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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).

Sorbic (SOR) and benzoic (BEN) acids were determined in fruit juice samples by using a net analyte signal-based methodology named HLA/GO (an hybrid linear analysis presented by Goicoechea and Olivieri) applied to spectroscopic signals. The calibration set was built with several fruit juices in order to take into account the natural variability and concentrations of both analytes covering the range usually present in commercial samples. Relative errors of prediction (REP %) of 3.6 and 5.2% were calculated for SOR and BEN respectively. Several figures of merit were calculated-sensitivity, selectivity, analytical sensitivity, and limit of detection. The method is quantitative, with reasonably good recoveries and excellent precision (less than 1%). Wavelength selection was applied, based on the concept of net analyte signal regression, and it allowed us to improve the method performance in samples containing non-modelled interferences, e.g. fruit juices different to those used to build the calibration model.

This article reports on the first application of a modified version of the bilinear least-squares model to absorbance-pH second-order data recorded for complex samples. The latter are composed of fruit drink powders, where four different analytes and additional background components occur. The analytes are the common juice colorants tartrazine, yellow sunset, allura red and indigo carmine. The data have been measured after generating a double pH gradient within a flow injection system. The selected chemometric methodology adequately exploits the second-order advantage, needed to take into account the background interferents present in real samples. Due to severe spectral overlapping between the acid and basic forms of each of the colorants in the working pH range, other second-order multivariate calibration methods such as parallel factor analysis and multivariate curve resolution-alternating least-squares could not be successfully applied to the presently studied samples. Recoveries of 94.8, 104.7, 109.3 and 105.3% were obtained for yellow sunset, indigo carmine, allura red and tartrazine respectively in the real test samples.

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La necesidad de producir más alimentos ha llevado al aumento del uso de pesticidas, entre ellos glifosato, el cual es ampliamente empleado en la producción de soja transgénica. Esto ha implicado que crezcan los casos de intoxicaciones y contaminación de recursos naturales. Por tal motivo los entes gubernamentales han formulado instrucciones de manipulación y de descarte de los envases comerciales. El objetivo del presente trabajo fue evaluar la capacidad de Candida tropicalis LMFIQ 703 para disminuir la concentración de glifosato en el tercer enjuague de bidones y así reducir el riesgo de impacto ambiental adverso que producen los residuos de pesticida en los envases vacíos almacenados por largos periodos de tiempo. Se sembraron suspensiones de levadura sin adaptación, en soluciones de Credit® Amonio (Ingrediente activo: sal amónica de la N-fosfonometil glicina) con concentración conocida (similar a la del tercer enjuague). Se incubó a 28°C durante 28 días y se realizó el recuento microbiológico de colonias de levadura cada 7 días. La determinación de la concentración de glifosato se hizo por fluorimetría con calibración multivariada y HPLC. Las levaduras se mantuvieron viables durante todo el experimento, con una disminución inicial por adaptación y una concentración final similar a la inicial. Los resultados de la cuantificación de glifosato a través de fluorescencia y calibración multivariada, aprovechando la ventaja de segundo orden del algoritmo MCR-ALS resultaron comparables con los obtenidos por el método de referencia (HPLC). Se puede concluir que la biorremediación propuesta fue eficiente ya que la concentración de glifosato disminuyó un 39%.