Marcelo F. Pistonesi

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.

Automatized flow-batch method for fluorescent determination of free glycerol in biodiesel samples using on-line extraction.

An automatic method, based on flow-batch (FB), for determining glycerol in biodiesel was developed. The FB systems draw upon the useful features of flow, batch and multi-commutation approaches. The standards and samples preparation, as well as, derivatization and analysis were fully automated. For that purpose, a homemade chamber was built. The proposed method is based on liquid-liquid extraction of glycerol and simultaneous oxidation with periodate, generating formaldehyde that reacts with acetylacetone. A fluorescent product of 3,5-diacetyl-1,4-dihydrolutidine was obtained. The fluorescence signal was recorded at λ(ex) =417 nm and λ(em) = 514 nm. A linear response was observed from 0.10 to 5.00 mg L(-1) glycerol, variation coefficient 1.5%, sampling rate 14 h(-1) and detection limit 0.036 mg L(-1) glycerol. The procedure was successfully applied to the analysis of biodiesel samples, and the results agreed with the reference method (ASTM D6584-07) at 95% confidence level.

Screening analysis of biodiesel feedstock using UV–vis, NIR and synchronous fluorescence spectrometries and the successive projections algorithm

This paper investigates the use of UV-vis, near infrared (NIR) and synchronous fluorescence (SF) spectrometries coupled with multivariate classification methods to discriminate biodiesel samples with respect to the base oil employed in their production. More specifically, the present work extends previous studies by investigating the discrimination of corn-based biodiesel from two other biodiesel types (sunflower and soybean). Two classification methods are compared, namely full-spectrum SIMCA (soft independent modelling of class analogies) and SPA-LDA (linear discriminant analysis with variables selected by the successive projections algorithm). Regardless of the spectrometric technique employed, full-spectrum SIMCA did not provide an appropriate discrimination of the three biodiesel types. In contrast, all samples were correctly classified on the basis of a reduced number of wavelengths selected by SPA-LDA. It can be concluded that UV-vis, NIR and SF spectrometries can be successfully employed to discriminate corn-based biodiesel from the two other biodiesel types, but wavelength selection by SPA-LDA is key to the proper separation of the classes.

Using UV-Vis spectroscopy for simultaneous geographical and varietal classification of tea infusions simulating a home-made tea cup.

In this work we proposed a method to verify the differentiating characteristics of simple tea infusions prepared in boiling water alone (simulating a home-made tea cup), which represents the final product as ingested by the consumers. For this purpose we used UV-Vis spectroscopy and variable selection through the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA) for simultaneous classification of the teas according to their variety and geographic origin. For comparison, KNN, CART, SIMCA, PLS-DA and PCA-LDA were also used. SPA-LDA and PCA-LDA provided significantly better results for tea classification of the five studied classes (Argentinean green tea; Brazilian green tea; Argentinean black tea; Brazilian black tea; and Sri Lankan black tea). The proposed methodology provides a simpler, faster and more affordable classification of simple tea infusions, and can be used as an alternative approach to traditional tea quality evaluation as made by skilful tasters, which is evidently partial and cannot assess geographic origins.

Using a simple digital camera and SPA-LDA modeling to screen teas

Classification or screening analysis of natural unprocessed teas using simple digital images and a variable selection algorithm is described. The proposed methodology uses color histograms generated on free downloadable software ImageJ 1.44p as a source of analytical information. Two chemometric methods were compared for classification of the resulting images, namely Soft Independent Modeling of Class Analogy (SIMCA), and Linear Discriminant Analysis (LDA) with variable selection by the Successive Projections Algorithm (SPA). The results were evaluated in terms of errors found in a sample set separate from the modeling process. The choice of more informative photometric color attributes (red-green-blue (RGB), hue (H), saturation (S), brightness (B), and grayscale) for screening the tea samples was made during the color modeling because SIMCA failed to give good results. Therefore the data treatment used SPA-LDA, which correctly classified all samples according to their geographical regions, whether from Brazilian, Argentinian or foreign soils.

Simultaneous determination of hydroquinone, resorcinol, phenol, m-cresol and p-cresol in untreated air samples using spectrofluorimetry and a custom multiple linear regression-successive projection algorithm

In this study, a novel, simple, and efficient spectrofluorimetric method to determine directly and simultaneously five phenolic compounds (hydroquinone, resorcinol, phenol, m-cresol and p-cresol) in air samples is presented. For this purpose, variable selection by the successive projections algorithm (SPA) is used in order to obtain simple multiple linear regression (MLR) models based on a small subset of wavelengths. For comparison, partial least square (PLS) regression is also employed in full-spectrum. The concentrations of the calibration matrix ranged from 0.02 to 0.2 mg L(-1) for hydroquinone, from 0.05 to 0.6 mg L(-1) for resorcinol, and from 0.05 to 0.4 mg L(-1) for phenol, m-cresol and p-cresol; incidentally, such ranges are in accordance with the Argentinean environmental legislation. To verify the accuracy of the proposed method a recovery study on real air samples of smoking environment was carried out with satisfactory results (94-104%). The advantage of the proposed method is that it requires only spectrofluorimetric measurements of samples and chemometric modeling for simultaneous determination of five phenols. With it, air is simply sampled and no pre-treatment sample is needed (i.e., separation steps and derivatization reagents are avoided) that means a great saving of time.

Automatic Flow-Batch System for Cold Vapor Atomic Absorption Spectroscopy Determination of Mercury in Honey from Argentina Using Online Sample Treatment

An automatic flow-batch system that includes two borosilicate glass chambers to perform sample digestion and cold vapor atomic absorption spectroscopy determination of mercury in honey samples was designed. The sample digestion was performed by using a low-cost halogen lamp to obtain the optimum temperature. Optimization of the digestion procedure was done using a Box-Behnken experimental design. A linear response was observed from 2.30 to 11.20 μg Hg L(-1). The relative standard deviation was 3.20% (n = 11, 6.81 μg Hg L(-1)), the sample throughput was 4 sample h(-1), and the detection limit was 0.68 μg Hg L(-1). The obtained results with the flow-batch method are in good agreement with those obtained with the reference method. The flow-batch system is simple, allows the use of both chambers simultaneously, is seen as a promising methodology for achieving green chemistry goals, and is a good proposal to improving the quality control of honey.

Turbidimetric and photometric determination of total tannins in tea using a micro-flow-batch analyzer.

Both turbidimetric and photometric determinations of total tannins in samples of green and black tea, using a micro-flow-batch analyzer (μFBA) were studied. The miniaturized system was formed using photocurable urethane-acrylate resin and ultraviolet lithography technique. The turbidimetric method was based on the precipitation reaction of Cu (II) with tannins in acetate medium at a pH of 4.5. The photometric method was based on the complexation reaction of tannins with ferrous tartrate. The turbidimetric μFBA was able to test 200 samples per hour. The photometric μFBA allowed 300 analyses per hour, generating 136μL of residue per analysis. The paired t test, at a 95% confidence level, showed no statistically significant differences between results obtained by both methods and the reference method. The urethane-acrylate μFBA maintained satisfactory physical and chemical properties, and represents an improvement over conventional flow-batch analyzer.

Eco-friendly sonoluminescent determination of free glycerol in biodiesel samples

This paper proposes a flow-batch methodology for the determination of free glycerol in biodiesel that is notably eco-friendly, since non-chemical reagents are used. Deionized water (the solvent) was used alone for glycerol (sample) extractions from the biodiesel. The same water was used to generate water-cavitation sonoluminescence signals, which were modulated by the quenching effect associated with the amount of extracted glycerol. The necessarily reproducible signal generation was achieved by using a simple and inexpensive piezoelectric device. A linear response was observed for glycerol within the 0.001-100 mg/L range, equivalent to 0.004-400 mg/kg free glycerol in biodiesel. The lowest measurable concentration of free glycerol was estimated at 1.0 µg/L. The selectivity of the proposed method was confirmed by comparing the shape and retention of both real and calibration samples to standard solution chromatograms, presenting no peaks other than glycerol. All samples (after extraction) are greatly diluted; this minimizes (toward non-detectability) potential interference effects. The methodology was successfully applied to biodiesel analysis at a high sampling rate, with neither reagent nor solvent (other than water), and with minimum waste generation. The results agreed with the reference method (ASTM D6584-07), at a 95% confidence level.

A new automated approach to determine monosodium glutamate in dehydrated broths by using the flow-batch methodology

The advantages of the flow-batch methodology were exploited to implement a simple system with nephelometric detection for the determination of monosodium glutamate (MSG) in food samples. The method is based on the inhibitory effect of the MSG over the crystallization of L-lysine in an isopropanol/acetone mixture. The calibration curve was prepared on-line. The method was linear over the range of 2.8 x 10(-3) to 1.1 x 10(-2)gL(-1) and a detection limit of 9.7 x 10(-5)gL(-1) was achieved. It was successfully applied to determine the MSG concentration in food samples, without a previous treatment. A recovery study was carried out on real samples and the percentages were between 98 and 106%.