Real-time profiling of fatty acids and category authentication in vacuum-packed sliced Iberian ham using online near infrared spectroscopy

This study evaluates the potential of online near infrared (NIR) spectroscopy for the real-time prediction of fatty acid composition and the classification of sliced Iberian ham into commercial categories. A total of 254 samples, representing the four official Spanish commercial categories, were analysed under both vacuum-packed and unpackaged conditions using two online NIR devices (a diode array sensor and Fourier-Transform near infrared (FT-NIR) instrument). Although calibration models were developed for palmitic, stearic, and oleic acids, external validation revealed that only the oleic acid model, developed using the diode array sensor, met all recommended statistical criteria (coefficient of determination for prediction (R 2 p ) of 0.61 and 0.62 with a standard error of prediction corrected for bias (SEP c ) of 2.07 g/100 g and 2.01 g/100 g), in both formats, respectively, for routine application. Regarding qualitative models, the diode array instrument achieved balanced and robust classification performance, with external validation yielding a sensitivity of 93.75 %, specificity of 89.47 %, and a non-error rate (NER) of 92.16 % in vacuum-packed samples, and sensitivity of 93.75 %, specificity of 84.21 %, and NER of 90.20 % in unpackaged samples. These findings confirm that the diode array NIR instrument is the most suitable for industrial implementation, enabling reliable, real-time prediction of oleic acid and authentication of Iberian ham categories directly in their commercial vacuum-packed presentation. • Online NIR spectroscopy was applied for real-time analysis of Iberian ham. • Fatty acids were predicted directly on the sorting lines. • Oleic acid models with the Perten DA 7440 met all external validation criteria. • Premium vs non-premium categories were classified under both packaging formats.