Green-tea-synthesized silver nanoparticles as a sensing platform for determination of tetracycline in honey samples.

BACKGROUND: Silver nanoparticles (AgNPs) can be easily obtained in aqueous solution by chemical reduction using appropriate reducing agents and stabilizers. The development of environmentally friendly methods using non-toxic solvents and reagents has become an alternative for the synthesis of these particles and their future application as sensor probes for agricultural products. In this work, a straightforward method based on green tea extracts as reducing and capping agent is proposed for the synthesis of AgNPs, followed by their evaluation as a sensing platform for determination of tetracycline in honey samples. RESULTS: Highly stable nanoparticles were easily obtained by combining green tea aqueous extracts and ultrasound irradiation for 2 min. The as-synthesized AgNPs, spherical in shape and with average size of 8.5 nm, were evaluated for determination of tetracycline by following the changes on the localized surface plasmon resonance band at 450 nm induced by the presence of this antibiotic at pH 5.8. The method was successfully applied in the concentration range between 200 and 800 µg L-1 with R2 > 0.996 and limit of detection of 52.7 µg L-1 . Multiple honey samples were analyzed, and the recovery values obtained ranged between 82.8% and 116%, with relative standard deviation values lower than 6.69%. CONCLUSION: The results obtained demonstrate that the AgNPs synthesized using just green tea extracts represent a promising and sustainable alternative tool for the cost-effective determination of tetracycline antibiotics in honey. © 2021 Society of Chemical Industry.

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.

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.

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).

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.