Standard Curve

High-performance liquid chromatography (HPLC) to determine shikimic acid is used as a complementary tool to differentiate wine varieties. In order to correctly classify, measurement uncertainty of shikimic acid by HPLC in red wine was estimated considering the following components: uncertainty associated with the preparation of shikimic acid stock solution, uncertainty associated with quantification using a calibration curve, and uncertainty associated with precision. The most important contribution to total uncertainty was the method precision. The expanded uncertainty (U) for different wine varieties was between 2.6 and 8.5%. The method was applied to determine the concentration of shikimic acid in different emerging wine varieties cultivated in Chile, such as Carmenère, Shiraz, and Pinot Noir, comparing them with classical varieties, such as Cabernet Sauvignon and Merlot. Shiraz wines presented lower shikimic acid concentrations (between 27 and 86 mg L−1 with U (k=2) = 2.6%) than Cabernet Sauvignon wines (between 41 and 142 mg L−1 with U (k=2) = 8.1%), but their concentrations were higher than found in Merlot (from 9 to 41 mg L−1 with U (k=2) = 4.3%) and Carmenère wines (between 7 and 49 mg L−1 with U (k=2) = 5.8%). Pinot Noir was the variety with the lowest concentration of this acid (7–14 mg L−1 with U (k=2) = 8.5%).

Near-infrared spectroscopy (NIRS) has been widely used in the pharmaceutical field because of its ability to provide quality information about drugs in near-real time. In practice, however, the NIRS technique requires construction of multivariate models in order to correct collinearity and the typically poor selectivity of NIR spectra. In this work, a new methodology for constructing simple NIR calibration models has been developed, based on the spectrum for the target analyte (usually the active principle ingredient, API), which is compared with that of the sample in order to calculate a correlation coefficient. To this end, calibration samples are prepared spanning an adequate concentration range for the API and their spectra are recorded. The model thus obtained by relating the correlation coefficient to the sample concentration is subjected to least-squares regression. The API concentration in validation samples is predicted by interpolating their correlation coefficients in the straight calibration line previously obtained. The proposed method affords quantitation of API in pharmaceuticals undergoing physical changes during their production process (e.g. granulates, and coated and non-coated tablets). The results obtained with the proposed methodology, based on correlation coefficients, were compared with the predictions of PLS1 calibration models, with which a different model is required for each type of sample. Error values lower than 1–2% were obtained in the analysis of three types of sample using the same model; these errors are similar to those obtained by applying three PLS models for granules, and non-coated and coated samples. Based on the outcome, our methodology is a straightforward choice for constructing calibration models affording expeditious prediction of new samples with varying physical properties. This makes it an effective alternative to multivariate calibration, which requires use of a different model for each type of sample, depending on its physical presentation.

A novel on-line preconcentration method based on liquid–liquid (L–L) extraction with room temperature ionic liquids (RTILs) coupled to flame atomic absorption spectrometry (FAAS) was developed for cadmium determination in plastic food packaging materials. The methodology is based on the complexation of Cd with 2-(5-bromo-2-pyridylazo)-5-diethylaminophenol (5-Br-PADAP) reagent after sample digestion followed by extraction of the complex with the RTIL 1-butyl-3-methylimidazolium hexafluorophosphate ([C4mim][PF6]). The mixture was loaded into a flow injection analysis (FIA) manifold and the RTIL rich-phase was retained in a microcolumn filled with silica gel. The RTIL rich-phase was then eluted directly into FAAS. A enhancement factor of 35 was achieved with 20 mL of sample. The limit of detection (LOD), obtained as IUPAC recommendation, was 6 ng g−1 and the relative standard deviation (R.S.D.) for 10 replicates at 10 μg L−1 Cd concentration level was 3.9%, calculated at the peak heights. The calibration graph was linear and a correlation coefficient of 0.9998 was achieved. The accuracy of the method was evaluated by both a recovery study and comparison of results with direct determination by electrothermal atomic absorption spectrometry (ETAAS). The method was successfully applied for Cd determination in plastic food packaging materials and Cd concentrations found were in the range of 0.04–10.4 μg g−1.

An HPLC method for the determination of dexamethasone, dexamethasone sodium phosphate and chloramphenicol in presence of each other in pharmaceutical preparations has been developed using a Shim-Pack CLC-ODS column (6.0 × 150 mm2). These analytes were separated under isocratic conditions. Various chromatographic parameters including linearity, precision and accuracy have been evaluated. The method was found to be suitable for analysis of these drug substances in presence of each other. The run time was less than 15 min. This method is suitable for application to various dosage forms.