Use of color based chromatographic images obtained from comprehensive two-dimensional gas chromatography in authentication analyses.

Comprehensive two-dimensional gas chromatography (GC×GC) has been an important technique used to acquire as much information as possible from a wide variety of samples. Qualitative contour plots analysis provides useful information and in daily use it ends up being handled as images of the volatile organic compounds by analysts. Cachaça samples are used in this paper to showcase the use of two-dimensional chromatographic images as the main source for authentication purposes through one-class classifiers, such as data-driven soft independent modeling of class analogy (DD-SIMCA).

Portable NIR spectrometer for quick identification of fat bloom in chocolates.

Cocoa butter provides desirable sensory properties to chocolates; however, the exposure of chocolate to temperature variations during transportation and/or storage can lead to changes in the polymorphic form of butter, with the appearance of a dull-white film on the chocolate surface, known as fat bloom. This study investigated the use of a portable NIR spectrometer combined with chemometric tools to discriminate milk chocolate, white chocolate, 40% cocoa chocolate, and 70% cocoa chocolate samples, which were subjected to temperature abuse for 6 hours. The PCA allowed separating the samples into three classes: control at 20 °C, chocolate subjected to 35 °C, and chocolate subjected to 40 °C, for each type of chocolate studied.

Evaluation of the acidic strengths on electronic ground and excited states of proton transfer dye using Excitation-Emission fluorescence matrix (EEM) and Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS).

Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) was for the first time successfully used to evaluate an intricate photophysical behavior, where deprotonation on the electronic ground state (S), intra and intermolecular proton transfer processes (ESPT and ESIPT) on the electronic excited state (S) can simultaneously be presented. In this sense, the organic dye 2-(2'-hydroxyphenyl)benzothiazole (HBT) was used as a proof-of-concept model, where MCR-ALS showed to be a powerful tool for discriminate chemical reactions that occur concomitantly on different potential energy surfaces, which include photochemical reactions. As a result, the chemometric method showed to be a straightforward approach for the determination of the acidic strengths of those equilibria were estimated as 8.

Authentication and identification of adulterants in virgin coconut oil using ATR/FTIR in tandem with DD-SIMCA one class modeling.

This study evaluates the use of Fourier transform infrared spectroscopy with attenuated total reflectance (ATR/FTIR) in tandem with data driven soft independent modeling of class analogy (DD-SIMCA) to check authenticity and monitor virgin coconut oil adulteration. By using infrared spectra of pure samples and samples adulterated with canola, corn, sunflower and soybean, one class models were developed to evaluate the authenticity and adulteration of virgin coconut oil. The proposed methodology was able to confirm the authenticity and to detect the adulteration with all tested oils in a concentration range of 10-40%.

Paper-based SERS substrate and one-class classifier to monitor thiabendazole residual levels in extracts of mango peels.

The assessment of pesticide residue levels demands fast, low cost and easy-to-use procedures which are not found in conventional methods. In this work, SERS substrates based on the deposition of gold nanoparticles (GNPs) on common office paper were prepared using a wax printer. These substrates combined with Data Driven Soft Independent Modelling of Class Analogies (DD-SIMCA), a one-class classifier algorithm, were used for detection of pesticide residues in water extracts of mango peels.