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Rapid and reliable identification of gelatin origin is critically important for food authentication and halal verification. This study proposes a label-free optical sensing approach based on surface plasmon resonance (SPR) for discriminating bovine, porcine, and fish gelatin. Gelatin solutions (1–8% w/v) were analyzed using a prism-coupled attenuated total reflection (ATR)-SPR configuration, where resonance angle shifts were extracted from reflectance minima. Complementary finite-difference time-domain (FDTD) simulations were performed to validate experimental trends and elucidate field interactions at the metal–dielectric interface. Results show distinct refractive index (RI) profiles and concentration-dependent resonance shifts for each gelatin type, enabling clear differentiation without chemical labeling. At higher concentrations (7–8%), fish gelatin exhibits the highest RI, followed by porcine and bovine gelatin. Porcine gelatin demonstrates the most linear and sensitive response, with a strong correlation (R² = 0.9412) between concentration and resonance angle shift. Simulation results are in good agreement with experimental data, confirming the sensitivity of SPR to subtle RI variations. The novelty of this work lies in the integration of ATR-SPR and numerical modeling for rapid, non-destructive, and label-free identification of gelatin sources across multiple animal origins. This approach offers a promising platform for real-time food authentication, quality control, and halal assurance, with potential for portable and on-site sensing applications.
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