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.

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<p>The determination of the total acid using UV spectroscopy and multi-product multivariate calibration is presented as an alternative to the conventional method through potentiometric titration. The model was developed including different products (fruit nectar of different flavors and light fruit nectar) where outliers samples were identified and excluded. Partial least squares (PLS) regression was used in order to build the model. Accuracy, represented by the values of the Root Mean Squared Errors of Calibration (RMSEC) and Prediction (RMSEP) were 0.0641 and 0.0534 mg/100 mL, respectively. The confidence ellipse confirms that accuracy was achieved at 99 % confidence, while residues showed random behavior, confirming linearity for the model developed. The proposed methodology shows advantages as fastness, does not requires sample preparation and does not generate toxic waste, being an alternative to the conventional method based on potentiometry.</p><p>&nbsp;</p><p>DOI: 10.14685/rebrapa.v6i1.177</p>

ResumoA pesca assume importante papel na economia brasileira; oferece mão de obra e renda, além de alimento para população. Porém, os dados estatísticos sobre a pesca marinha no Brasil são insuficientes, por ser uma atividade basicamente extrativista, descentralizada e cercada de grande informalidade. Um dos principais problemas enfrentados é a quantificação da sua importância econômica. Por isso, o presente trabalho reúne e analisa os dados da produção de peixes nas regiões brasileiras, na época de 2000 a 2007. Os resultados permitem situar o contexto nacional da produção da pesca, de forma que podem ser observadas as regiões que mais produziram, destacando a pesca artesanal do Norte e Nordeste do país.

Total acidity and vitamin C were determined by using ultraviolet spectroscopy and multi-product multivariate calibration alternately to the reference methods, the potentiometry and Tillman's, respectively. In the developed multi-products models, different products were included (industrialized juices based on soya of different flavors and light). The linear partial least squares (PLS) method was used in the model construction and the outlier samples were evaluated. The accuracy at the 99% level, represented by the root mean square error of calibration (RMSEC) and prediction (RMSEP), was confirmed through the confidence ellipse, whereas the residuals presented random behavior, which indicates that the data fit a linear model. Sensitivity and analytical sensitivity presented adequate results in the determination of vitamin C and acidity, considering the concentration range used 0.83-16.83 mg 100 mL-1 for vitamin C and 0.17-0.34 g 100 mL-1 for total acidity. The inverse of the analytical sensitivity shows that it is possible to distinguish samples with difference in vitamin C concentration of the order of 0.73 mg 100 mL-1, and samples with difference in total acidity of the order of 6.1 x 10-3 g 100 mL- 1.The multi-product PLS model present limits of detection and quantification for vitamin C of 2.43 and 7.36 mg 100 mL-1, respectively. For total acidity, the limits of detection and quantification achieved were 0.02 and 0.06 mg 100 mL-1, respectively. The values for residual prediction deviation (RPD) presented results within the range of values, which classify the models as satisfactory. In addition, the multi-product calibration is fast, because it does not require reagents/solvents and does not generate toxic waste, being an alternative to the conventional methods and being in agreement with the requirements of green chemistry.