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An alternative method to predict distillation temperatures (DTs) in Brazilian crude oil samples using 1H nuclear magnetic resonance (1H NMR) spectroscopy in association with partial least squares (PLS) regression is proposed. From the acquisition of 1H NMR spectra of 74 crude oil samples along with their DTs obtained by gas chromatography, PLS models were built to predict DTs from 5 to 90% distilled. In calibration and prediction steps, coefficients of multiple determination (R2) and root-mean-square errors (RMSEs) were monitored throughout the studied range. The root-mean-square error of prediction (RMSEP, %) was the most important modeling parameter monitored, showing a decreasing behavior across the studied range and present values lower than 5% for some models. The residual analysis through bias and non-parametric permutation tests were taken into account for each built model. Lastly, the curves of DTs estimated by chemometrics, named DTEC, were faced with simulated distillation (SimDis) for each prediction sample. The developed methodology by 1H NMR–PLS can be successfully applied to Brazilian and similar crude oil samples to determine DTs from 5 to 90% distilled.

A review of the literature covering the evolution of amino acid, protein, lipid and carbohydrate analysis in food samples by electromigration techniques over the last 20 years is presented. The manuscript summarizes different modes, including capillary zone electrophoresis, micellar electrokinetic chromatography, capillary electrochromatography, capillary gel electrophoresis, capillary isotachophoresis, non-aqueous (or nonaqueous) capillary electrophoresis, capillary isoelectric focusing and microfluidic chip electrophoresis, employing different detection systems, such as ultraviolet-visible absorption, laser-induced fluorescence, mass spectrometry, amperometric detection, and capacitively coupled contactless conductivity detection. Briefly, the present review evidences that CE is a very interesting analytical separation technique for food analysis, offering short analysis times and versatility in a simple sample preparation step as inherent advantages compared to classical chromatographic methodologies, which make it a separation technique that is very attractive for quality control in industry and government agencies.