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A new methodology is proposed to automate the monitoring of sulfonamide residues in milk samples. It combines a screening unit for the total amount of sulfonamide with capillary electrophoresis-mass spectrometry (CE-MS) equipment for processing the samples containing a detectable level of sulfonamide. The screening unit consists of continuous-flow system (CFS) to precipitate the proteins connected on-line to the CE-MS equipment, in which a common characteristic ion of all sulfonamides was monitored with the MS detector by flushing the sample through the capillary. The confirmatory method is based on the purification and preconcentration of sulfonamides in a CFS unit and posterior analysis by CE-MS. The sample treatment unit was also on-line connected to the CE-MS equipment. In order to increase sensitivity, the flow rate of the sheath liquid was diminished from 0.5 to 0.2 microL.min(-1) by increasing the content in water from 0 to 50% and the formic acid from 0.5 to 1.5% in this liquid and by applying an overimposed pressure of 5 mbar during the electrophoretic separation. The method allowed the analysis of 30 samples per hour.

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Two widely employed antimicrobials, benzoic and sorbic acids, were simultaneously determined in commercial orange juices employing a combination of a flow injection system with pH gradient generation, diode array spectrophotometric detection, and chemometric processing of the recorded second-order data. Parallel factor analysis and multivariate curve resolution-alternating least-squares were used for obtaining the spectral profiles of sample components and concentration profiles as a function of pH, including provisions for managing rank-deficient data sets. An appropriately designed calibration with a nine-sample set of binary mixtures of standards, coupled to the use of the second-order advantage offered by the applied chemometric techniques, allowed quantitation of the analytes in synthetic test samples and also in commercial orange juices, even in the presence of unmodeled interferents (with relative prediction errors of 8.7% for benzoic acid and 2.5% for sorbic acid). No prior separation or sample pretreatment steps were required. The comparison of results concerning commercial samples with a laborious reference technique yielded satisfactory statistical indicators (recoveries were 99.0% for benzoic acid and 101.4% for sorbic acid).

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