An updated procedure for zeaxanthin and lutein quantification in corn grains based only in water and ethanol.

Corn grains are a major source of both the bioactive carotenoids zeaxanthin and lutein. Current methods to quantify these substances have some disadvantages related to sustainability and sample throughput. This work aimed to develop a green, efficient, rapid, and reproducible analytical method to quantify these xanthophylls in corn grains. Solvents recommended by the CHEM21 solvent selection guide were screened. The extraction by dynamic maceration and separation by ultra-high-performance liquid chromatography were optimized by design of experiments. Then, the entire analytical procedure was validated and compared with procedures used for the same purpose, including an official one, and applied to different corn samples. The proposed method was demonstrated to be greener, equal to or more efficient, faster, and more reproducible than the comparative methods. The extraction step could be scaled up for industrial production of zeaxanthin- and lutein-enriched extracts, as it uses only compatible food grade ethanol and water.

Unveiling meloxicam monohydrate process of dehydration by an at-line vibrational multi-spectroscopy approach.

Meloxicam (MLX) is a non-steroidal anti-inflammatory drug, extensively used for inflammatory diseases and pain treatments, which exhibits five known solids forms. Form IV of MLX, a zwitterionic monohydrate (MH), is an emblematic hydrate case with promissory dissolution properties in a poorly soluble drug. However, the lack of information about MH stability regarding the dehydration process and phase transition impedes the development of further stability studies. A multi-spectroscopic/chemometric approach was implemented coupling middle- (MIR), near-infrared (NIR) and Raman spectroscopies to monitor the heat-mediated dehydration process of MH. The application of multivariate curve resolution-alternating least squares (MCR-ALS) to multi-source spectra by data fusion allow a complete view of the phenomena, improving the selectivity and precision to establish the transition temperatures and to identify involved species. It was revealed a two-step mechanism, where MH changes to Form V at 90 °C obtaining its complete dehydration at 130 °C, Form V remains unchanged during the temperature range 130-190 °C and then the polymorphic conversion to Form I starts, which reaches 100 % at 230 °C before melting MLX (248 °C). The findings of this work allow set targets in the process control of products using MH. Additionally, MCR-ALS detected an event not evidenced by conventional thermal analysis, the transformation of Form V to Form I.

A green and sustainable method for monitoring the chemical composition of soybean: an alternative for quality control.

INTRODUCTION: Soybean is one of the most important crops in the world, an important source of isoflavones, and used to treat various chronic diseases. High-performance liquid chromatography (HPLC), associated with multivariate experiments and green solvents, is increasingly used to develop comprehensive elution methods for quality control of plants and derivatives. OBJECTIVE: The work aims to establish a HPLC fingerprinting method for soybean seeds employing Green Chemistry Principles, a sustainable solvent with low toxicity, and a comprehensive experimental design that reduces the number of experiments. MATERIALS AND METHODS: The fingerprinting method was optimised through Design of Experiments by evaluating seven chromatographic variables: initial percentage of ethanol (X1), final percentage of ethanol (X2), temperature (X3), percentage of acetic acid in water (X4), flow rate (X5), run time (X6), and stationary phase (X7). The dependent variable was the number of peaks (n). RESULTS: An initial factorial design for screening purposes indicated that the most significant quantitative parameters to separate soybean metabolites were X1 and X3. The conditions were optimised by a Doehlert design, to obtain a HPLC-PAD (photodiode array detector) fingerprinting of the polar extract of soybean seeds with the markers identified by liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS). The optimum fingerprinting method was determined as 5-55% of ethanol in 30 min, at 35°C, and flow rate of 1 mL/min, by employing a phenyl-hexyl column (150 mm × 4.6 mm). CONCLUSION: The developed green method enabled markers of soybean to be separated and identified and could be an eco-friendlier alternative for soybean quality control that covered seven Green Analytical Chemistry Principles.

In-line monitoring of cocrystallization process and quantification of carbamazepine-nicotinamide cocrystal using Raman spectroscopy and chemometric tools.

A cocrystallization process may involve several molecular species, which are generally solid under ambient conditions. Thus, accurate monitoring of different components that might appear during the reaction is necessary, as well as quantification of the final product. This work reports for the first time the synthesis of carbamazepine-nicotinamide cocrystal in aqueous media with a full conversion. The reactions were monitored by Raman spectroscopy coupled with Multivariate Curve Resolution - Alternating Least Squares, and the quantification of the final product among its coformers was performed using Raman spectroscopy and Partial Least Squares regression. The slurry reaction was made in four different conditions: room temperature, 40°C, 60°C and 80°C. The slurry reaction at 80°C enabled a full conversion of initial substrates into the cocrystal form, using water as solvent for a greener method. The employment of MCR-ALS coupled with Raman spectroscopy enabled to observe the main steps of the reactions, such as drug dissolution, nucleation and crystallization of the cocrystal. The PLS models gave mean errors of cross validation around 2.0 (% wt/wt), and errors of validation between 2.5 and 8.2 (% wt/wt) for all components. These were good results since the spectra of cocrystals and the physical mixture of the coformers present some similar peaks.

Laser-induced breakdown spectroscopy (LIBS) combined with hyperspectral imaging for the evaluation of printed circuit board composition.

In this study, laser-induced breakdown spectroscopy (LIBS) was combined with chemometric strategies (PCA, Principal Component Analysis) and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) to investigate the metal composition of a printed circuit board (PCB) sample from a mobile phone. Scanning electron microscopy-EDS was used for two main reasons: it was possible at the same time to visualize the sample surface, craters (made by the laser pulses) and also the chemical composition of the samples. A 30 mm×40 mm area of the mobile phone PCB sample, which was manufactured in 2011, was investigated. In this case, a matrix with 30 rows and 40 columns (1200 points) was analyzed, and 10 pulses were performed at each point. A total of 12,000 emission spectra were recorded in the wavelength range from 186 to 1040 nm. After an initial exploratory investigation using PCA, 18 emission lines were selected (representing the elements Al, Au, Ba, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Sb, Si, Sn, Ti and Zn) and then normalized by the relative intensities, and a new PCA was calculated with the autoscaled data. For example, Au and Si were mainly observed in the superficial electrical contacts and in the bulk of the PCB, respectively. A second sample (a mouse PCB) was also analyzed and Pb (emission lines 357.273, 363.956, 368.346, 373.994 and 405.780 nm) was identified in the solders. In addition, this element was determined using FAAS (flame atomic absorption spectrometry) and the Pb concentration was around 25% (w/w). This study opens the possibility for improved recycling processes and the chemical investigation of solid samples measuring a few millimeters in dimension without sample preparation.

Tracking the degradation of fresh orange juice and discrimination of orange varieties: an example of NMR in coordination with chemometrics analyses.

Brazil is currently the largest exporter of concentrated orange juice and, unlike the other exporter countries, the domestic consumption is mainly based on the fresh orange juice. The quality control by evaluating the major chemical constituents under the influence of the most important factors, such as temperature and storage time of the product, is very important in this context. Therefore, the objective of this study was to evaluate the influence of temperature and time on the degradation of fresh orange juice for 24h, by using (1)H NMR technique and chemometric tools for data mining. The storage conditions at 24h led to the production of the formic, fumaric and acetic acids; and an increase of succinic and lactic acids and ethanol, which were observed at low concentration at the initial time. Furthermore, analysis by PCA has successfully distinguished the juice of different species/varieties as well as the metabolites responsible for their separation.

A trade off between separation, detection and sustainability in liquid chromatographic fingerprinting.

It is now recognized that analytical chemistry must also be a target for green principles, in particular chromatographic methods which typically use relatively large volumes of hazardous organic solvents. More generally, high performance liquid chromatography (HPLC) is employed routinely for quality control of complex mixtures in various industries. Acetonitrile and methanol are the most commonly used organic solvents in HPLC, but they generate an impact on the environment and can have a negative effect on the health of analysts. Ethanol offers an exciting alternative as a less toxic, biodegradable solvent for HPLC. In this work we demonstrate that replacement of acetonitrile with ethanol as the organic modifier for HPLC can be achieved without significantly compromising analytical performance. This general approach is demonstrated through the specific example analysis of a complex plant extract. A benchmark method employing acetonitrile for the analysis of Bidens pilosa extract was statistically optimized using the Green Chromatographic Fingerprinting Response (GCFR) which includes factors relating to separation performance and environmental parameters. Methods employing ethanol at 30 and 80°C were developed and compared with the reference method regarding their performance of separation (GCFR) as well as by a new metric, Comprehensive Metric to Compare Liquid Chromatography Methods (CM). The fingerprint with ethanol at 80°C was similar to or better than that with MeCN according to GCFR and CM. This demonstrates that temperature may be used to replace harmful solvents with greener ones in HPLC, including for solvents with significantly different physiochemical properties and without loss in separation performance. This work offers a general approach for the chromatographic analysis of complex samples without compromising green analytical chemistry principles.

Application of the response surface and desirability design to the Lambda-cyhalothrin degradation using photo-Fenton reaction.

Lambda-cyhalothrin is a potent pyrethroid insecticide used widely in pest management. Detectable levels of the pyrethroid in agricultural watersheds are potentially toxic to aquatic organisms. There is little information in the scientific literature about degradation in aqueous media of the Lambda-cyhalothrin by Advanced Oxidative Process. A mathematical approach for the degradation of this compound has not yet been fully explored… The Central composite design (CCD) and response surface method (RSM) were applied to evaluate and optimize the interactive effects of two operating variables. The initial dosages of H2O2 and Fe(2+) on photo-Fenton degradation of an aqueous solution of Lambda-cyhalothrin in a recirculation flow-through UV photoreactor were used. The remaining concentration of Lambda-cyhalothrin (y1) and the percentage removal of total organic carbon (y2) were the monitored factors since they are dependent parameters of y1 and y2. According to analysis of variances (ANOVA) results, two proposed models can be used to navigate the design space with regression coefficient R(2) - 0.834 and 0.843 for y1 and y2, respectively. A multi-response optimization procedure, based on the global desirability of the factors, was performed to establish the best concentrations of hydrogen peroxide and ferrous sulfate that would allow the most efficient degradation of Lambda-cyhalothrin concomitant with a maximal removal of total organic carbon. The global desirability surface revealed that 0.295 mmol L(-1) of ferrous sulfate and 3.85 mmol L(-1) of hydrogen peroxide were close to the optimum conditions to satisfy both factors simultaneously using minimal amounts of reagents. These photo-Fenton conditions promoted 100% of Lambda-cyhalothrin degradation and 79.83% TOC removal (mineralization) in 120 min of reaction time.

Multivariate curve resolution of pH gradient flow injection mixture analysis with correction of the Schlieren effect.

Multivariate curve resolution using alternating least squares (MCR-ALS) was used to quantify ascorbic (AA) and acetylsalicylic (ASA) acids in four pharmaceutical samples using a flow injection analysis (FIA) system with pH gradient and a diode array (DAD) spectrometer as a detector. Four different pharmaceutical drugs were analyzed, giving a data array of dimensions 51 x 291 x 61, corresponding respectively to number of samples, FIA times and spectral wavelengths. MCR-ALS was applied to these large data sets using different constraints to have optimal resolution and optimal quantitative estimations of the two analytes (AA and ASA). Since both analytes give an acid-basic pair of species contributing to the UV recorded signal, at least four components sholuld be proposed to model AA and ASA in synthetic mixture samples. Moreover, one additional component was needed to resolve accurately the Schlieren effect and another additional component was also needed to model the presence of possible interferences (like caffeine) in the commercial drugs tablets, giving therefore a total number of 6 independent components needed. The best quantification relative errors were around 2% compared to the reference values obtained by HPLC and by the oxidation-reduction titrimetric method, for ASA and AA respectively. In this work, the application of MCR-ALS allowed for the first time the full resolution of the FIA diffusion profile due to the Schlieren effect as an independent signal contribution, suggesting that the proposed MCR-ALS method allows for its accurate correction in FIA-DAD systems.

Application of genetic algorithm for selection of variables for the BLLS method applied to determination of pesticides and metabolites in wine.

A variable selection methodology based on genetic algorithm (GA) was applied in a bilinear least squares model (BLLS) with second-order advantage, in three distinct situations, for determination by HPLC-DAD of the pesticides carbaryl (CBL), methyl thiophanate (TIO), simazin (SIM) and dimethoate (DMT) and the metabolite phthalimide (PTA) in wine. The chromatographic separation was carried out using an isocratic elution with 50:50 (v/v) acetonitrile:water as mobile phase. Preprocessing methods were performed for correcting the chromatographic time shifts, baseline variation and background. The optimization by GA provided a significant reduction of the errors, where for SIM and PTA a decrease of three times the value obtained using all variables, and an improvement in the distribution of them, reducing the observed bias in the results were observed. Comparing the RMSEP of the optimized model with the uncertainty estimates of the reference values it is observed that GA can be a very useful tool in second-order models.