Multi-product multivariate calibration: Determination of quality parameters in soybean industrialized juices

Abstract

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.