RAPID AND NON-DESTRUCTIVE AUTHENTICATION AND QUANTIFICATION OF CRYSTAL PEPPER POWDER ADULTERATION USING NIR SPECTROSCOPY AND CHEMOMETRIC MODELING

Powdered pepper is a highly susceptible food product to adulteration, particularly when premium cultivars are replaced or partially substituted with lower-cost raw materials. Crystal pepper is highly valued in gourmet cuisine due to its sensory and commercial characteristics, resulting in a higher market value and increasing the incentive for fraudulent substitution. Aristotle pepper, a lower-cost cultivar, may be used as an adulterant in powdered Crystal pepper, compromising product authenticity and potentially affecting its commercial value. Therefore, rapid, reliable, and non-destructive analytical tools capable of supporting real-time authentication are required. In this context, near-infrared (NIR) spectroscopy combined with chemometric techniques represents a promising alternative for the rapid assessment of powdered pepper authenticity. The objective of this study was to evaluate the potential of NIR spectroscopy coupled with chemometric modeling for the detection and quantification of Aristotle pepper adulteration in Crystal pepper powder. A total of 30 samples of Crystal pepper and Aristotle pepper were prepared, and adulterated samples were obtained at 10, 15, 20, and 25% adulteration levels. Spectral data were acquired using a benchtop NIR spectrometer in the 1100–2100 nm wavelength range. The spectra were evaluated under different preprocessing conditions, including untreated spectra, Savitzky–Golay smoothing (SG, 15:2), Standard Normal Variate (SNV), and normalization. Chemometric classification models were subsequently evaluated using LDA, SNV, and KNN approaches to discriminate between adulterated and non-adulterated samples. Among the evaluated approaches, the combination of Savitzky–Golay preprocessing and LDA provided the highest classification performance, reaching an accuracy of 0.98. This result demonstrates the capacity of NIR spectral information, particularly after appropriate spectral preprocessing, to discriminate Crystal pepper powder according to its adulteration status. In addition to qualitative discrimination, Partial Least Squares Regression (PLSR) was implemented to establish a quantitative relationship between the NIR spectral data and the adulteration level. The PLSR model achieved an R² value of 0.95, indicating a strong relationship between the spectral information and the proportion of Aristotle pepper present in the samples. Overall, the results demonstrate the potential of NIR spectroscopy combined with chemometric modeling as a rapid and non-destructive analytical strategy for both authentication and adulteration-level estimation in powdered Crystal pepper. This approach could contribute to the development of rapid screening tools for quality control and authenticity assessment of premium pepper products, with potential applicability to real-time monitoring in the food industry.