Chemometrics is a subfield of chemistry that emerged from advances in analytical instrumentation and computing. When seeking to solve chemical problems that depend on many concomitants experimental variables, chemometrics can be employed in order to extract as much information as possible in the least possible number of experiments. In addition, it is possible to evaluate the important effects and interactions among the variables to understand the processes being monitored in each system. In this sense, this article aimed to develop a didactic experiment of caffeine extraction using an espresso machine, applying the 25-1 fractional factorial design. The variables studied were temperature (75 and 78 °C), pressure (2 and 15 bar), granulation (bean and ground), type of coffee (special and traditional) and period of the day (morning and afternoon) to obtain maximum extraction of caffeine. The coffee extracts obtained were analyzed using UV-Vis molecular absorption spectrophotometry. The developed experiment showed the potential to spread the application of chemometrics in the academic environment and to facilitate the teaching of fractional factorial design.

Determining inorganic constituents in illicit drugs can indicate its purity and presence of adulterants. In this study, we analyzed 52 street cocaine samples, seized in three different regions of Espírito Santo, state of Brazil. Inductively coupled plasma optical emission spectrometry was used to determine Al, Ca, Cu, Fe, Mn, Mg, Zn concentrations and inductively coupled plasma mass spectrometry to determine Mo, Co, Pb and P concentrations. From analyte recovery tests, the accuracy was considered acceptable and the proposed method satisfactory. Most of the samples exhibited a relatively homogeneous inorganic profile with similar concentrations of investigated elements, however some samples had very discrepant concentrations. High concentrations of Al, Ca, Fe, Mg, Mn, and P were found, indicating that adulterants such as gypsum, marble powder, limestone, cement, and others must be used to increase the profitability of the illicit drug market.

A teaching experiment on supervised pattern recognition in chemometrics was proposed in this tutorial to introduce partial least squares discriminant analysis (PLS-DA). A new approach of the experiment published in the first tutorial of this series was revisited and employed to the classification of edible vegetable oils. The spectra of olive, canola, soybean and corn oils were obtained using an attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectrometer in the range of 600 to 4000 cm-1. The combination of ATR-FTIR and PLS-DA classification method was able to correctly classify 100% of the validation samples. The Matlab commands, routines and functions were presented, and a didactic explanation of the concepts and interpretation of the data was provided.

Black pepper is one of the most consumed spices worldwide and the evaluation of trace elements content is essential to promote consumer safety. In this study, concentrations of the elements As, Cd, Co, Cu, Fe, Mn, Mo, Ni, Pb, Se, V and Zn was determined in samples of black peppercorn (n = 25) and ground black pepper (n = 25) to verify how processing affects element concentrations. The elements were determined by inductively coupled plasma mass spectrometry and flame atomic absorption spectrometry. A principal component analysis showed that Fe, Pb and V was influenced by the processing and ground black pepper samples showed higher levels for these elements than black peppercorn. Although specific legislation for spices is not available in Brazil, results indicated that Pb concentrations in two brands of the processed samples under investigation exceeded the maximum level established by Brazilian and European legislation for vegetables and fruits. These results point to the necessity to control the processing of the black pepper, especially the grinding step.

The aim of this manuscript was to show the basic concepts and practical application of Partial Least Squares (PLS) as a tutorial, using the Matlab computing environment for beginners, undergraduate and graduate students. As a practical example, the determination of the drug paracetamol in commercial tablets using Near-Infrared (NIR) spectroscopy and Partial Least Squares (PLS) regression was shown, an experiment that has been successfully carried out at the Chemical Institute of Campinas State University for chemistry undergraduate course students to introduce the basic concepts of multivariate calibration in a practical way.