# Electrochemical Biosensing Platforms for Rapid and Early Diagnosis of Crop Fungal and Viral Diseases

## TL;DR

This review explores electrochemical biosensors for detecting crop diseases, highlighting their sensitivity, challenges in field use, and innovations to improve practical adoption.

## Contribution

The paper provides a critical evaluation of electrochemical biosensing platforms for crop disease detection and identifies key innovations to enable field deployment.

## Key findings

- Electrochemical biosensors can detect pathogens at ultralow levels, such as 0.3 fg/mL for viral proteins and 15 DNA copies for bacteria.
- Genosensors and aptasensors achieve the lowest detection limits due to nucleic acid amplification or high-affinity recognition.
- VOC sensors allow non-invasive monitoring but face specificity issues, while practical adoption is hindered by matrix interference and workflow complexity.

## Abstract

Crop fungal and viral diseases cause annual economic losses exceeding USD 150 billion globally, demanding rapid, sensitive, and field-deployable diagnostic technologies. This review critically evaluates recent advances in electrochemical biosensing platforms for early crop pathogen detection, focusing on immunosensors, genosensors, aptasensors, and VOC-based systems. Reported analytical performances demonstrate ultralow detection capabilities, including 0.3 fg mL−1 for viral coat proteins, 15 DNA copies for bacterial pathogens, 0.5 fg µL−1 RNA detection for viroids, and nanomolar-level VOC sensing (35–62 nM), with response times ranging from 2 to 60 min. Comparative analysis reveals that genosensors and aptasensors generally achieve the lowest LODs due to nucleic acid amplification or high-affinity recognition, while immunosensors provide robust protein-level specificity validated against ELISA. Volatile organic compound (VOC) sensors enable non-invasive, pre-symptomatic monitoring but face specificity challenges. Despite strong laboratory performance, practical adoption is limited by matrix-derived electrochemical interference, environmental instability of biorecognition elements, workflow complexity, and insufficient standardization across studies. Emerging innovations, including magnetic bead enrichment, nanoporous and graphene-based electrodes, microfluidic integration, AI-assisted impedance interpretation, and biodegradable substrates, are progressively addressing these bottlenecks. This review emphasizes that successful field translation requires holistic workflow engineering, matrix-matched validation, and harmonized performance metrics rather than incremental sensitivity improvements alone. By integrating analytical chemistry, nanomaterials engineering, and agricultural decision-support frameworks, electrochemical biosensing platforms hold significant potential to enable decentralized, rapid, and sustainable crop disease management.