Reinaldo F. Teófilo

Quimiometria II: planilhas eletrônicas para cálculos de planejamentos experimentais, um tutorial

This work describes, through examples, a simple way to carry out experimental design calculations applying an spreadsheets. The aim of this tutorial is to introduce an alternative to sophisticated commercial programs that normally are too complex in data input and output. An overview of the principal methods is also briefly presented. The spreadsheets are suitable to handle different types of computations such as screening procedures applying factorial design and the optimization procedure based on response surface methodology. Furthermore, the spreadsheets are sufficiently versatile to be adapted to specific experimental designs.

Physical–mechanical and antimicrobial properties of nanocomposite films with pediocin and ZnO nanoparticles

This work aimed to develop nanocomposite films of methyl cellulose (MC) incorporated with pediocin and zinc oxide nanoparticles (nanoZnO) using the central composite design and response surface methodology. This study evaluated film physical-mechanical properties, including crystallography by X-ray diffraction, mechanical resistance, swelling and color properties, microscopy characterization, thermal stability, as well as antimicrobial activity against Staphylococcus aureus and Listeria monocytogenes. NanoZnO and pediocin affected the crystallinity of MC. Load at break and tensile strength at break did not differ among films. NanoZnO and pediocin significantly affected the elongation at break. Pediocin produced yellowish films, but nano ZnO balanced this effect, resulting in a whitish coloration. Nano ZnO exhibited good intercalation in MC and the addition of pediocin in high concentrations resulted crater-like pits in the film surfaces. Swelling of films diminished significantly compared to control. Higher concentrations of Nano ZnO resulted in enhanced thermal stability. Nanocomposite films presented antimicrobial activity against tested microorganisms.

Computational performance and cross‐validation error precision of five PLS algorithms using designed and real data sets

An evaluation of computational performance and precision regarding the cross‐validation error of five partial least squares (PLS) algorithms (NIPALS, modified NIPALS, Kernel, SIMPLS and bidiagonal PLS), available and widely used in the literature, is presented. When dealing with large data sets, computational time is an important issue, mainly in cross‐validation and variable selection. In the present paper, the PLS algorithms are compared in terms of the run time and the relative error in the precision obtained when performing leave‐one‐out cross‐validation using simulated and real data sets. The simulated data sets were investigated through factorial and Latin square experimental designs. The evaluations were based on the number of rows, the number of columns and the number of latent variables. With respect to their performance, the results for both simulated and real data sets have shown that the differences in run time are statistically different. PLS bidiagonal is the fastest algorithm, followed by Kernel and SIMPLS. Regarding cross‐validation error, all algorithms showed similar results. However, in some situations as, for example, when many latent variables were in question, discrepancies were observed, especially with respect to SIMPLS. Copyright

QSPR Study of Passivation by Phenolic Compounds at Platinum and Boron-Doped Diamond Electrodes

= 0.851, and standard error of validation SEV = 0.097. A BDD model with one latent variable and four descriptors was built and validated in the same way; however, the statistical parameters Q2 = 0.333, R2 = 0.586, and SEV = 0.159 were of inferior quality with respect to the model for the Pt electrode. Both models were applied for prediction of 10 phenolic compounds. The Pt model showed to be suitable for predictive purposes. It was observed that passivation was much weaker on the BDD electrode than on the Pt electrode. Different interactions and reactions involving phenolics at the electrodes are the main reasons for such large differences between the models. Exploratory analyses were also performed and interpreted in terms of chemical concepts, such as phenolic reactivity, size/shape, hydrogen bonding, and electronic features. These findings can be useful to explore the possibility to predict phenolic passivation and to design electrochemical experiments involving different phenolic compounds. Furthermore, these PLS models aid in understanding electrode inactivation by phenolic compounds.

Correlation of quantitative sensorial descriptors and chromatographic signals of beer using multivariate calibration strategies.

In this study, two important sensorial parameters of beer quality - bitterness and grain taste - were correlated with data obtained after headspace solid phase microextraction - gas chromatography with mass spectrometric detection (HS-SPME-GC-MS) analysis. Sensorial descriptors of 32 samples of Pilsner beers from different brands were previously estimated by conventional quantitative descriptive analyses (QDA). Areas of 54 compounds systematically found in the HS-SPME-GC-MS chromatograms were used as input data. Multivariate calibration models were established between the chromatographic areas and the sensorial parameters. The peaks (compounds) relevant to build each multivariate calibration model were determined by genetic algorithm (GA) and ordered predictors selection (OPS), tools for variable selection. GA selected 11 and 15 chromatographic peak areas, for bitterness and grain taste, respectively; while OPS selected 17 and 16 compounds for the same parameters. It could be noticed that seven variables were commonly pointed out by both variable selection methods to bitterness parameter and 10 variables were commonly selected to grain taste attribute. The peak areas most significant to the evaluation of the parameters found by both variable selection methods fed to the PLS algorithm to find the proper models. The obtained models estimated the sensorial descriptors with good accuracy and precision, showing that the utilised approaches were efficient in finding the evaluated correlations. Certainly, the combination of proper chemometric methodologies and instrumental data can be used as a potential tool for sensorial evaluation of foods and beverages, allowing for fast and secure replication of parameters usually measured by trained panellists.

Estimation of cellulose crystallinity of sugarcane biomass using near infrared spectroscopy and multivariate analysis methods

A method for estimation of sugarcane (Saccharum spp.) biomass crystallinity using near infrared spectroscopy (NIR) and partial least squares regression (PLS) as an alternative to the standard method using X-ray diffractometry (XRD) is proposed. Crystallinity was obtained using XRD from sugarcane bagasse. NIR spectra were obtained of the same material. PLS models were built using the NIR and crystallinity values. Cellulose crystallinity ranged from 50 to 81%. Two variable selection algorithms were applied to improve the predictive ability of models, i.e. (a) Ordered Predictors Selection (OPS) and (b) Genetic Algorithm. The best model, obtained with the OPS algorithm, presented values of correlation coefficient of prediction, root mean squared error of prediction and ratio of performance deviation equals to 0.92, 3.01 and 1.71, respectively. A scatter matrix among lignin, α-cellulose, hemicellulose, ash and crystallinity was built that showed that there was no correlation among these properties for the samples studied.

Synthesis and Characterization of Magnetic Nanocrystalline Diamond Films

Magnetic semiconductors are promising materials for electronic applications, because it is possible to control the quantum state of the electron spin (up or down), providing almost total spin polarization. We present boron-doped nanocrystalline diamond samples with magnetic properties prepared by chemical vapor deposition process and characterized using X-ray photoelectron spectroscopy, energy dispersive X-ray spectroscopy, Raman spectroscopy, scanning electron microscopy and magnetization assays. We believe that ferromagnetic elements were incorporated into the diamond film by diffusion from stainless steel substrates, during film growth.

Influence of pH and Matrix Components in the Chromatographic Response of Pesticides

The pH effect of potato, apple, and soil matrices on the chromatographic response of nine pesticides was evaluated. All chromatographic analyses were performed in duplicate on a gas chromatograph with electron capture detection. The matrix effect observed in the chromatographic response of the pesticides was evaluated by comparison. We compared the chromatographic response of each pesticide in pure solvent and in organic extract obtained for the matrices. The organic extracts were obtained by solid–liquid extraction with partition at low temperature. Depending on the matrix pH, a greater or lesser amount of co-extractives can be extracted into the organic phase, which affects the matrix effect. The pH of the samples before the extraction process was modified in order to check their influence on pesticide responses. Statistical analyses involving principal component analysis and marginal means revealed that, in the potato and apple matrices, the co-extractives exerted positive effects on the chromatographic response of the analytes. At lower pH, the extraction of co-extractives from potato and apple was favored, thus increasing the matrix effect for these samples.

Multivariate Calibration to Determine Phorbol Esters in Seeds of Jatropha curcas L. Using Near Infrared and Ultraviolet Spectroscopies

The building of partial least squares (PLS) regression models using near infrared (NIR) and ultraviolet (UV) spectroscopies to estimate the concentrations of phorbol esters (PEs) in Jatropha curcas L. is presented. The models were built using two algorithms for variable selection, ordered predictors selection (OPS) and genetic algorithm (GA). Chromatographic analyses were performed to determine the concentrations of PEs. Spectral data were obtained from seeds and oil extract. The results of PLS models were performed by analyzing statistical parameters of quality such as root mean square error of prediction (RMSEP) and correlation coefficient of external predictions (Rp). The parameters obtained for NIR-PLS and UV-PLS models with OPS were respectively: RMSEP 0.48 and 0.22 mg g and Rp 0.49 and 0.96. For GA were obtained, respectively: RMSEP 0.52 and 0.28 mg g and Rp 0.12 and 0.95. The models built from seeds and oil extracts can be used respectively for screening and to accurately predict the PEs content. The OPS method provided simpler and more predictive models compared to those obtained by the selection of variables using the GA. Thus, the UV-PLS-OPS model can be used as an alternative method to quantification of PEs.

Extraction of pectin from ponkan (Citrus reticulata Blanco cv. Ponkan) peel: Optimization and structural characterization

A central composite experimental design was used to evaluate the influence of pH, extraction time and liquid:solid ratio on the yield and uronic acid content of the pectin from ponkan peel. The response surface methodology showed that the yield is positively influenced by lower pHs, longer extraction times and higher liquid:solid ratio, whereas the uronic acid content decreases with increasing extraction time. The conditions that resulted in the highest yield and highest uronic acid content were defined as pH 1.6, extraction time of 100 min and liquid:solid ratio of 36 mL/g. The pectin obtained under these conditions (PPOP) had an experimental yield of 25.6%, below the predicted theoretical value despite the good fit of the model (R2 = 0.96) and the galacturonic acid content was 84.5%, in close agreement with the predicted theoretical value. PPOP was composed mainly of a homogalacturonan with degree of methyl esterification of 85.7% and a rhamnogalacturonan I region mainly branched by galactans. In addition, PPOP had a very low degree of acetylation (0.1%) and average molar mass of 80,650 g/mol, determined by light scattering. The results showed that ponkan peel may be used as a source of citrus pectin in the regions where this species is cultivated.