A method using dispersive liquid-liquid microextraction (DLLME) based on low density solvent (LDS) combined with liquid chromatography with diode array detection (LC-DAD) has been developed for determination of parabens. Some DLLME parameters such as kind and volumes of extraction and disperser solvents, pH of the aqueous samples, ionic strength, extraction, centrifugation and speed time, were investigated. The method exhibits good linearity (0.9990 to 0.9993), limits of detection (0.5-0.8 µg L-1), and limits of quantification (1.3-2.4 µg L-1). In optimum conditions, enrichment factors and recoveries of studied parabens obtained were 38.9 to 88.4% and 30.3 to 68.0%, respectively. Surface water samples collected from Mogi Guaçu River (São Paulo state, Brazil) were analyzed, showing average contents of methyl-, ethyl-, propyl-, and n-butylparaben of 8.0, 5.8, 13.1 and 15.1 µg L-1, respectively. This is the first study on parabens in a Brazilian River, in a long stretch of river (ca. 300 km of extension).

A correlação entre a composição química e os dados sensoriais de 28 amostras de cachaças foi investigada através de análise de componentes principais (PCA). Um modelo químico usando análise discriminante linear (LDA) para classificar as amostras de cachaças de acordo com suas qualidades sensoriais foi então elaborado. Este modelo apresentou habilidades preditivas de calibração e validação de 87,4 e 100%, respectivamente, e foi capaz de reconhecer corretamente 7 dentre 9 amostras adicionais, apresentando-se como uma ferramenta alternativa potencial para o reconhecimento das qualidades sensoriais de cachaças.

The correlation between the chemical composition and the sensory data for 28 cachaça samples was investigated using principal component analysis (PCA). A chemical model was then developed using linear discriminant analysis (LDA) to classify the distillate samples according to their sensory qualities. This model presented predictive abilities of calibration and validation of 87.4 and 100%, respectively, and was able to recognize correctly 7 out of 9 additional samples according to their sensory evaluations, showing itself as a potential alternative tool of recognizing cachaça sensory qualities.

As concentrações de 39 compostos orgânicos foram determinadas em três frações (cabeça, coração e cauda) obtidas da destilação em alambique do caldo de cana fermentado. Os resultados foram avaliados utilizando-se análise de variância (ANOVA), teste de Tukey, análise de componentes principais (PCA), agrupamento hierárquico (HCA) e análise discriminante linear (LDA). De acordo com PCA e HCA, os dados experimentais conduzem à formação de três agrupamentos. As frações de cabeça deram origem a um grupo mais definido. As frações coração e cauda apresentaram alguma sobreposição coerente com sua composição em ácidos. As habilidades preditivas de calibração e validação dos modelos gerados pela LDA para a classificação das três frações foram de 90,5 e 100%, respectivamente. Este modelo reconheceu como coração doze de treze cachaças comerciais (92,3%) com boas características sensoriais, apresentando potencial para a orientação do processo de cortes.

Concentrations of 39 organic compounds were determined in three fractions (head, heart and tail) obtained from the pot still distillation of fermented sugarcane juice. The results were evaluated using analysis of variance (ANOVA), Tukey's test, principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). According to PCA and HCA, the experimental data lead to the formation of three clusters. The head fractions give rise to a more defined group. The heart and tail fractions showed some overlap consistent with its acid composition. The predictive ability of calibration and validation of the model generated by LDA for the three fractions classification were 90.5 and 100%, respectively. This model recognized as the heart twelve of the thirteen commercial cachaças (92.3%) with good sensory characteristics, thus showing potential for guiding the process of cuts.