1H NMR Mixture Design-Fingerprints and ASCA Analysis in Ilex paraguariensis: Model Stability in Search of a Global Metabolome.

The effects of experimental repetitions and solvent extractors on the 1H NMR fingerprinting of yerba mate extracts, obtained from two genders and two light environments, were analyzed in-depth by ANOVA-simultaneous component analysis (ASCA). Different solvents were used according to a mixture design based on ethanol, dichloromethane, and hexane and their combinations. The number of experimental repetitions significantly affected the ASCA results. Increasing repetitions led to decreases in the percentage effect variance values and an increase in the percentage residual variance. However, secondary sexual dimorphism, light availability, and their interaction effects became more significant with decreasing p-values at or above the 95% confidence level. The choice of a solvent extractor significantly affects the chemical profile and can lead to distinct conclusions regarding the significance of effect values. Pure solvents yielded different conclusions about the significance of factorial design effects, with each solvent extracting unique metabolites and maximizing information for specific effects. However, the use of binary solvent mixtures, such as ethanol-dichloromethane, proved more efficient in extracting sets of compounds that simultaneously differentiate between different experimental conditions. The mixture design-fingerprint strategy provided satisfactory results expanding the range of extracted metabolites with high percentage of residual variances and low explained percentage effect variances in the ASCA models. Ternary and even higher-ordered mixtures could be good alternative extracting media for work-intensive procedures. Our study underscores the significance of experimental design and solvent selection in metabolomic analysis, improving the accuracy, robustness, and interpretability of metabolomic models, leading to a better understanding of the chemical composition and biological implications of plant extracts.

Authentication of carioca common bean cultivars (Phaseolus vulgaris L.) using digital image processing and chemometric tools.

Bean authentication can result in higher quality products for commerce. Partial least squares discriminant analysis (PLS-DA) was applied to digital images in order to develop a methodology that allows the non-destructive discrimination of three Phaseolus vulgaris L. cultivars (Agro ANfc9, IPR-Andorinha, and IPR-Sabiá) having different technological characteristics. Principal component analysis resulted in a separation of these cultivars, but with a certain amount of overlap. Supervised analysis showed that three PLS1-DA models, each for two cultivars, was moderately better than the simultaneous treatment of all three cultivars (PLS2-DA). Permutation test evaluated statistical significance of PLS-DA models. The classification models were more accurate for Agro ANfc9 and IPR-Sabiá cultivars than for IPR-Andorinha. The Agro ANfc9-IPR-Sabiá model correctly classified 100% of the two bean classes in both training and test sets. This analytical strategy is fast, inexpensive, environmentally friendly, and can be applied for bean quality control helping cultivar authenticity for commerce.

Ecometabolic mixture design-fingerprints from exploratory multi-block data analysis in Coffea arabica beans from climate changes: Elevated carbon dioxide and reduced soil water availability.

Ecometabolic mixture design-fingerprinting in coffee cultivated under climate change was chemically explored using ComDim. Multi-blocks were formed using UV, NIRS, 1H NMR, SWV, and FT-IR data. ComDim investigated all these different fingerprints according to the extractor solvent and in virtue of atmospheric CO2 increase. Ethanol and ethanol-dichloromethane showed the best separations due to CO2 environment. 1H NMR loading indicate increases of fatty acids, caffeine, trigonelline, and glucose in beans under current CO2 levels, whereas quinic acid/chlorogenic acids, malic acid, and kahweol/cafestol increased in beans under elevated CO2 conditions. SWV indicated quercetin and chlorogenic acid as important compounds in coffee beans cultivated under current and elevated CO2, respectively. Based on the ethanol and ethanol-dichloromethane fingerprints, k-NN correctly classified the beans cultivated under different carbon dioxide environments and water availabilities, confirming the existence of metabolic changes due to climate changes. SWV proved to be promising compared with widely used spectrometric methods.

The main effects of elevated CO2 and soil-water deficiency on 1H NMR-based metabolic fingerprints of Coffea arabica beans by factorial and mixture design.

The metabolic response of Coffea arabica trees in the face of the rising atmospheric concentration of carbon dioxide (CO2) combined with the reduction in soil-water availability is complex due to the various (bio)chemical feedbacks. Modern analytical tools and the experimental advance of agronomic science tend to advance in the understanding of the metabolic complexity of plants. In this work, Coffea arabica trees were grown in a Free-Air Carbon Dioxide Enrichment dispositive under factorial design (22) conditions considering two CO2 levels and two soil-water availabilities. The 1H NMR mixture design-fingerprinting effects of CO2 and soil-water levels on beans were strategically investigated using the principal component analysis (PCA), analysis of variance (ANOVA) - simultaneous component analysis (ASCA) and partial least squares-discriminant analysis (PLS-DA). From the ASCA, the CO2 factor had a significant effect on changing the 1H NMR profile of fingerprints. The soil-water factor and interaction (CO2 × soil-water) were not significant. 1H NMR fingerprints with PCA, ASCA and PLS-DA analysis determined spectral profiles for fatty acids, caffeine, trigonelline and glucose increases in beans from current CO2, while quinic acid/chlorogenic acids, malic acid and kahweol/cafestol increased in coffee beans from elevated CO2. PLS-DA results revealed a good classification performance between the significant effect of the atmospheric CO2 levels on the fingerprints, regardless of the soil-water availabilities. Finally, the PLS-DA model showed good prediction ability, successfully classifying validation data-set of coffee beans collected over the vertical profile of the plants and included several fingerprints of different extracting solvents. The results of this investigation suggest that the association of experimental design, mixture design, PCA, ASCA and PLS-DA can provide accurate information on a series of metabolic changes provoked by climate changes in products of commercial importance, in addition to minimizing the extra work necessary in classic analytical approaches, encouraging the development of similar strategies.

Potential biomonitoring of atmospheric carbon dioxide in Coffea arabica leaves using near-infrared spectroscopy and partial least squares discriminant analysis.

The potencial of Coffea arabica leaves as bioindicators of atmospheric carbon dioxide (CO2) was evaluated in a free-air carbon dioxide enrichment (FACE) experiment by using near-infrared reflectance (NIR) spectroscopy for direct analysis and partial least squares discriminant analysis (PLS-DA). A supervised classification model was built and validated from the spectra of coffee leaves grown under elevated and current CO2 levels. PLS-DA allowed correct test set classification of 92% of the elevated-CO2 level leaves and 100% of the current-CO2 level leaves. The spectral bands accounting for the discrimination of the elevated-CO2 leaves were at 1657 and 1698 nm, as indicated by the variable importance in the projection (VIP) score together with the regression coefficients. Seven months after suspension of enriched CO2, returning to current-CO2 levels, new spectral measurements were made and subjected to PLS-DA analysis. The predictive model correctly classified all leaves as grown under current-CO2 levels. The fingerprints suggest that after suspension of elevated-CO2, the spectral changes observed previously disappeared. The recovery could be triggered by two reasons: the relief of the stress stimulus or the perception of a return of favorable conditions. In addition, the results demonstrate that NIR spectroscopy can provide a rapid, nondestructive, and environmentally friendly method for biomonitoring leaves suffering environmental modification. Finally, C. arabica leaves associated with NIR and mathematical models have the potential to become a good biomonitoring system.

PARAFAC HPLC-DAD metabolomic fingerprint investigation of reference and crossed coffees.

In this study two cultivars of Coffea arabica L., Bourbon (reference) and IPR101 (crossing) were analyzed. The extracts were prepared according to a simplex centroid design with four components, ethanol, ethyl acetate, dichloromethane, and hexane. Multiway data were obtained by HPLC-DAD analysis of the fifteen different mixtures for each cultivar. The PARAFAC methodology was used to investigate the chromatographic fingerprint. For both cultivars, Factor 1 was able to discriminate mixtures containing ethyl acetate as solvent. Factor 2 indicated that mixtures in pure ethanol and binary mixtures containing ethanol were the most efficient in extracting chlorogenic acids and factor 3 identified methylxanthines through spectrophotometric profile in all mixtures. Higher concentrations were obtained by the ethanol, dichloromethane and hexane ternary mixture for the Bourbon cultivar and by the quaternary mixture of these solvents with ethyl acetate for the IPR101 cultivar. Trigonelline and cafestol were extracted in both cultivars. The reference coffee showed higher relative abundances of cafestol ester, chlorogenic acids and trigonelline whereas the crossed coffee showed higher levels of caffeine. To confirm these results, UPLC-MS was used as a complementary method to confirm the presence of the metabolites in these extracts. The three way PARAFAC strategy determines correlations of HPLC-DAD chromatographic and spectral data simultaneously with samples permitting a more unambiguous assignment of metabolic groups than can be obtained treating chromatographic and spectral data separately by two way methods. This can provide higher quality chromatographic fingerprints for food chemistry.

Otimização dos parâmetros operacionais de eletrocoagulação aplicada à recuperação de efluentes de lavagem de veículos / Optimization of electrocoagulation operating parameters applied to the recovery vehicle washing wastewater

RESUMO No Brasil, cerca de 32.700 postos de lavagem de veículos consomem 3,7 milhões de m3/mês-1, média de 60 L por veículo. Esse consumo poderia ser minimizado, se o efluente fosse devidamente tratado e reutilizado. Como diversos tipos de efluentes têm sido eficientemente tratados por técnicas eletroquímicas, como a eletrocoagulação (EC) e a eletroflotação (EF), o objetivo principal deste estudo foi desenvolver um sistema de tratamento de efluentes de lavagem de carros por EC, usando eletrodos de alumínio. Parâmetros como pH inicial, corrente elétrica aplicada e tempo de eletrólise foram otimizados por meio de análises físico-químicas e estatísticas. Em sua condição ótima, pH 5, corrente elétrica de 3,5 A e tempo de 20 minutos, o sistema conseguiu reduzir em 73% a demanda química de oxigênio (DQO), 58% de surfactantes e no mínimo 90% a turbidez e os sólidos suspensos totais (SST). Além da simples implantação e operação, a técnica mostrou-se eficiente na recuperação desse tipo de efluente, podendo ser utilizada em sistemas de reúso de água de lavagem de veículos.

ABSTRACT In Brazil, about 32,700 vehicle washing stations consume 3,7 million m3 per month-1, average of 60 L per vehicle. Consumption could be minimized if the effluent was properly treated and reused. As different types of effluents have been effectively treated by electrochemical techniques, such as electrocoagulation (EC) and electrocoagulation (EF), the main objective of this study was to develop a treatment system of carwash wastewater, by EC using electrodes aluminum. Parameters like the initial pH, applied electric current and electrolysis time were optimized by means of physical-chemical analysis and statistics. In its optimum condition, pH 5, electrical current of 3,5 A and time of 20 minutes, the system has managed to reduce by 73% the chemical oxygen demand (COD), 58% of surfactants and a minimum of 90% turbidity and total suspended solids (TSS). Besides the simple installation and operation, the technique was efficient in the recovery of this type of effluent and can be used in reuse system carwash water.

Development and characterization of multiple emulsions for controlled release of Trichilia catigua (Catuaba) extract.

Considering the antioxidant activity of the Trichilia catigua extract (TCE), the aim of the current study was to develop and characterize W/O/W multiple emulsions containing different vegetable oils as a platform to deliver a TCE. The extract displayed antioxidant activity (IC50) of 4.59 µg/mL and total phenol content (TPC) of 50.84%. Formulations were prepared by the phase-inversion emulsification method and analyzed for morphological appearance, pH, conductivity, droplet size and distribution, content of active, rheological properties, in vitro release, skin permeation, and stability. Formulations prepared with canola oil were selected and displayed regular morphology, mean diameter 2.77 µm (without TCE), 3.07 µm with 0.5% and 3.23 µm with 1.0% TCE. Rheometry (flow) showed pseudoplastic behavior with minimal thixotropy for both systems. TCE could be released from emulsions containing 1.0% and 0.5% TCE in a controlled manner for 16 and 23 h, respectively. The emulsions allowed good retention of TCE in the skin (stratum corneum, epidermis, and dermis). In a 180-d assessment of accelerated chemical stability, TPC was more reduced for the emulsions at 40 °C; other parameters remained stable. Multiple emulsions containing TCE were developed, exhibited good characteristics, and may be considered for future investigations as anti-aging formulations for the skin.

Experimental designs characterizing seasonal variations and solvent effects on the quantities of coumarin and related metabolites from Mikania laevigata.

Statistical design mixtures of acetone, chloroform, dichloromethane and ethanol were used to study the effects of different solvents and their mixtures on the quantities of coumarin and related metabolites extracted from Mikania laevigata samples harvested in each of the four seasons. RP-HPLC-DAD and both positive and negative modes of UPLC-MS analyses were used to determine relative quantities of coumarin, o-coumaric acid and melilotic acids in each season for all the mixture design extracts. The existence and measurement of the relative abundances of melilotic acid in Mikania laevigata have not been reported previously. Highest coumarin concentrations were encountered in the summer whereas its o-coumaric acid precursor and melilotic acid were most abundant in the spring. O-coumaric and melilotic acids concentrations were strongly correlated during the year. Also solvent effects were seen to be significant. Ethanol and 1:1 binary mixtures of ethanol and acetone extracted the largest quantities of coumarin whereas ethanolic binary and ternary mixtures with chloroform and dichloromethane provided the best yields of o-coumaric and melilotic acids. Statistical mixture models indicated that synergic binary interactions, especially those involving ethanol with acetone or chloroform, are important in the Mikania extraction process.

Chemometric discrimination of genetically modified Coffea arabica cultivars using spectroscopic and chromatographic fingerprints.

Multivariate statistical design and principal component analysis (PCA) applied to RP-HPLC-DAD and FTIR spectroscopic data were performed to investigate the fingerprints of four coffee cultivars, traditional red bourbon and three genetically modified cultivars. The design and response surface results showed that extraction dependence on solvent composition of one of the genetically modified cultivars, IAPAR 59, was very similar to that found for the red bourbon standard. PCA of the FTIR spectra obtained from all the simplex centroid design mixtures indicated that the 1:1 binary ethanol-dichloromethane solution resulted in the best separation of the four cultivars. The IPR 108 cultivar has more intense vibrational bands in the 3200-3,600 cm(-1) and 1100-1,600 cm(-1) regions indicating higher acid and fat levels than those of the other cultivars. The UV absorptions close to 275 nm of the RP-HPLC-DAD spectra are correlated with the strengths of the infrared absorptions between 3400 and 3,460 cm(-1) and can be explained by varying caffeine concentrations in the four cultivars.

Principal component and Tucker3 analyses of high performance liquid chromatography with diode-array detection fingerprints of crude extracts of Erythrina speciosa Andrews leaves.

Mixtures of ethanol, dichloromethane, hexane and acetone obtained according to a statistical design have been used to extract substances from Erythrina speciosa Andrew leaves for chromatographic fingerprinting. The plant extracts from each mixture were analyzed by HPLC-DAD providing UV-vis spectra for each chromatographic peak. These chromatograms and spectra for the design mixtures were then treated with principal component (PCA), Tucker3 and PARAFAC analyses. PCA indicated the existence of five different chromatographic fingerprints for the leave extracts depending on the solvent mixture composition. Different chromatographic peak areas were strongly correlated with the mixture proportions of acetone, dichloromethane and ethanol. Tucker3 and PARAFAC analyses were very useful for identifying simultaneous correlations between chromatographic peak areas, spectral band absorbances and solvent proportions. The acetone proportion was highly correlated with the area of the 3.69 min retention time peak and the spectral absorbances between 250 and 260 nm, consistent with the presence of natural polyphenols. The dichloromethane mixture proportion was strongly correlated with the 12.19 min chromatographic peak area and a single spectral absorbance at 201 nm. This spectral absorption is characteristic of the electronic structures of terpenes and alkaloids.

Statistical mixture design selective extraction of compounds with antioxidant activity and total polyphenol content from Trichilia catigua.

Statistical design mixtures of water, methanol, acetone and ethanol were used to extract material from Trichilia catigua (Meliaceae) barks to study the effects of different solvents and their mixtures on its yield, total polyphenol content and antioxidant activity. The experimental results and their response surface models showed that quaternary mixtures with approximately equal proportions of all four solvents provided the highest yields, total polyphenol contents and antioxidant activities of the crude extracts followed by ternary design mixtures. Principal component and hierarchical clustering analysis of the HPLC-DAD spectra of the chromatographic peaks of 1:1:1:1 water-methanol-acetone-ethanol mixture extracts indicate the presence of cinchonains, gallic acid derivatives, natural polyphenols, flavanoids, catechins, and epicatechins.

pKa determinations of xanthene derivates in aqueous solutions by multivariate analysis applied to UV-Vis spectrophotometric data.

Xanthenes form to an important class of dyes which are widely used. Most of them present three acid-base groups: two phenolic sites and one carboxylic site. Therefore, the pKa determination and the attribution of each group to the corresponding pKa value is a very important feature. Attempts to obtain reliable pKa through the potentiometry titration and the electronic absorption spectrophotometry using the first and second orders derivative failed. Due to the close pKa values allied to strong UV-Vis spectral overlap, multivariate analysis, a powerful chemometric method, is applied in this work. The determination was performed for eosin Y, erythrosin B, and bengal rose B, and also for other synthesized derivatives such as 2-(3,6-dihydroxy-9-acridinyl) benzoic acid, 2,4,5,7-tetranitrofluorescein, eosin methyl ester, and erythrosin methyl ester in water. These last two compounds (esters) permitted to attribute the pKa of the phenolic group, which is not easily recognizable for some investigated dyes. Besides the pKa determination, the chemometry allowed for estimating the electronic spectrum of some prevalent protolytic species and the substituents effects evaluation.

Enhanced extraction yields and mobile phase separations by solvent mixtures for the analysis of metabolites in Annona muricata L. leaves.

The effects of five extraction solvents and their mixtures on the yield of metabolites in crude and fractionated extracts of Annona muricata L. leaves were investigated by direct comparison. Extraction media were prepared using simplex centroid mixtures of ethanol, ethyl acetate, dichloromethane, acetone, and chloroform. The effects of the mobile phase solvent strength and the analysis wavelength on the chromatographic separation were also investigated. Solvent mixtures rather than pure solvents were found to be the most efficient extractors for the different fractions. The results indicated that the mobile phase composed of methanol/acetonitrile/water (26:27:47 v/v/v) was most suitable for the basic fraction analysis at 254 nm, whereas the mobile phase composed of methanol/acetonitrile/water (35:35:30 v/v/v) was the most adequate for the organic fraction analysis at 254 nm. The results indicated that the chromatographic profiles and number of peaks were affected by the mobile phase strength and analysis wavelength.

Chemometric evaluation of adulteration profile in coffee due to corn and husk by determining carbohydrates using HPAEC-PAD.

The detection of impurities in coffee samples already roasted and ground is a constant concern mainly in order to verify the incidence of frauds. Carbohydrates contents are important as variations on original constitutes of different matrixes may be able to reveal the final composition of the product. In this sense, a study is performed in this paper in order to evaluate the quality through concentration of total carbohydrates in Arabic roasted and ground coffee. Chemometric methods were applied in order to verify an adulteration pattern by coffee husk and corn, by the mixture of different amounts of these contaminants to coffee, following a statistical design of Simplex-Centroid. It could be concluded that this method was efficient in distinguishing different matrixes. In pure coffee, higher concentrations were found for galactose and mannose with levels of 8.25% and 9.65% (w/w), respectively. However, in the pure husks, the main carbohydrates were mannitol (with a level of 0.64%), arabinose (with 4.24%), and xylose (with 3.40%). For the corn sample, glucose was detected in greater quantity, with 52.53% (w/w). Models presenting the influence of adulterants incorporated to coffee in the carbohydrate level were obtained.

Statistical mixture design investigation of fractionated and total extracts from Erythrina speciosa Andrews leaves.

The simplex centroid mixture design for the ethanol, dichloromethane, hexane and acetone solvents has been applied to the extraction of crude mass and the fiber, organic, neutral and basic fractions as well as the fractionation residues of Erythrina speciosa Andrews leaves. Binary and ternary synergic solvent interactions are seen to provide dominant contributions to the extraction of both crude mass and all the fractions. Quadratic and special cubic mixture models precisely predict the extracted quantities of each fraction and the residue as a function of the proportions of the four solvents. Different solvent mixtures are found to be the most efficient extractors for the different fractions: binary dichloromethane-hexane mixtures for the fiber fraction, ternary ethanol-dichloromethane-acetone mixtures for the neutral fraction, binary ethanol-dichloromethane mixtures for the organic fraction, crude extract and residue values and ternary ethanol-dichloromethane-hexane mixtures for the basic fraction. Principal component analysis shows that the ethanol-dichloromethane mixtures are important for extracting large quantities of the basic and organic fractions as well as of the residue and crude masses.

Mixture design optimization of extraction and mobile phase media for fingerprint analysis of Bauhinia variegata L.

Two statistical mixture designs were used to optimize the proportions of solvents used in both the extraction medium and the reversed liquid chromatographic mobile phase to improve the quality of chromatographic fingerprints of Bauhinia variegata L extracts. For modeling, the number of peaks was used as a measure of fingerprint information. Three mobile phases, each with a chromatographic strength of two, gave good results. A methanol/water (77:23 v/v) mixture resulted in 17 peaks in the chromatographic fingerprint whereas acetonitrile/water (64.5:35.5 v/v) and methanol/acetonitrile/water (35:35:30 v/v/v) mixtures resulted in 18 and 20 peaks, respectively. The corresponding optimum solvent compositions to extract chemical substances for these three mobile phases were ethanol/acetone (25:75 v/v/v) and dichloromethane/acetone (70:30 v/v) mixtures, and pure dichloromethane, respectively. The mixture designs are useful for understanding the influence of different solvents on the strengths of the extraction medium and the mobile phase.

Multivariate chromatographic fingerprint preparation and authentication of plant material from the genus Bauhinia.

Multivariate analysis and statistical mixture designs were used for chromatographic fingerprint preparation and authentication of the plant material of three species of the genus Bauhinia. The extracts were analysed by reversed-phase high-performance liquid chromatography. Mixture design gave an optimum solvent composition for extracting components from the plants of 36% dichloromethane, 17% ethanol and 47% ethyl acetate (by volume), while an optimum mobile phase for chromatographic analyses was found to be 27% methanol, 27% acetonitrile and 46% of water (by volume). Results from principal component analysis, hierarchical analysis and soft independent modelling by class analogy showed that Bauhinia candicans cannot be synonymous with B. forficata Link. It was also possible to trace the metabolic profile without identifying its chemical constituents and to determine a chromatographic discriminating region. The characteristics responsible for discrimination between B. candicans and B. forficata were more polar substances that presented peaks with retention times around 1.65 and 1.81 min.

Statistical mixture design--principal component optimization for selective compound extraction from plant material.

A simplex centroid design is used to optimize solvent mixtures for selective extraction of compounds from Erythrina speciosa Andrews leaves. Three main groups of compounds characterized by chromatographic retention times of 1.7, 3.1, and 6.6 min were extracted. The chromatographic peak heights registered at 1407 equally spaced times for each design extract were converted into principal components (PCs). Three PCs account for 89.1% of the data variance and have important loading values at the above retention times. Quadratic mixture models were found to adequately describe the response surfaces of their PC score values. Maximizing the first PC scores while minimizing the second and third ones results in an optimum 83% dichloromethane-17% acetone mixture that selectively extracts the group of compounds with retention times around 3.1 min. Maximizing the second PC scores and minimizing the third PC scores leads to a 78% hexane-22% acetone mixture adequate for extracting the 6.6 min retention time compounds as well as other compounds with high retention times. The 1.7 min group of compounds is most efficiently extracted on maximizing the third PC that results in a 50% ethanol-50% acetone mixture. The Derringer-Suich algorithm confirmed the determination of these optimized mixtures.