Paulo R. Filgueiras

Quantification of animal fat biodiesel in soybean biodiesel and B20 diesel blends using near infrared spectroscopy and synergy interval support vector regression.

In this work, multivariate calibration based on partial least squares (PLS) and support vector regression (SVR) using the whole spectrum and variable selection by synergy interval (siPLS and siSVR) were applied to NIR spectra for the determination of animal fat biodiesel content in soybean biodiesel and B20 diesel blends. For all models, prediction errors, bias test for systematic errors and permutation test for trends in the residuals were calculated. The siSVR produced significantly lower prediction errors compared to the full spectrum methods and siPLS, with a root mean squares error (RMSEP) of 0.18%(w/w) (concentration range: 0.00%-69.00%(w/w)) in the soybean biodiesel blend and 0.10%(w/w) in the B20 diesel (concentration range: 0.00%-13.80%(w/w)). Additionally, in the models for the determination of animal fat biodiesel in blends with soybean diesel, PLS and SVR showed evidence of systematic errors, and PLS/siPLS presented trends in residuals based on the permutation test. For the B20 diesel, PLS presented evidence of systematic errors, and siPLS presented trends in the residuals.

Prediction of the distillation temperatures of crude oils using 1H NMR and support vector regression with estimated confidence intervals

This paper aims to estimate the temperature equivalent to 10% (T10%), 50% (T50%) and 90% (T90%) of distilled volume in crude oils using (1)H NMR and support vector regression (SVR). Confidence intervals for the predicted values were calculated using a boosting-type ensemble method in a procedure called ensemble support vector regression (eSVR). The estimated confidence intervals obtained by eSVR were compared with previously accepted calculations from partial least squares (PLS) models and a boosting-type ensemble applied in the PLS method (ePLS). By using the proposed boosting strategy, it was possible to identify outliers in the T10% property dataset. The eSVR procedure improved the accuracy of the distillation temperature predictions in relation to standard PLS, ePLS and SVR. For T10%, a root mean square error of prediction (RMSEP) of 11.6°C was obtained in comparison with 15.6°C for PLS, 15.1°C for ePLS and 28.4°C for SVR. The RMSEPs for T50% were 24.2°C, 23.4°C, 22.8°C and 14.4°C for PLS, ePLS, SVR and eSVR, respectively. For T90%, the values of RMSEP were 39.0°C, 39.9°C and 39.9°C for PLS, ePLS, SVR and eSVR, respectively. The confidence intervals calculated by the proposed boosting methodology presented acceptable values for the three properties analyzed; however, they were lower than those calculated by the standard methodology for PLS.

Membrane lipid profile monitored by mass spectrometry detected differences between fresh and vitrified in vitro-produced bovine embryos.

This study aimed to evaluate the impact of vitrification on membrane lipid profile obtained by mass spectrometry (MS) of in vitro-produced bovine embryos. Matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) has been used to obtain individual embryo membrane lipid profiles. Due to conditions of analysis, mainly membrane lipids, most favorably phosphatidylcholines (PCs) and sphingomyelins (SMs) have been detected. The following ions described by their mass-to-charge ratio (m/z) and respective attribution presented increased relative abundance (1.2-20×) in the vitrified group: 703.5 [SM (16:0) + H]+; 722.5 [PC (40:3) + Na]+; 758.5 [PC (34:2) + H]+; 762.5 [PC (34:0) + H]+; 790.5 [PC (36:0) + H]+ and 810.5 [PC (38:4) + H]+ and/or [PC (36:1) + Na]+. The ion with a m/z 744.5 [PCp (34:1) and/or PCe (34:2)] was 3.4-fold more abundant in the fresh group. Interestingly, ions with m/z 722.5 or 744.5 indicate the presence of lipid species, which are more resistant to enzymatic degradation as they contain fatty acyl residues linked through ether type bonds (alkyl ether or plasmalogens, indicated by the lowercase e and p, respectively) to the glycerol structure. The results indicate that cryopreservation impacts the membrane lipid profile, and that these alterations can be properly monitored by MALDI-MS. Membrane lipids can therefore be evaluated by MALDI-MS to monitor the effect of cryopreservation on membrane lipids, and to investigate changes in lipid profile that may reflect the metabolic response to the cryopreservation stress or changes in the environmental conditions.

A survey of adulterants used to cut cocaine in samples seized in the Espírito Santo State by GC-MS allied to chemometric tools

Cocaine is a stimulant drug of the central nervous system (CNS) extracted from the leaves of Erytroxylum coca. It is defined as a tropane alkaloid containing 1R-(exo,exo)-3-(benzoyloxy)-8-methyl-8-azabicyclo[3.2.1]octane-2-carboxylic acid methyl esther. However, despite its defined composition, a wide variety of chemical additives are present in cocaine found in the illicit market, such as benzocaine, lidocaine, caffeine, procaine and phenacetin. In this work, 512 cocaine samples seized by the Civil Police of Espirito Santo state (PC-ES, Brazil) were analyzed by gas chromatography mass spectrometry (GC-MS) allied to principal component analysis (PCA) in order to classify the samples as a function of seizure year (2008, 2009, 2010, 2011 and 2012) and location (metropolitan, north, south and central). The cocaine content (wt.%) and its adulterants were also estimated. Analyzing the samples seized between 2008 and 2011, three sample sets are clearly grouped according to the degree of adulteration with caffeine and lidocaine: 100-50 wt.% of cocaine; 50-20 wt.% of cocaine; and 20-80 wt.% of lidocaine and 60-80 wt.% of caffeine, simultaneously. The last group is formed by samples seized between 2008 and 2009, which proves the higher degree of adulteration during this period. In 2012, higher cocaine content was observed for the 191 analyzed samples than in samples from previous years. The PCA data also suggests that the metropolitan region samples had a higher degree of adulteration than the state countryside samples.

Estudo do teste de Scott via técnicas espectroscópicas: um método alternativo para diferenciar cloridrato de cocaína e seus adulterantes

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.

Assessment of robustness on analysis using headspace solid-phase microextraction and comprehensive two-dimensional gas chromatography through experimental designs.

Plackett-Burman experimental design was applied for the robustness assessment of GC×GC-qMS (Comprehensive Two-Dimensional Gas Chromatography with Fast Quadrupolar Mass Spectrometric Detection) in quantitative and qualitative analysis of volatiles compounds from chocolate samples isolated by headspace solid-phase microextraction (HS-SPME). The influence of small changes around the nominal level of six factors deemed as important on peak areas (carrier gas flow rate, modulation period, temperature of ionic source, MS photomultiplier power, injector temperature and interface temperature) and of four factors considered as potentially influential on spectral quality (minimum and maximum limits of the scanned mass ranges, ions source temperature and photomultiplier power). The analytes selected for the study were 2,3,5-trimethylpyrazine, 2-octanone, octanal, 2-pentyl-furan, 2,3,5,6-tetramethylpyrazine, and 2-nonanone e nonanal. The factors pointed out as important on the robustness of the system were photomultiplier power for quantitative analysis and lower limit of mass scanning range for qualitative analysis.

Validation of the near infrared spectroscopy method for determining soil organic carbon by employing a proficiency assay for fertility laboratories

Current research indicates that near infrared (NIR) spectroscopy is the most promising alternative technique for the determination of soil organic carbon (SOC) in laboratories worldwide and that it may serve as a total or partial replacement for the traditional wet chemistry methods. In this research, NIR spectroscopy was developed and validated as a method for the determination of SOC aiming to promote the use of NIR technology in the soil laboratories of Brazil as a routine analysis method. To this end, multivariate calibration models were constructed from a large number of soil samples (1490 samples) that encompassed the variability of Brazilian soils. These models were validated by submitting the concentrations of soil organic matter (SOM) as determined by NIR spectroscopy to the proficiency assay for fertility laboratories, which is coordinated by the Brazilian Agricultural Research Corporation (Embrapa Soils). The proposed methodology using NIR spectroscopy received the excellence index of quality, which gives a certificate seal issued by the interlaboratory programme. Therefore, the robustness of the NIR method was proved in a conclusive way by a proficiency test programme dedicated to evaluating the reference method for SOM determination employed by over a hundred soil laboratories in Brazil.

Experimento didático de quimiometria para calibração multivariada na determinação de paracetamol em comprimidos comerciais utilizando espectroscopia no infravermelho próximo: um tutorial, parte II

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.

Quantification of the contents in biojet fuel blends using near infrared spectroscopy and multivariate calibration

In this work a methodology was developed for the quantification of the contents of petroleum-derived hydroprocessed esters and fatty acids (HEFAs) and farnesane jet fuels in binary and ternary mixtures using near infrared spectroscopy and multivariate calibration based on partial least squares (PLS) regression. The developed models are simpler, faster and cheaper when compared to the standard reference method ASTM D6866-12, with a further advantage of differentiation between biofuels. Petroleum-derived jet fuel and biofuels were determined in binary blends with a root mean square error of prediction (RMSEP) value of 0.48% (v/v) for both HEFA and petroleum-derived jet fuels, with a limit of detection of 0.56% (v/v). Ternary blends presented values of RMSEP of 0.69% (v/v), 0.35% (v/v) and 0.44% (v/v) for HEFA, farnesane and petroleum-derived jet fuels, respectively, with limits of detection in the range of 0.12 to 0.24% (v/v). The developed models, based on bias and permutation tests, did not present systematic errors and trends in residuals, turning them appropriately for analysis of biojet fuel blends.