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March 29, 2026ChemistrySelect1 citations

An Efficient and Sensitive SPR‐Based Method for Yellow Rust Detection in Wheat for Effective Forecasting and Management

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RRRizwana RehsawlaSJSurbhi JainMTMonika Tomar

Key Points

  • To develop a sensitive and efficient SPR-based biosensor for the early detection of wheat stripe rust caused by Pst.
  • Developed a surface plasmon resonance (SPR) biosensor using zinc oxide and gold-coated glass prisms
  • Immobilized single-stranded DNA probes specific for the Pst gene
  • Measured sensitivity and detection threshold for Pst detection using the biosensor.
  • Achieved a detection range of 1-150 ng/µL for Pst
  • Demonstrated a sensitivity value of 0.18°/(ng/µL)
  • Showed a detection threshold as low as 1 ng/µL
  • Exhibited high specificity for target sequences
  • Maintained usability for up to 10 detection cycles with signal retention.

Abstract

ABSTRACT Puccinia striiformis f. sp. tritici (Pst), is a fungal pathogen and causal agent of wheat stripe rust. This pathogen poses a significant threat to global wheat production. Traditional detection techniques often suffer from many limitations such as low sensitivity, high cost of the reagents, and time‐consuming procedures. To overcome these challenges, we developed a Surface Plasmon Resonance (SPR)‐based DNA biosensor for early detection of Pst. The sensor chip was prepared by depositing a 200 nm thick layer of zinc oxide (ZnO) over a gold‐coated BK‐7 glass prisms, with subsequent immobilization of single‐stranded (ss) DNA probes for the Pst‐specific ketopantoate reductase‐like protein gene. The biosensor exhibited a detection range of 1–150 ng/µL with a sensitivity value of 0.18°/(ng/µL) and a detection threshold of 1 ng/µL. The biosensor demonstrated high specificity toward complementary target sequences with a usable reusability value up to 10 cycles with noted signal retention. In this paper, we present a first‐in‐scope demonstration of an SPR‐based DNA biosensor for Pst detection providing a label‐free, real‐time detection scheme with low costs. Our developed platform bears considerable promise for implementation within forecasting systems as part of timely management protocols for wheat cultivation.

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Cite This Study

Rehsawla et al. (2026) studied this question.

synapsesocial.com/papers/69c8c22cde0f0f753b39c5cbhttps://doi.org/10.1002/slct.202506406
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