与遥感等当前现场规模工具相结合的最佳管理实践。该项目将是第一个将同一样本的原位纳米传感器、遥感和作物建模连接起来的项目，从而建立一个平台，以增进对土壤生物地球化学、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（黄叶与养分胁迫之间的联系）和原位土壤传感器（养分命运和运输）的假设。除了测试已开发的传感器系统外，该项目还将制定土壤养分传感器的开发、测试和部署的策略和最佳实践，这些传感器可以在任何地方复制以进行传感器测试和/或假设检验，从而改进模型和观测网络管理土壤健康。这种传感器网络和由此产生的模型预计将带来精准农业，即仅在需要时才以计量方式将肥料撒到田地的特定位置。该奖项反映了 NSF 的法定使命，并通过使用基金会的知识进行评估，被认为值得支持。优点和更广泛的影响审查标准。

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