Tilapia (Oreochromis niloticus) is the most cultivated fish species in Brazil. Studies have shown that fish consumption is related to the prevention of cardiovascular diseases due to its high contents of polyunsaturated fatty acids, as omega-3 (n-3) and omega-6 (n-6). In this sense, a new method to determine omega-3 and omega-6 by near-infrared (NIR) spectroscopy and multivariate calibration based on partial least squares (PLS) was proposed. Spectra of fillets of Nile tilapias packed under vacuum were obtained and compared to the reference method (gas chromatography) used for quantification of fatty acids. The outliers were evaluated in the models that were validated by calculation of the parameters for model performance estimation, showing promising results. The appropriate values achieved for accuracy, limits of detection and quantification, indicate that the NIR/PLS models can be an alternative to chromatography in the determination of omega-3 and omega-6 in fillets of Nile tilapia. Furthermore, the spectra acquisition on the vacuum-packed fillet contributes to the NIR/PLS method in terms of cost and quickness.

In this work the vitamin C was determined in industrialized nectar juices through ultraviolet (UV) spectroscopy and multiproduct multivariate calibration, based on partial least squares (PLS) regression. Since samples with different flavors, sugar content (light or not) were together in the model construction, it can be considered as a multiproduct and, due to the heterogeneity of the samples, it was necessary to optimize the calibration and validation sets by outliers elimination. The model was developed and validated by the evaluation of the figures of merit such as: accuracy, sensitivity, analytical sensitivity, adjust, linearity, relative prediction deviation, limits of detection and quantification, indicating that the multiproduct model developed from UV spectroscopy and PLS regression can be used in the industrial routine analysis as an alternative to titration or other time and reagent consuming methods. Here, it was evidenced that the UV-PLS multiproduct model provides advantages as being free of sample preparation steps, is suitable to be updated in order to measure other parameters, does not generates residues and is feasible to be implemented for on-line monitoring. Furthermore, the application of multivariate calibration in multiproduct models is extremely attractive from the industrial point of view.