Kohonen Neural Network maps were used for exploratory analysis of Brazilian Pilsner beers. The input data consisted of the peak areas of the volatile profile compounds of samples obtained after headspace solid phase microextraction coupled to gas chromatography. The chromatographic peaks were identified as originating from compounds such as alcohols, esters, organic acids, phenolic compounds, ketone and others typically found in the headspace of such samples. Analysis of the Kohonen maps showed that the 20 different brands of beer could be grouped into six sets, with three of these sets having only one sample, according to the composition of their volatile fractions. The volatile species associated with the similarities and differences between each sample group were tentatively identified by mass spectrometry and their contributions to the grouping are discussed.

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A voltammetric procedure optimized by experimental design for glyphosate determination in soil, water and vegetable samples is described. The voltammetry experiments were performed using a hanging mercury drop electrode (HMDE). The DPV variables involved in the optimization process were: voltage step, pulse amplitude, pulse interval, voltage step time and concentration of the supporting electrolyte. A full 2 5 factorial design was chosen to evaluate these effects. From the results obtained by the factorial design the three most important factors were determined. These variables were evaluated with a central composite design. Under the optimized conditions, the operational range was from 0.050 to 100.0 mg dm-3 and the detection and quantification limits were 14 and 48 µg dm-3 , respectively. The optimized method was successfully applied to glyphosate determination in soil, water and vegetables after purifying with an ion exchange resin and derivation.

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This study focuses on the determination of the chemical profile of 24 non-aged Brazilian artisanal sugarcane spirits (cachaça) samples through chromatographic quantification and chemometric treatment via principal component analysis (PCA) and Kohonen’s neural network. In total, forty-seven (47) chemical compounds were identified in the samples of non-aged artisanal cachaça, in addition to determining alcohol content, volatile acidity, and copper. For the PCA of the chemical compounds’ profile, it could be observed that the samples were grouped into seven groups. On the other hand, the variables’ bearings were grouped together, making it difficult to separate the components in relation to the sample groups and reducing the chances of obtaining all the necessary information. However, by using a Kohonen’s neural network, samples were grouped into eight groups. This tool proved to be more accurate in the groups’ formation. Among the chemical classes of the compounds observed, esters stood out, followed by alcohols, acids, aldehydes, ketones, phenol, and copper. The abundance of esters in these samples may suggest that these compounds would be part of the regional standard for cachaças produced in the region of Salinas, Minas Gerais.

Contaminants of emerging concern are organic compounds used in large quantities by the society for various purposes. They have shown biological activity at low concentrations, which gives great environmental relevance. The difficulty to detect and quantify contaminants of emerging concern in the environment stimulates the development of appropriate analytical methods. In this work a chemometric approach to positive and negative electrospray ionization (ESI) optimization for the simultaneous determination of contaminants of emerging concern in water samples by liquid chromatography-ion trap-time of flight-high resolution mass spectrometry (LC-IT-TOF-HRMS) was applied. Three types of phase modifiers were used: formic acid, ammonium hydroxide and formic acid/ammonium formate. The effects of operational parameters such as mobile phase modifier concentrations, mobile phase flow rate, heating block temperature and drying gas flow rate were evaluated by the 2 4 − 1 fractional factorial experimental design, resolution IV, in the screening phase and by Doehlert experimental design. Initial factorial experimental design studies indicated that the phase modifier ammonium hydroxide was more efficient compared to the other evaluated modifiers. It provided higher ion intensities to the majority of analytes. Doehlert experimental design allowed finding a region indicative of the optimum experimental conditions for most analytes. The best experimental condition observed was 3.5 mM ammonium hydroxide concentration; 0.0917 mL/min of mobile phase; 300°C heating block temperature; and drying gas at 200 kPa. These optimized parameters resulted in decreased detection limits of the method. The optimized method was applied to the evaluation of water samples coming from the Rio Doce basin -Minas Gerais/Brazil utilizing multivariate exploratory techniques such as principal component analysis and Kohonen neural network. In this way, the use of chemometric approach showed to be a promising way to optimize the simultaneous determination of twentyone contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS using ESI.