Investigating the potential of NIR spectroscopy for quality assessment of vacuum-packed and unpackaged sliced Iberian ham

Abstract

Near infrared spectroscopy (NIRS) is an extremely useful tool for quality control and traceability in the agri-food industry, particularly for high-value products such as 100 % ‘black seal’ sliced Iberian ham. The aim of this research was to study the feasibility of using NIRS technology to authenticate the quality of vacuum-packed and unpackaged sliced Iberian ham (59 black seal, 62 red seal, 56 green seal and 55 white seal samples), based on the development of predictive NIRS models for determining the fatty acid profile of the product. In this study, we used a bench-top instrument designed for laboratory applications, along with three portable near infrared (NIR) sensors with different optical configurations and technical specifications, suitable for in situ analysis. Regression models were formulated using NIR spectra and applying various signal pre-treatment methods. For the unpackaged samples, the best models achieved residual predictive deviation for cross-validation (RPD_cv) values of 1.85, 1.82, and 1.87 for palmitic, stearic, and oleic acids respectively, using the bench-top sensor. The linear variable filters (LVF) instrument proved to be the best instrument for in situ analysis, with RPD_cv values of 1.38, 1.28, and 1.42, for the three fatty acids analysed. For the vacuum-packed product and the LVF sensor, the RPD_cv values for the three fatty acids studied ranged between 1.37 and 1.46. The findings are encouraging for the sliced Iberian ham sector, highlighting the use of NIRS for the control of premium products. Nevertheless, further studies are needed to improve the prediction models and make them applicable.