Food additives are chemical substances added to improve organoleptic characteristics, in this context, there are several synthetic dyes, such as sunset yellow, tartrazine, erioglaucine, allura red, indigo carmine, and new coccine, that can also be identified through different analytical techniques such as infrared spectroscopy, UV-Vis spectrophotometry, high performance liquid chromatography with diode array detector and mass spectrometry. Therefore, the objective of this work was to compare methods developed for different analytical techniques, in order to identify the one that presents greater efficiency in certain applications. For this, the patterns of the dyes were analyzed, as well as their mixtures and foods that had them. As a result, the CLAE-DAD presents excellent selectivity and linearity of the calibration curves, but it presents higher LD and LQ values when compared to the UV-Vis, in turn the infrared provides information regarding functional groups and bonds. Mass spectrometry showed great capabilities in identifying the molecular formula and better selectivity in the absence of the erioglaucine dye. It is not feasible to indicate the best or worst analytical approach, but it is possible to point out which one is more suitable for each application. Regarding the quantification capacity, chromatography and UV-Vis are good alternatives, but in mixtures containing more than one dye, CLAE-DAD is more suitable due to the better selectivity. Regarding the identification capacity, mass spectrometry, especially FT-ICR MS, is the most appropriate technique to propose molecular formulas due to its high resolution and mass accuracy. The advantage of FTIR was the easier sample preparation, being able to analyze the dyes in the solid state.

This study proposed using a portable microscope combined with a smartphone and application (PhotoMetrix® application) to evaluate the authenticity of Brazilian banknotes (R$50 and R$100) and national driver’s licenses (NDL) through image acquisition (Samsung S7) and chemometric treatment (principal component analysis (PCA)). Six regions of the banknote were analyzed: holographic band; lower and upper tactile regions containing the number referring to the value of the note; microprints above the effigy (obverse); and numbers and the surroundings of the animal formed by microprints (reverse). For NDLs, the regions were the following: the coat of arms of the republic; the state map with microprints; optical ink variation; distorted positive microletters with technical failure; negative guilloche; typographic numbering; micro letter wire; and region with line printing. For the chemometric study with Photometrix®, we selected a region of interest (ROI) of 32 × 32 and 64 × 64 pixels with autoscaled data using the channels red (R), green (G), blue (B), hue (H), saturation (S), value (V), lightness (L) and intensity (I). We obtained excellent results for differentiating banknotes and NDLs, both by visual and chemometric analyses (PCA). This study demonstrates the effectiveness of using a portable microscope and a smartphone as a portable forensic tool that is fast, robust, low-cost and reliable.

The study of the spectrum of light has increased its range of action in the field of chemistry, with the help of several advanced equipment and innovative techniques that have become a strong ally of analytical chemistry. However, the simplicity of obtaining results integrated with mobile devices appears as an interesting path to be taken in the field of chemical analysis. This work addresses the dissemination of an application called REDGIM for smartphones on the Android platform capable of working with multivariate image analysis using chemometric methods through the luminous intensities of photos and R (red), G (green) and B (blue) channels. In order to show the potential of REDGIM, we propose two applications using the partial least squares (PLS) regression method: 1) quantification of free chlorine in tap water; and 2) quantification of cannabinol, (CBN, a type of cannabinoid) in marijuana and hashish samples. The free chlorine concentration obtained for two investigated samples was 0.73 and 0.74 mg L-1 and 0.74 and 0.76 mg L-1 by the spectrophotometer and by the application (container: cuvette), respectively. For the quantification of CBN in marijuana and hashish samples, the mean concentration ranged from 6.137 to 8.823 mg mL-1. The results obtained by the application are compatible with results from traditional techniques, such as UV-Vis spectrophotometry, for example. Therefore, REDGIM was proved to be a simple and accessible technological tool for the scientific community, being viable for chemical tests of a multivariate nature.

Beer is commonly produced with four inputs: water, malt, hops, yeast and, in some cases, brewing adjuncts. Industrial and artisanal processes essentially follow the same steps and may undergo minor changes due to the style of beer. Despite this, many consumers attribute higher quality to craft beer compared to industrial ones. In this study, we applied the analytical techniques of infrared (IR), hydrogen nuclear magnetic resonance (1H NMR) and mass spectrometry (ESI(±)FT-ICR MS) to discriminate craft beers from industrial ones (brands common to the Brazilian market). In addition, Partial Least Squares (PLS) and Support Vector Machine (SVR) regression were used to estimate some beer properties (pH, total acidity (meq·L-1, color (EBC), bitterness (IBU), alcohol content (%v/v) and density (g·mL-1)). The use of the IR allowed the identification of vibrations attributed to chemical compounds common to beverages, such as water (3320 and 1640 cm-1), carbohydrates (1500 cm-1) and ethanol (1050-1040 and 875-865 cm-1). 1H NMR showed good applicability in identifying classes of organic compounds in the beverage, where signs attributed to alcohols, organic acids, carbohydrates and amino acids were observed. The ESI(+)FT-ICR MS allowed the identification of chemical compounds present in beverages, allowing the construction of a fingerprint of the beers. In addition, the application of chemometric tools enabled the prediction of physicochemical properties, presenting promising results in the prediction of alcohol content (RMSEC 0.2430 and RMSEP 0.3929) and bitterness (RMSEC 1.3022 and RMSEP 1.6008), and also in the classification regarding the manufacturing process (craft and industrial beer).

The objective of this work was to control the purity level of canephora coffees (Conilon coffee) from the state of Espírito Santo (Brazil), as a function of the addition of grounds produced by the coffees themselves using a portable microspectrometer in the infrared region. (microNIR), associated with chemometric tools. The PCA model grouped the coffees according to the level of adulterant in the samples and showed that the presence of moisture and polysaccharides is important for the discrimination between pure and adulterated samples. PLS-DA and SIMCA classification models were built with commercial samples and resulted in the discrimination of authentic and non-authentic samples with accuracy values above 90% and 82% for PLS-DA and SIMCA, respectively. The quantification results presented by the PLS model were satisfactory for all models, reaching the best results at 75 °C with RMSEP values of 6.13 wt%, R2p = 0.9917; and LOD in the range of 5.6-8.9 wt%; LOQ = 17-26.8 wt%, according to IUPAC; relative standard deviation for repeatability of 1.0 and 1.7 wt%; and intermediate precision of 3.4 and 1.1 wt% for low (<10 wt%) and high (≈ 90 wt%) levels of adulterants, respectively. Therefore, this work represents the first exploratory study to analyze adulterations with coffee grounds by portable NIR, demonstrating the potential of the equipment against this type of adulteration.

Many instrumental techniques are used to monitor the quality of food products, highlighting near infrared spectroscopy (NIRS). In order to determine the authenticity of 60 commercial oil samples seized by the Espírito Santo state police, this work used a portable spectrometer in the NIR region associated with chemometric tools such as principal component analysis (PCA) and partial least squares regression (PLS) to classify and quantify possible adulterants present such as soybean oil. In addition, physicochemical tests (acidity, peroxide and ultraviolet absorption) were carried out on commercial samples. The PLS regression model built to quantify soybean oil showed a coefficient of determination (R2) greater than 0.99, showing itself to be satisfactory. The results showed that all samples analyzed had a high content of adulterant and cannot be classified as extra virgin olive oil.

Wax deposit is of a great concern in the petroleum industry and causes partial or total blockage of the pipelines. In this work, four Brazilian crude oils (P1-P4) and five inhibitors solutions (I1-I5) were used associating rheology results to understand, at a molecular level, the characteristics of the saturated fractions by high-resolution mass spectrometry (Orbitrap coupled to atmospheric pressure chemical ionization (APCI) source) and two-dimensional gas chromatography coupled to mass spectrometry (GC × GC-MS). The effectiveness of wax inhibitors can be demonstrated by the viscosity decrement. The characterization of the saturated fractions by GC × GC-MS and high resolution mass spectrometry showed that is possible to conclude that inhibitor I1 favored the inhibition process of paraffins when oils have a smaller and monocyclic saturated chain hydrocarbon (HC) profiles, whereas for oils with larger amounts of polycyclic chain HCs, the inhibitor I4 appeared to be the alternative.

A new method to identify the authenticity of Brazilian banknotes (R$) is proposed using digital image analysis by a smartphone application, Photometrix®, associated with chemometric tools. Authentic banknotes (n = 4) obtained in local bank and falsified (n = 12) by the author himself by means of three printers (laser-Deskjet®, wax-Color Qube® and inkjet-Deskjet®) were used for the development of the methodology. An experimental planning was performed to evaluate the authenticity of the banknotes determining: the best region (holographic band, tactile region in the lower left and right upper number, effigy microimpressions, lower number left, animal figure, watermark and puzzle); Region of Interest (ROI) (16x16; 32x32 and 64x64 pixels), focal length (8, 12, 15 and 20 cm) and variation of the smartphone (Motorola G5 Plus, Samsung S7 and LG K10). The best regions chosen were effigy microimpressions and round the animal. Promising results were obtained from ROI 16x16 pixels with focal length fixed at 10 cm. Thus, the application presents promising features for analyzing the authenticity of banknotes by digital images making it fast, non-destructive, portable, with low cost, and can be accessed by all society.

It has been recurring adulterations in fuels (such as gasoline, ethanol and diesel), being necessary the exploration of the use of more modern analytical techniques capable of controlling the quality of these fuels, since some regulated tests may be inefficient to detect the adulteration. Among them, it is highlighted proton nuclear magnetic resonance (1H NMR) spectroscopy, and portable near infrared spectroscopy (microNIR). In this work, it was studied the conformities of 115 samples of seized fuels (76 of gasoline, 23 of ethanol, and 16 of diesel) by means of standardized techniques with parameters established by the ANP. Results obtained were compared to photometer, MicroNIR and 1H NMR analyzes. The analyzes carried out by ANP showed four nonconforming samples (one of gasoline and three of ethanol). By the photometric technique, only 14 gasoline samples had ethanol content permitted by legislation (i.e ≈ 27 %v/v). By 1H NMR analysis, it was possible to verify nonconformities by presence of aromatics and olefins compounds in the gasoline and diesel samples as well as of methanol in fuel ethanol samples. It is also worth noting the efficiency of MicroNIR when combined with unsupervised chemometric methods to indicate nonconformities presented by 1H NMR and photometry techniques.

Corrosion processes were evaluated for AISI 316 and AISI 1020 steels by scanning electron microscopy (SEM), atomic force microscopy (AFM) and light microscopy. Coupons were immersed in four crude oil samples with different total acid numbers (TANs) for 48 days at room temperature. The steels were also exposed to three blends (B1-B3), produced by quaternary mixtures of the oils, with lower TANs than their respective original oils. SEM micrographs showed pitting-type corrosion in most cases. AFM imaging showed drastic changes in the peak-to-peak values, topographic profiles and phase images of the AISI 1020 coupons exposed to all oils and blend B3 as compared to the unexposed steel. Defects were produced on the surface of almost all the samples exposed to naphthenic corrosion. Exposure to the oil blends reduced the extent of the naphthenic corrosion on the coupons, especially blends B1 and B2. The oil mixtures (blends) reduced corrosion.

Phenolic compounds are important environmental contaminants due to their high toxicity and persistence in the environment. The use of enzyme-based electrochemical biosensors is a simple, sensitive and low-cost alternative for the determination of these pollutants in contaminated waters. However, in most cases, it is impossible to detect specific compounds in a mixture of phenols due to signal-overlap, as the instruments operate at very close potentials, given that the system is based on a single enzyme to detect similar structures. In order to overcome this problem, in the present work we have successfully used multivariate calibration with partial least squares (PLS) for the simultaneous determination of hydroquinone and guaiacol by a tyrosinase-based biosensor that was assembled using an enzyme extract from yam. The use of PLS allowed us to work with a large number of voltammograms, leading to a single mathematical model for the simultaneous determination of phenols of similar structure in real samples with concentration values of mmol L-1.

Competitive adaptive reweighted sampling-partial least squares (CARS-PLS) and negative-ion mode electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI(-) FT-ICR MS) data were adopted to assess the total acid number (TAN) of crude oil distillation cuts. Two crude oil samples and 24 derivatives with TAN ranging from 0.20 to 0.39 mg of KOH g-1 were investigated. The multivariate calibration PLS model was built with 18 calibration samples and tested with 8 validation samples. CARS-PLS reduced the number of variables from 1610 to only 4, allowing the identification of molecular formulas that are truly related to the TAN. The root mean square error of prediction (RMSEP) obtained was 0.01 mg of KOH g-1, which is lower than the error when using all variables (0.03 mg of KOH g-1). Finally, it was observed that the N and O2 compound classes are the most important classes for providing a better correlation between ESI(-) FT-ICR mass spectra and TAN values.

Jatropha curcas L. is an oil crop that has been studied as a potential source of biodiesel. A high protein pie is produced as a byproduct of the biodiesel production, which could be used as animal feed. However, the pie has toxic compounds, as phorbol esters and other toxins, which prevents the use as animal feed. For this reason, Embrapa (Brazilian Agricultural Research Corporation) has been working in genetic breeding to develop non-toxic J. curcas genotypes. To evaluate this process, a simple and fast analytical technique was employed to obtain responses in a short time. Leaf spray (LS) is a recent ambient ionization mass spectrometry technique in which the sample itself serves as support and ion source. Here, toxic and non-toxic J. curcas leaves were differentiated by LS using a linear ion trap mass spectrometer and partial least squares discriminant analysis (PLS-DA) model chemometrics. It was possible to differentiate toxic and non-toxic leaves and to identify the m/z values that contribute to discrimination between the groups.

Cocaine is usually seized mixed with a wide variety of adulterants such as benzocaine, lidocaine, caffeine, and procaine. The forensic identification of cocaine in these street drug mixtures is normally performed using colorimetric testing kits, but these tests may suffer from interferences, producing false-positive results. Here, we describe the use of analytical techniques including attenuated total reflection Fourier transform infrared (ATR-FTIR) and ultraviolet-visible (UV-VIS) spectroscopies to distinguish between cocaine and other adulterants (lidocaine, promethazine, powdered milk and yeast) that yield positive results on the Scott test using the thiocyanate cobalt reagent. A further 13 substances were also analyzed using the Scott test.

The quantity of salts in the crude oils depends on the origin and of the wells production and these salts cause several problems during the transport and the process of refine as corrosions, incrustations and deactivation of the employed catalysts in the refineries. In this study were implemented changes for improvements in the execution of ASTM D 6470 method and has also developed a new methodology of extraction system of salts using process of mechanical agitation without heating. The results of the optimization produce larger efficiency and safety to the process compared to the traditional ASTM method.