# Duplex EIS Sensor for Salmonella Typhi and Aflatoxin B1 Detection in Soil Runoff

**Authors:** Kundan Kumar Mishra, Krupa M Thakkar, Sumana Karmakar, Vikram Narayanan Dhamu, Sriram Muthukumar, Shalini Prasad

PMC · DOI: 10.3390/bios15100654 · 2025-10-01

## TL;DR

A portable sensor detects Salmonella and Aflatoxin in soil runoff, enabling rapid on-site environmental and food safety monitoring.

## Contribution

A portable, label-free duplex sensor for simultaneous detection of Salmonella Typhi and Aflatoxin B1 in soil runoff with high precision.

## Key findings

- The sensor achieves a detection limit of 1 CFU/mL for Salmonella Typhi and 0.001 ng/mL for Aflatoxin B1.
- Impedance measurements from the handheld device strongly correlate with benchtop results (R2 > 0.95).
- Machine learning classification of contaminated samples yields an ROC-AUC > 0.8.

## Abstract

Monitoring contamination in soil and food systems remains vital for ensuring environmental and public health, particularly in agriculture-intensive regions. Existing laboratory-based techniques are often time-consuming, equipment-dependent, and impractical for rapid on-site screening. In this study, we present a portable, non-faradaic electrochemical impedance-based sensing platform capable of simultaneously detecting Salmonella Typhimurium (S. Typhi) and Aflatoxin B1 in spiked soil run-off samples. The system employs ZnO-coated electrodes functionalized with crosslinker for covalent antibody immobilization, facilitating selective, label-free detection using just 5 µL of sample. The platform achieves a detection limit of 1 CFU/mL for S. Typhi over a linear range of 10–105 CFU/mL and 0.001 ng/mL for Aflatoxin B1 across a dynamic range of 0.01–40.96 ng/mL. Impedance measurements captured with a handheld potentiostat were strongly correlated with benchtop results (R2 > 0.95), validating its reliability in field settings. The duplex sensor demonstrates high precision with recovery rates above 80% and coefficient of variation below 15% in spiked samples. Furthermore, machine learning classification of safe versus contaminated samples yielded an ROC-AUC > 0.8, enhancing its decision-making capability. This duplex sensing platform offers a robust, user-friendly solution for real-time environmental and food safety surveillance.

## Linked entities

- **Chemicals:** Aflatoxin B1 (PubChem CID 186907)

## Full-text entities

- **Chemicals:** Aflatoxin B1 (MESH:D016604), ZnO (MESH:D015034)
- **Species:** Salmonella enterica subsp. enterica serovar Typhi (no rank) [taxon 90370], Salmonella enterica subsp. enterica serovar Typhimurium (no rank) [taxon 90371]

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12562585/full.md

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Source: https://tomesphere.com/paper/PMC12562585