An official website of the United States government.

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

PORTABLE, IN-FIELD BIOSENSOR FOR MULTIPLEX SENSING OF COMMON MIDWESTERN HERBICIDES

Investigators
Johnson, Anna Kerr
Institutions
Iowa State University
Start date
2021
End date
2024
Objective
Goal I. Develop Nanoporous Gold Leaf Electrodes for Specific Pesticide DetectionObjective 1. Fabricate atrazine, glyphosate, dicamba, 2,4-dichlorophenoxyacetic acid sensors using various enzymes (e.g., glycine oxidase, glyoxalate reductase, horseradish peroxidase, tyrosinase, acetylcholinesterase, and antibodies) Objective 2.Incorporate machine learning algorithms to optimize fabrication processObjective 3. Determine the surface functionalization method (e.g., glutaraldehyde, EDC/NHS) that allows for the most sensitive detection of pesticidesObjective 4. Adjust enzyme concentration between 2-2000 unit/mL to capture nominal concentrations of the pesticides in surface water using amperometry and/or electrochemical impedance spectroscopyObjective 5. Test interferent pesticides and inorganic molecules against each pesticide-specific biosensor with a maximum of 10% interferenceObjective 6. Merge individual pesticide biosensors onto multiplex platform and perform accuracy tests compared to individual calibration with a minimum of 95% accuracyObjective 7. Test in complex fluids such as river water and soil slurries and compare the accuracy to the multiplex calibration with a minimum of 95% accuracyGoal II. Develop 3D Printed Microfluidic Cartridge Objective 1. Design microfluidic chamber for a peel-and-stick multiplex sensor using fluid dynamics software and 3D print using FormLabsObjective 2. Confirm design with real-time monitoring of fluid flow using a cameraObjective 3. Incorporate multiplex sensor and compare results to pesticide calibrations developed in Goal I. Ensure a 95% accuracyObjective 4. Confirm in complex fluids with a 95% accuracyGoal III. Validate In-Field Pesticide Data with ML AlgorithmsObjective 1. Use models developed from Goal I & II to formulate a machine learning algorithm from 50 data setsObjective 2. Collect water samples from South Fork Iowa River watershed and ensure pesticide detectionObjective 3. Obtain true pesticide concentrations by using the USDA-ARS and Iowa State University for mass spectroscopy and liquid/gas chromatographyObjective 4. Iterate ML algorithm to ensure in-field pesticide accuracy of 95% by comparing to laboratory confirmationGoal IV. Extension and Dissemination of ResearchObjective 1. Host workshops at Iowa State University that are open to students, staff, and the public; workshops will be held at the beginning of the project to gather stakeholder feedback and at the end of the project to demonstrate the deviceObjective 2. Work with the Iowa State University Extension office to have direct correspondence with immediate stakeholders including farmers and policy makersObjective 3. Disseminate research findings through attending and presenting at conferences as well as through publicationsGoal V. Mentorship and Career DevelopmentObjective 1. Actively mentor 2-4 undergraduate researchers throughout the scope of the projectObjective 2. Gain experience and establish communication with farmers and other stakeholders to ensure sustainable and precision agriculture aligned with the AFRI Farm Bill priority of Agriculture Systems and Technology
Funding Source
Nat'l. Inst. of Food and Agriculture
Project source
View this project
Project number
IOWW-2020-10083
Accession number
1026406
Categories
Prevention and Control
Pesticide Residues
Chemical Contaminants
Policy and Planning