Abstract:
Various honey samples and their adulterants from C3 plants (rice syrup) and C4 based plants (sugar syrup, corn syrup, and jaggery syrup) were analyzed using Near-Infrared Spectroscopy (NIRS) coupled with aquaphotomics and chemometric algorithms for qualitative and quantitative assessment. To validate the authenticity of the collected samples, stable carbon isotope ratio analysis (SCIRA) was performed. Spectral data for honey samples were acquired using NIRS (600–2600 nm, 1 nm resolution) and optimized using aquaphotomics by selecting wavelengths associated with water characteristics. Additionally, the aquaphotomics wavelength range was expanded by including spectral variables related to the O-H bend second overtone (1940 nm), O-H stretch/O-H bend combination (1960 nm), and O-H bend/C-O stretch combination band (2100 nm). The performance of these optimized variables was evaluated using qualitative (PCA, k-means, LDA, SVM) and quantitative (PCR, SVR, PLS) analyses, achieving a maximum classification accuracy of 100 % and a regression coefficient (R²) of 0.999. This study provides a rapid, non-destructive, and highly accurate method for honey authentication, offering significant applications in food quality control and combating fraudulent honey adulteration. The proposed approach can be effectively implemented in the honey industry and regulatory bodies to ensure product authenticity, protect consumer health, and maintain market integrity.