Multi-commutated flow system for inorganic selenium speciation in infusion tea samples by chemical vapor generation atomic fluorescence spectrometry.

This work proposes an automated strategy for the inorganic selenium speciation in infusion tea samples, employing an MSFIA-CVG-AFS system and sodium tetrahydroborate for chemical vapor generation. The selenium total is determined after an online prereduction step of selenium (VI) to selenium (IV) in alkaline media, using a UV reactor with a 15 W Hg lamp. Selenium (IV) is quantified directly on the sample, and selenium (VI) is determined by the difference between the total selenium and selenium (IV) concentrations. The optimization of the chemical parameters: hydrochloric acid - hydrobromide acid solution concentration, potassium iodide concentration, sodium hydroxide concentration, and sodium tetrahydroborate concentration was performed using a (24-1) two-level fractional factorial design. The validation parameters were determined for total selenium and selenium (IV), and the results found were: limits of detection and quantification of 0.05 and 0.18 µg L-1, respectively; a linear range of 0.18-5.0 µg L-1, precision expressed as the relative standard deviation of 2.1% for a sample number of 10, for both analytes. The system allows the speciation analysis with an injection throughput of 15 injections per hour. This analytical method was applied for inorganic selenium speciation in nine infusions of tea samples purchased commercially in supermarkets in Palma de Mallorca City, Spain. The concentrations of selenium (IV) and total selenium varied from 0.2 to 0.6 µg L-1 and 0.4-2.0 µg L-1, respectively. The accuracy method was evaluated using spike tests, and the recoveries achieved varied from 91 to 111%.

Speciation analysis based on digital image colorimetry: Iron (II/III) in white wine.

This work proposes an analytical strategy utilizing digital images (DI) for the iron inorganic speciation in white wine. The method was established by the reaction of iron(II) ions with 1,2 ortho-phenanthroline as a chromogenic reagent. Total iron was determined using the same reagent after the addition of hydroxyl ammonium chloride as a reducing agent. In both cases, digital images of the standards/chromogenic reagent and samples were acquired and stored in JPEG format. The region of interest (ROI) was determined with a constant square shape for all images. The ROI was submitted to decomposition in color values according to the RGB additive color model. However, the data obtained by the blue channel was the one used in the construction of the analytical curves because it presented the highest sensitivity. The optimization of the experimental conditions of the procedure was performed by employing multivariate techniques. The precision was evaluated using a wine sample with iron (II) and total iron contents of 0.41 and 0.69 mg L-1, respectively. The results expressed as relative standard deviations were 3.57% for iron (II) and 4.76% for total iron contents. A comparison between the results obtained for total iron by the DI method with the results found using flame atomic absorption spectrometry confirmed the method accuracy. The DI procedure was applied for speciation analysis in six white wine samples and the contents found varied from 0.41 to 1.67 mg L-1 for iron (II) and from 0.69 to 1.71 mg L-1 for total iron. These results are in agreement with those found for speciation analysis of iron in wine samples. Iron (III) contents can be found by the difference between the total iron and iron (II) contents.

Multivariate optimization techniques in food analysis - A review.

This work presents a critical review of multivariate techniques employed for optimization of methods developed in food analysis. A comparison between the response surface methodologies has been performed, it evidencing advantages and drawbacks of these. Applications of the main chemometric tools (central composite and Box Behnken designs and Doehlert matrix) often utilized for optimization of sample preparation procedures and also instrumental conditions of analytical techniques for determination of organic and inorganic species in food samples are shown. Also, a brief discussion on the use of multiple responses and robustness test in food analysis has been presented.