Phytochemical-based quality control of cayenne pepper using spectroscopic monitoring of lycopene content and antioxidant capacity

Quality control in cayenne pepper fruit is important for maintaining product consistency. The research aimed to evaluate lycopene content and antioxidant capacity as the main indicators of cayenne pepper quality. Visible-near infrared (Vis-NIR) spectroscopy is an emerging technology that can predict lycopene content and antioxidant capacity non-destructively, accurately, and quickly. Spectral data (381–1065 nm) were analyzed using support vector machine regression to develop the calibration model. Reference data on lycopene and antioxidant capacity were determined using spectrophotometry method. The results displayed a robust association between spectra and reference data. The calibration model for lycopene content and antioxidant capacity generated sufficient performance in terms of accuracy. For both parameters, the models showed correlation coefficient ( R ) ≥ 0.85, root mean square error of calibration (RMSEC) ≥ 17.61, root mean square error of cross validation (RMSECV) ≥ 42.01, and ratio of prediction to deviation (RPD) ≥ 1.95. Based on these results, it further strengthens that Vis-NIR technology was able to non-destructively assess lycopene content and antioxidant capacity. In the food and postharvest industries, the developed method shows promise for fast quality screening, automated grading, and real-time monitoring. Additionally, Vis-NIR spectroscopy’s rapidity and non-destructive nature make it scalable for industrial uses, especially in precision agriculture and contemporary quality control systems. These findings support the potential of non-destructive technology as an alternative for the quality control system of cayenne pepper quality in the agricultural and food industries.