Point-of-use detection of ascorbic acid using a spectrometric smartphone-based system.

A rapid and portable analytical methodology has been developed for ascorbic acid (Vitamin C) quantification from aqueous samples using a spectrometric smartphone-based system for the first time. The method employs point-of-use approaches both for sample preparation and sample measurement, demonstrating the capability for mobile quality control of pharmaceutical and food products. Our approach utilizes an oxidation-reduction reaction between ascorbic acid and methylene blue, followed by a dispersive liquid-liquid microextraction (DLLME) to extract the aqueous-phase methylene blue into organic media. Then, a back-extraction procedure is employed to transfer the methylene blue to aqueous media, followed by analysis of the sample's absorption spectrum using the spectrometric smartphone-based system. The DLLME and back-extraction procedures are optimized by use of a two-step multivariate optimization strategy. Finally, vitamin C supplements and orange juice are used as real-world samples to assess the applicability of the smartphone-based method, which is successfully compared with the standard laboratory-based approach.

Rapid determination of hydrophilic phenols in olive oil by vortex-assisted reversed-phase dispersive liquid-liquid microextraction and screen-printed carbon electrodes.

A novel approach is presented to determine hydrophilic phenols in olive oil samples, employing vortex-assisted reversed-phase dispersive liquid-liquid microextraction (RP-DLLME) for sample preparation and screen-printed carbon electrodes for voltammetric analysis. The oxidation of oleuropein, hydroxytyrosol, caffeic acid, ferulic acid and tyrosol was investigated, being caffeic acid and tyrosol selected for quantification. A matrix-matching calibration using sunflower oil as analyte-free sample diluted with hexane was employed to compensate matrix effects. Samples were analyzed under optimized RP-DLLME conditions, i.e., extractant phase, 1M HCl; extractant volume, 100µL; extraction time, 2min; centrifugation time, 10min; centrifugation speed, 4000rpm. The working range showed a good linearity between 0.075 and 2.5mgL-1 (r = 0.998, N = 7) for caffeic acid, and between 0.075 and 3mgL-1 (r = 0.999, N = 8) for tyrosol. The methodological limit of detection was empirically established at 0.022mgL-1 for both analytes, which is significantly lower than average contents found in olive oil samples. The repeatability was evaluated at two different spiking levels (i.e., 0.5mgL-1 and 2mgL-1) and coefficients of variation ranged from 8% to 11% (n = 5). The applicability of the proposed method was tested in olive oil samples of different quality (i.e., refined olive oil, virgin olive oil and extra virgin olive oil). Relative recoveries varied between 83% and 108% showing negligible matrix effects. Finally, fifteen samples were analyzed by the proposed method and a high correlation with the traditional Folin-Ciocalteu spectrophotometric method was obtained. Thereafter, the concentrations of the fifteen oil samples were employed as input variables in linear discriminant analysis in order to distinguish between olive oils of different quality.

Microwave-Assisted Extraction of Phenolic Compounds from Almond Skin Byproducts (Prunus amygdalus): A Multivariate Analysis Approach.

A microwave-assisted extraction (MAE) procedure to isolate phenolic compounds from almond skin byproducts was optimized. A three-level, three-factor Box-Behnken design was used to evaluate the effect of almond skin weight, microwave power, and irradiation time on total phenolic content (TPC) and antioxidant activity (DPPH). Almond skin weight was the most important parameter in the studied responses. The best extraction was achieved using 4 g, 60 s, 100 W, and 60 mL of 70% (v/v) ethanol. TPC, antioxidant activity (DPPH, FRAP), and chemical composition (HPLC-DAD-ESI-MS/MS) were determined by using the optimized method from seven different almond cultivars. Successful discrimination was obtained for all cultivars by using multivariate linear discriminant analysis (LDA), suggesting the influence of cultivar type on polyphenol content and antioxidant activity. The results show the potential of almond skin as a natural source of phenolics and the effectiveness of MAE for the reutilization of these byproducts.