Location: Sustainable Water Management Research
Project Number: 6066-13000-006-023-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 1, 2022
End Date: Dec 31, 2026
Objective:
1. Develop and validate a novel wireless fish-mounted sensor system.
2. Establish a correlation between water quality and spatio-temporal dynamics of chemical substances in freshwater fish.
Approach:
The proposed project builds on the principal investigator's prior work on developing flexible and microneedle-based electrochemical sensors and integrated systems for crop stress monitoring and wearable diagnostics. The research approaches aligned with the proposed objectives are detailed below:
Research Approach 1: Internet-of-Things-enabled multifunctional fish-mounted sensors with wireless data transmission capability.
This project will develop a multiplexed electrochemical sensor for quantitatively measuring a panel of metabolites in fish that are expressed/elevated in response to water toxicity. Each two-dimensional electrode surface will contain an array of protruded microneedles that will be fitted into the sclera of the eyeball. One key innovation would be to combine all the sensors in a single chip instead of having discrete sensors for measuring single metabolites, thereby substantially reducing the footprint. The microneedles will penetrate the sclera of the fish eyeball. The sensing mechanism relies on electrochemistry wherein redox reactions of selective metabolites on the chemically functionalized electrodes will be translated to current flow proportional to the metabolite concentration. The resulting redox current will be recorded and analyzed by the onboard data acquisition and processing (DAP) unit. This unit will include a LoRa (short for Long Range) gateway for wireless data transmission so that the measured time-series metabolite levels can be wirelessly monitored and stored in the cloud server. The sensors will be controlled remotely with an app, without being physically present at the experimental site. Both the multiplexed sensor and the DAP unit will be integrated on a single platform and covered with a waterproof encapsulation layer. The performance and accuracy of the sensor will be first validated at the PI's facility. The sensor will be calibrated with simulated solutions spiked with different concentrations of the target metabolites. The metabolite levels measured by the proposed sensor will be validated against the values from liquid chromatography-mass spectrometry tests.
Research Approach 2: Statistical analysis to correlate metabolic responses in fish with water toxicity. The multiplexed sensor will be tested in a nearby ARS facility. The fishes will be exposed to a combination of stresses representing different degrees of water toxicity and the resulting variations in the metabolic responses will be measured. The time-series metabolite levels, measured with the multiplexed sensor will be downloaded from the cloud server and processed to determine the functional correlations of the metabolites with the water quality. Classifiers will be used to differentiate different levels of water toxicity. The day at which metabolite levels start to show measurable variations after introducing stress will also be recorded. This will work as an 'early warning' signal of the possible degradation in water quality.
