Digital SERS Nanostructured Platform for Amplification-free Single-Molecule DNA Detection and Pre-Symptomatic Diagnosis of Kiwifruit Soft Rot

We present a digital surface-enhanced Raman spectroscopy (SERS) platform enabling enzyme- and amplification-free single-molecule DNA detection through Poisson distribution-driven quantification and geometrically optimized plasmonic nanostructures. Utilizing high-throughput UV lithography, we fabricated large-area nanopillar arrays (1.5 × 1.5 cm) with tunable heights (500-1300 nm) and periodicities (4-10 μm), addressing key limitations in conventional SERS methods via three innovations: (1) dynamic hotspot generation: Target DNA induces plasmonic dimerization between functionalized gold nanoprobes and Au-capped nanopillars, creating spatially resolved SERS enhancement (1326 cm^-1 DTNB signal), (2) digital counting algorithms: Compensate Raman intensity variations by quantifying activated pillars as discrete molecular events, and (3) geometric confinement: Spatial confinement effects enabling statistically robust single-molecule occupancy. This platform achieved 10 fM sensitivity for <i>Diaporthe</i> spp. DNA detection, outperforming PCR-electrophoresis (1 pM) by 2 orders of magnitude. Applied to presymptomatic kiwifruit diagnosis, the system identified pathogen DNA in asymptomatic samples prior to visual symptom development, validated by characteristic DTNB peaks (1326 cm^-1) absent in negative controls. The modular design permits multiplexed detection through probe diversification, while the absence of enzymatic steps enables field-deployable operation. By integrating single-molecule statistics with plasmonic signal amplification, this work establishes a robust framework for precision molecular diagnostics, demonstrating transformative potential for agricultural pathogen surveillance and low-abundance biomarker analysis. The technology's batch-producible nanopillar architecture and digital quantification strategy overcome longstanding reproducibility challenges in SERS-based detection, positioning it as a versatile tool for next-generation biosensing applications.