Fig. 6: Label-free SERS detection of pathogenic enveloped viruses using machine learning data analytics.
From: Multimodal sensing technologies for HPAI biosurveillance in poultry production systems
The process is demonstrated in two scenarios: a clean cell supernatant and a complex environmental dust matrix. A–D show that average SERS spectra and principal component analysis-linear discriminant analysis (PCA-LDA) can differentiate SARS-CoV-2, influenza A, and Zika virus in the clean matrix. A schematic (E) outlines the workflow. F–J Confirm that even within a noisy dust matrix, the viruses are successfully identified, evidenced by distinct spectral fingerprints, PCA-LDA scores, and a confusion matrix showing high classification accuracy24. Reproduced with permission from Garg et al., Biosensors and Bioelectronics (2024), Elsevier. License Number: 6153910838293.
