Fast Determination of Biodiesel Content in Commercial Diesel/Biodiesel Blends by Using Digital Images and Multivariate Calibration.

A new simple, rapid and inexpensive analytical method was developed to determine the biodiesel percentage in biodiesel/diesel blends through simple digital images of samples obtained by scanning with a commercial scanner. Soybean biodiesel and petroleum diesel samples were acquired from refineries currently in operation. There were prepared several mixtures within the range 1.5 to 12.0% of biodiesel in diesel oil, using the same procedure as is done in industry. The analytical signals were images recorded with a scanner. This data was decomposed with different color systems: RGB, HSV, HLS, CMYK and Grayscale. Chemometrics models based on color signals obtained from different mixtures of biodiesel/diesel were built. The quantification by using partial least squares (PLS) resulted in a RMSEP value for biodiesel of 0.9% (w/w); this load approximately 10-times smaller than the corresponding calibration range, with a correlation of 0.96 between predicted and reference values.

Single excitation-emission fluorescence spectrum (EEF) for determination of cetane improver in diesel fuel.

A highly sensitive spectrofluorimetric method has been developed for the determination of 2-ethylhexyl nitrate in diesel fuel. Usually, this compound is used as an additive in order to improve cetane number. The analytical method consists in building the chemometric model as a first step. Then, it is possible to quantify the analyte with only recording a single excitation-emission fluorescence spectrum (EEF), whose data are introduced in the chemometric model above mentioned. Another important characteristic of this method is that the fuel sample was used without any pre-treatment for EEF. This work provides an interest improvement to fluorescence techniques using the rapid and easily applicable EEF approach to analyze such complex matrices. Exploding EEF was the key to a successful determination, obtaining a detection limit of 0.00434% (v/v) and a limit of quantification of 0.01446% (v/v).

Second order advantage applied to the spectrophotometric analysis of ciprofloxacin and dexamethasone in ophthalmic drops; automatic green method using on-line photodegradation.

On-line photodegradation and spectrophotometric analysis assisted by multivariate curve resolution-alternating least squares (MCR-ALS) was developed the simultaneous determination of ciprofloxacin (CIP) and dexamethasone (DEX) in ophthalmic suspensions using an automated flow-batch analysis (FBA) system. CIP and DEX have strongly overlapped UV spectra. Overcoming this lack of selectivity involves augmenting data dimensionality. This could be performed by adding information about the sample photodegradation to obtain the so-called second order advantage. Commercial sample analysis was successfully performed and no statistical differences (α = 0.05) with respect to pharmacopeia methods were obtained. The proposed method offers several advantages over the methods developed to date. In agreement with the principles of green chemistry, only water was used as solvent, low amounts of waste were generated and on-line waste treatment was included in the system. Moreover, the cost per analysis was significantly reduced compared to methods that employ separative techniques.

Chemometric approach to visualize and easily interpret data from sequential extraction procedures applied to sediment samples.

The aim of this study was to assess metal mobility/availability in coastal surface (oxic) sediment samples from the Bahía Blanca estuary. Particularly, two sequential extraction procedures able to discriminate metals associated to amorphous Fe and Mn oxides and those associated with crystalline oxides of Fe were applied. Sequential procedures differ in the number of steps, type of reagents used, and in the order in which metals associated to organic matter are extracted. The studied metals were Cd, Cr, Cu, Pb, Ni and Zn because of their hazardous potential and relative abundance in the estuary. Tucker4 model with three factors describes appropriately the data sets (explained variance of 64.05%). This model made it possible to visualize and explain the information underlying in the data set. From the multivariate analysis, it was possible to evaluate the metal behaviour and their availability. In this way, Cd and Zn are associated to the more available fractions whereas Ni, Cr, Cu and Pb are mainly associated to the unavailable fractions. On the other hand, Zn and Cu are associated to organic matter fraction. Despite the fact that the two-fractionation schemes are quite different, the results obtained with both schemes are comparable.

Analysis of metals and phosphorus in biodiesel B100 from different feedstock using a Flow Blurring® multinebulizer in inductively coupled plasma-optical emission spectrometry.

A simple and fast method for determining the content of Na, K, Ca, Mg, P, and 20 heavy metals in biodiesel samples with inductively coupled plasma optical emission spectrometry (ICP OES) using a two-nozzle Flow Blurring(®) multinebulizer prototype and on-line internal standard calibration, are proposed. The biodiesel samples were produced from different feedstock such as sunflower, corn, soybean and grape seed oils, via a base catalyst transesterification. The analysis was carried out without any sample pretreatment. The standards and samples were introduced through one of the multinebulizer nozzles, while the aqueous solution containing yttrium as an internal standard was introduced through the second nozzle. Thus, the spectral interferences were compensated and the formation of carbon deposits on the ICP torch was prevented. The determination coefficients (R(2)) were greater than 0.99 for the studied analytes, in the range 0.21-14.75 mg kg(-1). Short-term and long-term precisions were estimated as relative standard deviation. These were acceptable, their values being lower than 10%. The LOQ for major components such as Ca, K, Mg, Na, and P, were within a range between 4.9 ng g(-1) for Mg (279.553 nm) and 531.1 ng g(-1) for Na (588.995 nm), and for the other 20 minor components they were within a range between 1.1 ng g(-1) for Ba (455.403 nm) and 2913.9 ng g(-1) for Pb (220.353 nm). Recovery values ranged between 95% and 106%.

Quantification of uncertainty in mercury wastewater analysis at different concentration levels and using information from proficiency test with a limited number of participants.

Measurement uncertainty is one of the most required parameters of analytical quality in environmental decision-making. Several approaches have been reported for estimating uncertainty in analytical measurements. The use of proficiency test (PT) is an alternative, not only for assessing the performance of individual analytical laboratories, but also for estimating the concordance of an analytical method and their measurement uncertainties. Here we develop a PT scheme for a limited number of analytical laboratories that took part in the analysis of total mercury in samples with complex matrix (chlor-alkali process wastewater effluent) in absence of references of the highest metrological hierarchy (e.g. primary method, primary CRM). Two in-house reference materials (IHRMs) were prepared at different levels of analyte concentration and the homogeneity required was verified for the intended use. A set of parametric and robust statistical tests were applied to evaluate the assigned values of each IHRM. Metrological compatibility assessment of PT results, evaluation of individual and global performance of the laboratories, and determination of uncertainty of the analytical measurements were evaluated in this restricted study scenario. Between-laboratory differences were found not significant (α=0.05). For both concentration levels we computed a relative standard uncertainty of 30% for the total Hg content.

Hybrid hard- and soft-modeling of spectrophotometric data for monitoring of ciprofloxacin and its main photodegradation products at different pH values.

A simple and fast on line spectrophotometric method combined with a hybrid hard-soft modeling multivariate curve resolution (HS-MCR) was proposed for the monitoring of photodegradation reaction of ciprofloxacin under UV radiation. The studied conditions attempt to emulate the effect of sunlight on these antibiotics that could be eventually present in the environment. The continuous flow system made it possible to study the ciprofloxacin degradation at different pH values almost at real time, avoiding errors that could arise from typical batch monitoring of the reaction. On the base of a concentration profiles obtained by previous pure soft-modeling approach, reaction pathways have been proposed for the parent compound and its photoproducts at different pH values. These kinetic models were used as a constraint in the HS-MCR analysis. The kinetic profiles and the corresponding pure response profile (UV-Vis spectra) of ciprofloxacin and its main degradation products were recovered after the application of HS-MCR analysis to the spectra recorded throughout the reaction. The observed behavior showed a good agreement with the photodegradation studies reported in the bibliography. Accordingly, the photodegradation reaction was studied by high performance liquid chromatography coupled with UV-Vis diode array detector (HPLC-DAD). The spectra recorded during the chromatographic analysis present a good correlation with the ones recovered by UV-Vis/HS-MCR method.

An ultrasonic-accelerated oxidation method for determining the oxidative stability of biodiesel.

Biodiesel is considered an alternative energy because it is produced from fats and vegetable oils by means of transesterification. Furthermore, it consists of fatty acid alkyl esters (FAAS) which have a great influence on biodiesel fuel properties and in the storage lifetime of biodiesel itself. The biodiesel storage stability is directly related to the oxidative stability parameter (Induction Time - IT) which is determined by means of the Rancimat® method. This method uses condutimetric monitoring and induces the degradation of FAAS by heating the sample at a constant temperature. The European Committee for Standardization established a standard (EN 14214) to determine the oxidative stability of biodiesel, which requires it to reach a minimum induction period of 6h as tested by Rancimat® method at 110°C. In this research, we aimed at developing a fast and simple alternative method to determine the induction time (IT) based on the FAAS ultrasonic-accelerated oxidation. The sonodegradation of biodiesel samples was induced by means of an ultrasonic homogenizer fitted with an immersible horn at 480Watts of power and 20 duty cycles. The UV-Vis spectrometry was used to monitor the FAAS sonodegradation by measuring the absorbance at 270nm every 2. Biodiesel samples from different feedstock were studied in this work. In all cases, IT was established as the inflection point of the absorbance versus time curve. The induction time values of all biodiesel samples determined using the proposed method was in accordance with those measured through the Rancimat® reference method by showing a R(2)=0.998.

Successive projections algorithm applied to spectral data for the simultaneous determination of flavour enhancers.

A novel variable selection strategy for multiple lineal regression (MLR), the successive projections algorithm (SPA), was applied to spectrophotometric data (190-320 nm) for the simultaneous determination of monosodium glutamate (MSG), guanosine-5'-monophosphate (GMP) and inosine-5'-monophosphate (IMP) in dehydrated broths samples. This selection method uses simple operations in a vector space to minimize variable collinearity and has become an interesting variable selection strategy for multivariate calibration. In this work, nine, six and four wavelengths for MSG, GMP and IMP, respectively, were selected to construct calibrations models in order to solve successfully the serious spectral overlapping in samples containing these analytes. The relative errors of prediction (REP) for the validation set were 2.3%, 0.9% and 1.8% for MSG, GMP and IMP, respectively. Commercial samples were analysed and a recovery study was carried out to verify the accuracy of the proposed method with satisfactory results. A continuous flow system was used to develop a simple, cheap and rapid method (sample throughput: 200 h(-1)), without any previous extraction step.

Kinetic approach for the enzymatic determination of levodopa and carbidopa assisted by multivariate curve resolution-alternating least squares.

A combination of kinetic spectroscopic monitoring and multivariate curve resolution-alternating least squares (MCR-ALS) was proposed for the enzymatic determination of levodopa (LVD) and carbidopa (CBD) in pharmaceuticals. The enzymatic reaction process was carried out in a reverse stopped-flow injection system and monitored by UV-vis spectroscopy. The spectra (292-600 nm) were recorded throughout the reaction and were analyzed by multivariate curve resolution-alternating least squares. A small calibration matrix containing nine mixtures was used in the model construction. Additionally, to evaluate the prediction ability of the model, a set with six validation mixtures was used. The lack of fit obtained was 4.3%, the explained variance 99.8% and the overall prediction error 5.5%. Tablets of commercial samples were analyzed and the results were validated by pharmacopeia method (high performance liquid chromatography). No significant differences were found (alpha=0.05) between the reference values and the ones obtained with the proposed method. It is important to note that a unique chemometric model made it possible to determine both analytes simultaneously.

Flow-batch technique for the simultaneous enzymatic determination of levodopa and carbidopa in pharmaceuticals using PLS and successive projections algorithm.

An enzymatic flow-batch system with spectrophotometric detection was developed for simultaneous determination of levodopa [(S)-2 amino-3-(3,4-dihydroxyphenyl)propionic acid] and carbidopa [(S)-3-(3,4-dihydroxyphenyl)-2-hydrazino-2-methylpropionic acid] in pharmaceutical preparations. The data were analysed by univariate method, partial least squares (PLS) and a novel variable selection for multiple lineal regression (MLR), the successive projections algorithm (SPA). The enzyme polyphenol oxidase (PPO; EC 1.14.18.1) obtained from Ipomoea batatas (L.) Lam. was used to oxidize both analytes to their respective dopaquinones, which presented a strong absorption between 295 and 540 nm. The statistical parameters (RMSE and correlation coefficient) calculated after the PLS in the spectral region between 295 and 540 nm and MLR-SPA application were appropriate for levodopa and carbidopa. A comparative study of univariate, PLS, in different ranges, and MLR-SPA chemometrics models, was carried out by applying the elliptical joint confidence region (EJCR) test. The results were satisfactory for PLS in the spectral region between 295 and 540 nm and for MLR-SPA. Tablets of commercial samples were analysed and the results obtained are in close agreement with both, spectrophotometric and HPLC pharmacopeia methods. The sample throughput was 18 h(-1).

Determination of phenol, resorcinol and hydroquinone in air samples by synchronous fluorescence using partial least-squares (PLS).

The determination of phenolic compounds is of great importance owing to their high toxicity. Some of them are present in tobacco smoke and it is important for their monitoring in air of closed room. A simple, rapid and sensitive method was developed for simultaneous determination of hydroquinone, resorcinol and phenol in this kind of samples. Synchronous fluorescence technique was used and the data were processed by using the partial least-squares (PLS) chemometric algorithm. The concentrations for experimental calibration matrix were varied between 0.02 and 0.2 mg L(-1) for hydroquinone, between 0.05 and 0.6 mg L(-1) for resorcinol and between 0.05 and 0.4 mg L(-1) for phenol in accordance with the national legislation. The cross-validation method was used to select the number of factors. To check the accuracy of the proposed method a recovery study on real samples was carried out.

Simultaneous determination of levodopa and benserazide by stopped-flow injection analysis and three-way multivariate calibration of kinetic-spectrophotometric data.

The simultaneous determination of levodopa and benserazide in pharmaceutical formulations is described, based on the application of multidimensional partial least-squares regression to the kinetic-spectrophotometric data provided by diode-array detection within a stopped-flow injection method where analytes react with periodate. Flow injection parameters were adequately optimized. Accurate analysis is performed with no sample pre-treatment steps, and with minimum experimental effort. Satisfactory recovery results were obtained on a number of synthetic and commercial samples, in the latter case including the comparison with liquid chromatography measurements.

New method for the determination of benzoic and sorbic acids in commercial orange juices based on second-order spectrophotometric data generated by a pH gradient flow injection technique.

Two widely employed antimicrobials, benzoic and sorbic acids, were simultaneously determined in commercial orange juices employing a combination of a flow injection system with pH gradient generation, diode array spectrophotometric detection, and chemometric processing of the recorded second-order data. Parallel factor analysis and multivariate curve resolution-alternating least-squares were used for obtaining the spectral profiles of sample components and concentration profiles as a function of pH, including provisions for managing rank-deficient data sets. An appropriately designed calibration with a nine-sample set of binary mixtures of standards, coupled to the use of the second-order advantage offered by the applied chemometric techniques, allowed quantitation of the analytes in synthetic test samples and also in commercial orange juices, even in the presence of unmodeled interferents (with relative prediction errors of 8.7% for benzoic acid and 2.5% for sorbic acid). No prior separation or sample pretreatment steps were required. The comparison of results concerning commercial samples with a laborious reference technique yielded satisfactory statistical indicators (recoveries were 99.0% for benzoic acid and 101.4% for sorbic acid).

A sensitive spectrophotometric method for lead determination by flow injection analysis with on-line preconcentration.

A new flow injection (FI) system for the determination of Pb(II) at trace level with a preconcentration step and spectrophotometric detection is proposed. It is based on preconcentration of lead ions on chitosan and dithizone-lead complex formation in aqueous medium (pH 9). The chemicals and FIA variables influencing the performance of the system were optimized and applied to the determination of lead in natural, well, and drinking water samples. It is a simple, highly sensitive, and low cost alternative methodology. The method provided a linear rage between 25 and 250mugl(-1), a detection limit of 5.0ngml(-1) and a sample throughput of 15h(-1). The obtained results of spiked samples are in good agreement between the proposed method and ICP-AES.

Flow injection analysis: Rayleigh light scattering technique for total protein determination.

A novel flow injection analysis (FIA) method with Rayleigh light scattering (RLS) detection was developed for the determination of total protein concentrations. This method is based on the weak intensity of RLS of bromothymol blue (BB) (3',3"-dibromothymolsulfonephthalein) which can be enhanced by the addition of protein in weakly acidic solution. A common spectrofluorimeter was used as a detector. It was proved that the application of this method to quantify the total proteins in real samples by using bovine serum albumin was possible. The RLS signal was detected at lambda(ex)= lambda(em)=572 nm. The linear range was 7.0-70.0 microg mL(-1), the detection limit was 3.75 microg mL(-1), the reproducibility was 5.5% (n=7), and the sample throughput was 26 h(-1).