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

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:
$30.0万
依托单位:
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
项目状态:
已结题
起止时间:
2019-01-01 至 2021-12-31

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中文摘要
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英文摘要
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.
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RII Track-2 FEC: Building Field-Based Ecophysiological Genome-to-Phenome Prediction
  • 批准号:
    1826820
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $400.0万
  • 财政年份:
    2018
  • 负责人:
    Stephen Welch
  • 依托单位:
HIGH PERFORMANCE COMPUTING SUPPORT FOR UNITED KINGDOM CONSORTIUM ON TURBULENT REACTING FLOWS (UKCTRF)
  • 批准号:
    EP/K025155/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $3.62万
  • 财政年份:
    2014
  • 负责人:
    Stephen Welch
  • 依托单位:
Prediction of toxic species in fire
  • 批准号:
    EP/E000150/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $26.98万
  • 财政年份:
    2007
  • 负责人:
    Stephen Welch
  • 依托单位:
An Instrument Combining Computerized 3D Plant Photogrammetry With Automated Physiological Monitoring
  • 批准号:
    9513549
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $33.42万
  • 财政年份:
    1996
  • 负责人:
    Stephen Welch
  • 依托单位:
海外基金