Flow injection colorimetric method using acidic ceric nitrate as reagent for determination of ethanol

Ceric ammonium nitrate has been used for qualitative analysis of ethanol. It forms an intensely colored unstable complex with alcohol. In this work, a simple flow injection (FI) colorimetric method was developed for the determination of ethanol, based on the reaction of ethanol with ceric ion in acidic medium to produce a red colored product having maximum absorption at 415 nm. Absorbance of this complex could be precisely measured in the FI system. A standard or sample solution was injected into a deionized water donor stream and flowed to a gas diffusion unit, where the ethanol diffused through a gas permeable membrane made of plumbing PTFE tape into an acceptor stream to react with ceric ammonium nitrate in nitric acid. Color intensity of the reddish product was monitored by a laboratory made LED based colorimeter and the signal was recorded on a computer as a peak. Peak height obtained was linearly proportional to the concentration of ethanol originally presented in the injected solution in the range of 0.1-10.0% (v/v) (r² = 0.9993), with detection limit of 0.03% (v/v). With the use of gas diffusion membrane, most of the interferences could be eliminated. The proposed method was successfully applied for determination of ethanol in some alcoholic beverages, validating by gas chromatographic method.     

Investigation into the structural composition of hydroalcoholic solutions as basis for the development of multiple suppression pulse sequences for NMR measurement of alcoholic beverages

An eight‐fold suppression pulse sequence was recently developed to improve sensitivity in ¹H NMR measurements of alcoholic beverages [Magn. Res. Chem. 2011 (49): 734–739]. To ensure that only one combined hydroxyl peak from water and ethanol appears in the spectrum, adjustment to a certain range of ethanol concentrations was required. To explain this observation, the structure of water–ethanol solutions was studied. Hydroalcoholic solutions showed extreme behavior at 25% vol, 46% vol, and 83% vol ethanol according to ¹H NMR experiments. Near‐infrared spectroscopy confirmed the occurrence of four significant compounds (‘individual’ ethanol and water structures as well as two water–ethanol complexes of defined composition – 1 : 1 and 1 : 3). The successful multiple suppression can be achieved for every kind of alcoholic beverage with different alcoholic strengths, when the final ethanol concentration is adjusted to a range between 25% vol and 46% vol (e.g. using dilution or pure ethanol addition). In this optimum region, an individual ethanol peak was not detected, because the ‘individual’ water structure and the 1 : 1 ethanol–water complex predominate. The nature of molecular association in ethanol–water solutions is essential to elucidate NMR method development for measurement of alcoholic beverages. The presented approach can be used to optimize other NMR suppression protocols for binary water–organic solvent mixtures, where hydrogen bonding plays a dominant role. Copyright © 2014 John Wiley & Sons, Ltd.     

Determination of ethanol in fuel ethanol and beverages by Fourier transform (FT)-near infrared and FT-Raman spectrometries

Fourier transform-near infrared (FT-NIR) and FT-Raman spectrometries have been used to design partial least squares (PLS) calibration models for the determination of the ethanol content of ethanol fuel and alcoholic beverages. In the FT-NIR measurements the spectra were obtained using air as reference, and the spectral region for PLS modeling were selected based on the spectral distribution of the relative standard deviation in concentration. In the FT-Raman measurements hexachloro-1,3-butadiene (HCBD) has been used as an external standard. In the PLS/FT-NIR modeling for ethanol fuel analysis 50 ethanol fuel standards (84.9-100% (w/w)) were used (25 in the calibration, 25 in the validation). In the PLS/FT-Raman modeling 25 standards were used (13 in the calibration, 12 in the validation). The PLS/FT-NIR and FT-Raman models for beverage analysis made use of 24 standards (0-100% (v/v)). Twelve of them contained sugars (1-5% (w/w)), one-half was used in the calibration and the other half in the validation. Different spectral pre-processing were used in the PLS modeling, depending on the type of sample investigated. In the ethanol fuel analysis the FT-NIR pre-processing was a 17 points smoothed first derivative and for beverages no spectral pre-processing was used. The FT-Raman spectra were pre-processed by vector normalization in the ethanol fuel analysis and by a second derivative (17 points smoothing) in the beverage analysis. The PLS models were used in the analysis of real ethanol fuel and beverage samples. A t-test has shown that the FT-NIR model has an accuracy equivalent to that of the reference method (ASTM D4052) in the analysis of ethanol fuel, while in the analysis of beverages, the FT-Raman model presents an accuracy equivalent to the reference method. The limits of detection for NIR and Raman calibration models were 0.05 and 0.2% (w/w), respectively. It has also been shown that both techniques, present better results than gas chromatography (GC) in evaluating the ethanol content of beverages.     

Screening of adulteration in packaging biocomposites by infrared spectroscopy and chemometrics

Fourier transform infrared spectroscopy coupled with chemometrics was employed to detect packaging polylactic acid-based biocomposite samples adulterated with polypropylene (PP) 30–45% and linear low-density polyethylene 2–10%. Principal component analysis, soft independent modeling of class analogy (SIMCA) and partial least square discriminate analysis (PLS-DA) chemometric techniques were utilized to classify samples in different classes. Totally, 362 samples were modeled in three different classes (two adulterated and one non-adulterated). The obtained results revealed that PLS-DA is the most suitable chemometric approach for prediction of probable adulteration in biocomposite samples with reliable specificity and selectivity. It could provide 99% correct class prediction rate between non-adulterated biocomposite samples and adulterated ones, while SIMCA methods provided 73.33% prediction accuracy in classification.     

Use of a copper electrode in alkaline medium as an amperometric sensor for sulphite in a flow-through configuration

A flow injection analysis (FIA) method has been developed for the determination of sulphite in beverages. The method is based on the amperometric detection (0.60 V vs Ag/AgCl (sat. NaCl)) of the analyte at a copper surface in an alkaline medium (1 M NaOH solution) with a manifold that incorporates flow extraction of sulphite as SO2 through a PTFE membrane. Under optimal experimental conditions the peak current response increases linearly with sulphite concentration over the range from 1.0 to 5.0 mM. The repeatability of the electrode response in the FIA configuration was evaluated as 4% ( n =20), the limit of detection of the method was 0.04 mM (S/N =3) and the analytical frequency was 50 h(-1). Since ethanol is also electroactive and permeates through the PTFE membrane, a strategy involving in a first step measurements of only ethanol by manipulating the pH of the donor stream was employed for wine samples. Then, both ethanol and sulphite were measured at the copper electrode at 0.40 V vs Ag/AgCl (sat. NaCl) and the sulphite concentration was determined by difference. Results for 3 different beverage samples (alcoholic and non-alcoholic) showed excellent agreement with the ones obtained by using a recommended procedure for sulphite analysis.     

Determination of glycol in aircraft ground deicing/anti-icing fluids using flow injection with refractive index detection

A simple method for determining glycol in deicing/anti-icing fluids has been developed. The method uses a single line FIA system with detection based on Schlieren optics. The concentration range was 0-5% glycol and the limit of detection was 0.05%. Samples were preferably pumped at a flow rate of 0.7 ml/min and 100 mul of distilled water was injected (reverse FIA). Detection was accomplished with an 18 mul spectrophotometric flow cell at a wavelength of 410 nm. The conduit connecting the injector and the detector was 10 cm long and had an inner diameter of 0.5 mm. The traditional FIA approach can also be applied, i.e. injection of samples into a carrier of water, but the linear working range is narrower in comparison to the reverse FIA method. Standard addition and near infrared spectroscopy confirmed the validity of the developed method.     

A chemometric approach to the detection of milk adulteration based on protein profiles determined by capillary electrophoresis

The general objective of this study was to utilize chemometrics in the interpretation of capillary electrophoresis milk protein profiles, for the detection of pasteurized milk adulteration with rehydrated milk powder or a rehydrated dairy-based milk substitute. The specific objectives were 1) to collect quantitative data on major casein and whey proteins in authentic and adulterated milks in a single CE analysis; and 2) to apply a pattern recognition procedure, Soft Independent Modeling of Class Analogies (SIMCA), on collected CE protein data, for the development of a statistical model useful in the detection of pasteurized milk adulteration. Authentic samples were fresh milk collected from various farms over a period of six months. Adulterated samples were authentic fresh milk partially or totally substituted with rehydrated milk powder or a rehydrated commercial milk substitute at different levels. Quantitative protein data obtained by capillary free zone electrophoresis for beta-lactoglobulin, alpha-lactalbumin, beta-casein, and alpha-casein of 86 samples, authentic and adulterated samples, were used as a training set to build a SIMCA multivariate statistical model. The detection of sample outliers was useful for the elimination of unusual samples and optimization of the multivariate model. From the 35 commercial pasteurized milks tested, which were treated as unknowns, a total of 14 samples (40%) were not assigned to the authentic or fresh milk group, meaning that these samples had some type of adulteration at the levels included in the training set (> 15%). Decision-making on detecting adulteration of unknown commercial pasteurized milk samples was eased since predictions were based on statistical probabilities.     

Integrated Biosensor Systems for Ethanol Analysis

Different integrated systems with a bi-enzymatic biosensor, working with two different methods for ethanol detection—flow injection analysis (FIA) or sequential injection analysis (SIA)—were developed and applied for ethanol extracted from gasohol mixtures, as well as for samples of alcoholic beverages and fermentation medium. A detection range of 0.05–1.5 g ethanol/l, with a correlation coefficient of 0.9909, has been reached when using FIA system, working with only one microreactor packed with immobilized alcohol oxidase and injecting free horseradish peroxidase. When using both enzymes, immobilized separately in two microreactors, the detection ranges obtained varied from 0.001 to 0.066 g ethanol/l, without on-line dilution to 0.010–0.047 g ethanol/l when a 1:7,000 dilution ratio was employed, reaching correlation coefficients of 0.9897 and 0.9992, respectively. For the integrated biosensor SIA system with the stop–flow technique, the linear range was 0.005–0.04 g/l, with a correlation coefficient of 0.9922.     

Determination of aluminum in beverages by automated non-segmented continuous flow analysis with fluorescent detection of the lumogallion complex

A method for the automated determination of aluminum in a variety of beverages is described. The method utilizes lumogallion as a complexing agent in a buffer solution. The system is very similar to flow-injection analysis (FIA), however, the tubing id is larger than that typically used in FIA. Therefore, the system is best described as non-segmented continuous flow analysis using fluorescence spectroscopy detection. The method is extremely simple, requiring virtually no sample preparation and only one reagent. The instrument detection limit for aluminum is 0.012 microgram ml-1 and calibration is linear to 3 micrograms ml-1. Results from a variety of beverage matrices are discussed and compared with the frequently used 8-hydroxyquinolone method utilizing a chloroform extraction and fluorescence spectroscopy detection.     

Determination of ethanol in alcoholic beverages by high-performance liquid chromatography-flame ionization detection using pure water as mobile phase

A method for the determination of ethanol in alcoholic beverages by high-performance liquid chromatography-flame ionization detection (HPLC-FID) was developed. An FID system could be directly connected to an HPLC system using pure water as a mobile phase. In a durability test using triacontylsilyl (C30)-silica gel stationary phase for 96 h, no significant change in the retention time of four alcohol compounds was observed. So the HPLC separation of alcoholic beverages was carried out on the C30-silica gel stationary phase. On application to the analysis of six kinds of alcoholic beverages, ethanol could be determined accurately by the proposed method.     

Application of Chromatography and Spectrometry to the Authentication of Alcoholic Beverages

The use of gas chromatography (GC), gas chromatography–mass spectrometry (GC–MS), and UV–VIS spectrophotometry for identifying the falsification of strong alcoholic beverages (vodka, gin, cognac, and whiskey) was considered. In the GC analysis of ethyl alcohol and vodkas based on it, the test alcohol was assigned to synthetic alcohol or to biochemically produced alcohol using a set of typical impurities, markers of the alcohol nature, which present in the test alcohol in a certain ratio and can be determined by GC or GC–MS analysis. The multicomponent analysis of cognacs and related liquors can reveal the replacement of cognac spirit with alcohol produced from nongrape raw materials, to determine whether the cognac spirit was in contact with oak wood and how long was the duration of its aging, and to detect the falsification of the age by adding certain ingredients. The limitations of chromatographic and spectrometric analytical techniques in the identification of adulterated alcoholic beverages was demonstrated. The validation criteria for testing the identification of alcoholic beverage components by chromatographic techniques received special attention.     

Evaluation of headspace solid-phase microextraction for the analysis of volatile carbonyl compounds in spirits and alcoholic beverages

A method was developed for the determination of C1-C6 carbonyl compounds in alcoholic solutions using pentafluorobenzoxymation followed by headspace sampling solid-phase microextraction and subsequent analysis by GC with electron-capture detection. Experimental conditions-alcohol content, exposure time, temperature and sample agitation were optimised. In this method, a spirit or distilled alcoholic beverage is first adjusted to 20% (v/v) alcohol. Detection limits for particular aldehydes and ketone varied from 0.05 to 0.5 microg/l and relative standard deviation was between 2.3 and 20%. Generally, the method showed good linearity for the tested concentration range 8 microg/l-0.32 mg/l with regression coefficients ranging between 0.9434 and 0.9983. The method was applied to the analysis of real alcoholic beverages (vodkas).     

Sequential (step-by-step) detection,identification and quantitation of extra virgin olive oil adulteration by chemometric treatment of chromatographic profiles

An analytical method for the sequential detection, identification and quantitation of extra virgin olive oil adulteration with four edible vegetable oils--sunflower, corn, peanut and coconut oils--is proposed. The only data required for this method are the results obtained from an analysis of the lipid fraction by gas chromatography-mass spectrometry. A total number of 566 samples (pure oils and samples of adulterated olive oil) were used to develop the chemometric models, which were designed to accomplish, step-by-step, the three aims of the method: to detect whether an olive oil sample is adulterated, to identify the type of adulterant used in the fraud, and to determine how much aldulterant is in the sample. Qualitative analysis was carried out via two chemometric approaches--soft independent modelling of class analogy (SIMCA) and K nearest neighbours (KNN)--both approaches exhibited prediction abilities that were always higher than 91% for adulterant detection and 88% for type of adulterant identification. Quantitative analysis was based on partial least squares regression (PLSR), which yielded R2 values of >0.90 for calibration and validation sets and thus made it possible to determine adulteration with excellent precision according to the Shenk criteria.     

Characterization of Gasoline by 1H Nuclear Magnetic Resonance and Chemometrics

Automotive fuel adulteration is an old and significant problem. One common type of fuel adulteration is the addition of diesel to gasoline. Unsupervised models were developed through hierarchical cluster and principal component analysis models. Supervised models through partial least square discriminant analysis using ¹H nuclear magnetic resonance spectra as the input were used to classify samples as adulterated or unadulterated. Quantitative models were developed using partial least squares to determine the gasoline and diesel concentrations in the samples. This set contained samples composed of pure gasoline and anhydrous ethanol reproducing commercial gasoline and other samples treated with diesel. Hierarchical cluster and principal component analysis did not distinguish between adulterated and unadulterated samples except for the most adulterated materials. However, partial least square discriminant analysis classified 100% of the samples correctly. The partial least square algorithm provided excellent regression models for the gasoline and diesel content. The determination coefficient was 0.9920 for both models, whereas the root mean square error of cross-validation and root mean square error of prediction for the diesel model were 2.32 and 1.42%, respectively, and 2.40 and 1.38% for the gasoline model.     

Development and application of an integrated system for monitoring ethanol content of fuels

An automated flow injection analysis (FIA) system for quantifying ethanol was developed using alcohol oxidase, horseradish peroxidase, 4-aminophenazone, and phenol. A colorimetric detection method was developed using two different methods of analysis, with free and immobilized enzymes. The system with free enzymes permitted analysis of standard ethanol solution in a range of 0.05–1.0 g of ethanol/L without external dilution, a sampling frequency of 15 analyses/h, and relative SD of 3.5%. A new system was designed consisting of a microreactor with a 0.91-mL internal volume filled with alcohol oxidase immobilized on glass beads and an addition of free peroxidase, adapted in an FIA line, for continued reuse. This integrated biosensor-FIA system is being used for quality control of biofuels, gasohol, and hydrated ethanol. The FIA system integrated with the microreactor showed a calibration curve in the range of 0.05–1.5 g of ethanol/L, and good results were obtained compared with the ethanol content measured by high-performance liquid chromatography and gas chromatography standard methods.     

Fluorometric determination of urea in alcoholic beverages by using an acid urease column-FIA system

An acid urease column was applied to a fluorometric flow-injection analysis (FIA) system as a recognition element for determination of urea in rice wines.

The acid urease has specific properties of showing its catalytic activity in low pH range and tolerance to ethanol in comparison to those of a urease from jack-beans. The enzymes were covalently immobilized onto porous glass beads with controlled pore size and then, packed into a small polymer column. The flow-type of the biosensing system was assembled with a sample injection valve, the immobilized enzyme column, and a flow-through quartz cell attached to a fluorescent spectrophotometer. Citrate buffer (50 mM, pH 5.0) as the carrier solution was continuously pumped through the system. Sample solutions were introduced into the system via a rotary injection valve. A standard urea solution was measured through monitoring variations in fluorescent intensity attributable to fluorescent isoindole derivatives formed by coupling with ammonia molecules released in the enzymatic hydrolysis of urea and orthophthalaldehyde reagents. The fluorescent intensity was measured under the conditions of λ_ex = 415 nm and λ_em = 485 nm. A wide, linear relationship was obtained between the concentration of urea (1.0–100 μM) and the variation in fluorescent intensity. The monitoring did not suffer from ethanol and various amino acids contained in rice wines. Real samples pretreated with ion exchange resins for removal of endogenous ammonia were introduced into the FIA system and urea in the samples was determined. These results were compared with those obtained with use of an F-kit method. The proposed FIA system should present sensitive, selective and convenient analysis of urea in alcoholic beverages.     

Screening Brazilian commercial gasoline quality by hydrogen nuclear magnetic resonance spectroscopic fingerprintings and pattern-recognition multivariate chemometric analysis

The identification of gasoline adulteration by organic solvents is not an easy task, because compounds that constitute the solvents are already in gasoline composition. In this work, the combination of Hydrogen Nuclear Magnetic Resonance (¹H NMR) spectroscopic fingerprintings with pattern-recognition multivariate Soft Independent Modeling of Class Analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a Monitoring Program for Quality Control of Automotive Fuels. SIMCA was performed on spectroscopic fingerprints to classify the quality of representative commercial gasoline samples selected by Hierarchical Cluster Analysis (HCA) and collected over a 6-month period from different gas stations in the São Paulo state, Brazil. Following optimized the ¹H NMR-SIMCA algorithm, it was possible to correctly classify 92.0% of commercial gasoline samples, which is considered acceptable. The chemometric method is recommended for routine applications in Quality-Control Monitoring Programs, since its measurements are fast and can be easily automated. Also, police laboratories could employ this method for rapid screening analysis to discourage adulteration practices.     

Structural and thermal characterization of Fe(III) and Fe(II) complexes with tridentate ONO pyridoxal semicarbazone

In the scope of design and optimise the equipment for alcoholic distillate beverages production, a sufficient knowledge of physical properties and phase equilibria is necessary. In this paper we present the temperature dependence of excess molar volumes of the ternary system ethanol+water+1-propanol at the range 288.15–323.15 K and atmospheric pressure, due to the importance of the 1-propanol among the flavour compounds contained into this type of beverages. Derived properties were computed due to its importance in the study of specific molecular interactions.     

Detection of the adulteration of traditional alcoholic beverages by the separation and determination of alprazolam, chloralhydrate and diazepam using reversed-phase high-performance liquid chromatography.

A simple, rapid and reliable reversed-phase high-performance liquid chromatographic method for the separation and determination of psycotropic substances viz., alprazolam, chloral hydrate and diazepam in traditional alcoholic beverages, such as toddy, has been developed. Separation was accomplished using a reversed-phase C18 column with water-methanol-acetic acid (35:65:0.1 v/v/v) as a mobile solvent and a photo-diode array detector at 210 nm. The limits of detection of alprazolam, chloral hydrate and diazepam were determined to be 0.8, 4.5 and 0.4 microg, respectively. The validity of the method was checked by analyzing nearly 200 samples collected from different outlets by enforcement authorities, and the extent of adulteration was determined.     

Chromatographic study of the chemical composition and potential toxicity of spirits and alcoholic beverages

The composition of vodkas, rectified food alcohols, cognacs, cognac spirits, and other strong alcoholic beverages was studied by chromatography and compared with the composition of industrial (synthetic and hydrolysis) ethyl alcohols, adulterated cognacs, and homemade spirits (samogon) from the illicit market. It was found that the majority of the test alcohol-containing liquids were close to commercial alcoholic beverages in terms of chemical composition and toxic properties. The samples containing ethylene glycol and enriched components of the head fraction of rectification should be considered most toxic.