RESUMEN
The plastics used in drug packaging systems and medical devices are composed of homologous polymers and generally contain additives such as antioxidants, plasticizers and others, to improve their physicochemical properties. However, these additives have potential drawbacks due to possible migration or leaching towards the drug product. Leaching can cause a change in the chemical composition of the drug which, in turn, could modify its therapeutic action and, in some cases, its organoleptic properties. Leachables may also be considered a health hazard due to their inherent toxicological properties. The analytical characterization (detection, identification, typification/qualification and quantification) of leachable substances is mandatory and this information must be included in the application dossier for the drug before it can receive regulatory approval. The main aim of this paper is to collect and contextualise the reported analytical approaches for characterising and/or controlling organic leachables from plastic materials in contact with drugs. We also describe the state of the art of leachables in conjunction with a valuable, broad-based compilation of directives and guidelines. We end by presenting an updated collection of leachables both gas and liquid chromatography studies as separation techniques over the last eight years. We decided to focus our review exclusively on organic leachables as there is already a wide body of research on inorganic impurities.
Asunto(s)
Contaminación de Medicamentos , Embalaje de Medicamentos , Plásticos/química , Técnicas de Química Analítica , Contaminación de Medicamentos/prevención & control , Preparaciones FarmacéuticasRESUMEN
BACKGROUND: The organoleptic quality of virgin olive oil depends on positive and negative sensory attributes. These attributes are related to volatile organic compounds and phenolic compounds that represent the aroma and taste (flavour) of the virgin olive oil. The flavour is the characteristic that can be measured by a taster panel. However, as for any analytical measuring device, the tasters, individually, and the panel, as a whole, should be harmonized and validated and proper olive oil standards are needed. RESULTS: In the present study, multivariate approaches are put into practice in addition to the rules to build a multivariate control chart from chromatographic volatile fingerprinting and chemometrics. Fingerprinting techniques provide analytical information without identify and quantify the analytes. This methodology is used to monitor the stability of sensory reference materials. CONCLUSION: The similarity indices have been calculated to build multivariate control chart with two olive oils certified reference materials that have been used as examples to monitor their stabilities. This methodology with chromatographic data could be applied in parallel with the 'panel test' sensory method to reduce the work of sensory analysis. © 2018 Society of Chemical Industry.
Asunto(s)
Cromatografía/normas , Aromatizantes/química , Análisis Multivariante , Aceite de Oliva/química , Compuestos Orgánicos Volátiles/química , Cromatografía/estadística & datos numéricos , Humanos , Aceite de Oliva/análisis , GustoRESUMEN
BACKGROUND: Virgin olive oil is the only food product for which sensory analysis is regulated to classify it in different quality categories. To harmonize the results of the sensorial method, the use of standards or reference materials is crucial. The stability of sensory reference materials is required to enable their suitable control, aiming to confirm that their specific target values are maintained on an ongoing basis. Currently, such stability is monitored by means of sensory analysis and the sensory panels are in the paradoxical situation of controlling the standards that are devoted to controlling the panels. RESULTS: In the present study, several approaches based on similarity analysis are exploited. For each approach, the specific methodology to build a proper multivariate control chart to monitor the stability of the sensory properties is explained and discussed. CONCLUSION: The normalized Euclidean and Mahalanobis distances, the so-called nearness and hardiness indices respectively, have been defined as new similarity indices to range the values from 0 to 1. Also, the squared mean from Hotelling's T2 -statistic and Q2 -statistic has been proposed as another similarity index. © 2018 Society of Chemical Industry.
Asunto(s)
Análisis de los Alimentos/normas , Aceite de Oliva/química , Análisis de los Alimentos/métodos , Frutas/química , Humanos , Análisis Multivariante , Olea/química , Aceite de Oliva/normas , Estándares de Referencia , GustoRESUMEN
Comprehensive two-dimensional gas chromatography (GC × GC) is the most effective multidimensional separation technique for in-depth investigations of complex samples of volatiles (VOC) in food. However, each analytical run produces dense, multi-dimensional data, so elaboration and interpretation of chemical information is challenging. This study exploits recent advances of GC × GC-MS chromatographic fingerprinting to study VOCs distributions from Extra Virgin Olive Oil (EVOO) samples of a single botanical origin (Picual), cultivated in well-defined plots in Granada (Spain), and harvested at different maturation stages. A new integrated work-flow, fully supported by dedicated and automated software tools, combines untargeted and targeted (UT) approaches based on peak-region features to achieve the most inclusive fingerprinting. Combined results from untargeted and targeted methods are consistent, reliable, and informative on discriminant features (analytes) correlated with optimal ripening of olive fruits and sensory quality of EVOOs. The great flexibility of the UT fingerprinting here adopted enables retrospective analysis with great confidence and provides data to validate the transferability of ripening indicators ((Z)-3-hexenal, (Z)-2-hexenal, (E)-2-pentenal, nonanal, 6-methyl-5-hepten-2-one, octane) to external samples sets. Direct image comparison, based on visual features, also is investigated for quick and effective pair-wise investigations. Its implementation with reliable metadata generated by UT fingerprinting confirms the maturity of 2D data elaboration tools and makes advanced image processing a real perspective.
Asunto(s)
Aceite de Oliva/química , Compuestos Orgánicos Volátiles/aislamiento & purificación , Cromatografía de Gases , Cromatografía de Gases y Espectrometría de Masas , Microextracción en Fase Sólida , Compuestos Orgánicos Volátiles/químicaRESUMEN
Fingerprinting methods describe a variety of analytical methods that provide analytical signals related to the composition of foodstuffs in a non-selective way such as by collecting a spectrum or a chromatogram. Mathematical processing of the information in such fingerprints may allow the characterisation and/or authentication of foodstuffs. In this context, the particular meaning of 'fingerprinting', in conjunction with 'profiling', is different from the original meanings used in metabolomics. This fact has produced some confusion with the use of these terms in analytical papers. Researchers coming from the metabolomic field could use 'profiling' or 'fingerprinting' on a different way to researchers who are devoted to food science. The arrival of an eclectic discipline, named 'foodomics' has not been enough to allay this terminological problem, since the authors keep on using the terms with both meanings. Thus, a first goal of this tutorial is to clarify the difference between both terms. In addition, the chemical approaches for food authentication, i.e., chemical markers, component profiling and instrumental fingerprinting, have been described. A new term, designated as 'food identitation', has been introduced in order to complete the life cycle of the chemical-based food authentication process. Chromatographic fingerprinting has been explained in detail and some strategies which could be applied has been clarified and discussed. Particularly, the strategies for chromatographic signals acquisition and chromatographic data handling are unified in a single framework. Finally, an overview about the applications of chromatographic (GC and LC) fingerprints in food authentication using different chemometric techniques has been included.
Asunto(s)
Análisis de los Alimentos/métodos , Cromatografía de Gases , Cromatografía Liquida , MetabolómicaRESUMEN
The aim of this article is to study tree-based ensemble methods, new emerging modelling techniques, for authentication of samples of olive oil blends to check their suitability for classifying the samples according to the type of oil used for the blend as well as for predicting the amount of olive oil in the blend. The performance of these methods has been investigated in chromatographic fingerprint data of olive oil blends with other vegetable oils without needing either to identify or to quantify the chromatographic peaks. Different data mining methods-classification and regression trees, random forest and M5 rules-were tested for classification and prediction. In addition, these classification and regression tree approaches were also used for feature selection prior to modelling in order to reduce the number of attributes in the chromatogram. The good outcomes have shown that these methods allow one to obtain interpretable models with much more information than the traditional chemometric methods and provide valuable information for detecting which vegetable oil is mixed with olive oil and the percentage of oil used, with a single chromatogram.
Asunto(s)
Minería de Datos/métodos , Contaminación de Alimentos/análisis , Aceites de Plantas/química , Cromatografía/métodos , Análisis Discriminante , Aceite de OlivaRESUMEN
Main goals of the present work were to develop authentication models based on liquid and gas chromatographic fingerprinting of triacylglycerols (TAGs) from palm oil of different geographical origins in order to compare them. For this purpose, a set of palm oil samples were collected from different continents: South eastern Asia, Africa and South America. For the analysis of the information in these fingerprint profiles, a pattern recognition technique such as partial least square discriminant analysis (PLS-DA) was applied to discriminate the geographical origin of these oils, at continent level. The liquid chromatography, coupled to a charged aerosol detector, (HPLC-CAD) TAGs separation was optimized in terms of mobile phase composition and by means of a solid silica core column. The gas chromatographic method with a mass spectrometer was applied under high temperature (HTGC-MS) in order to analyze the intact TAGs. Satisfactory chromatographic resolution within a short total analysis time was achieved with both chromatographic approaches and without any prior sample treatment. The rates of successful in prediction of the geographical origin of the 85 samples varied between 70% and 100%.
Asunto(s)
Aceites de Plantas , Triglicéridos/aislamiento & purificación , África , Asia Sudoriental , Cromatografía Líquida de Alta Presión , Análisis Discriminante , Cromatografía de Gases y Espectrometría de Masas , Análisis de los Mínimos Cuadrados , Aceite de Palma , Aceites de Plantas/química , Aceites de Plantas/clasificación , América del SurRESUMEN
The characterization and authentication of fats and oils is a subject of great importance for market and health aspects. Identification and quantification of triacylglycerols in fats and oils can be excellent tools for detecting changes in their composition due to the mixtures of these products. Most of the triacylglycerol species present in either fats or oils could be analyzed and identified by chromatographic methods. However, the natural variability of these samples and the possible presence of adulterants require the application of chemometric pattern recognition methods to facilitate the interpretation of the obtained data. In view of the growing interest in this topic, this paper reviews the literature of the application of exploratory and unsupervised/supervised chemometric methods on chromatographic data, using triacylglycerol composition for the characterization and authentication of several foodstuffs such as olive oil, vegetable oils, animal fats, fish oils, milk and dairy products, cocoa and coffee.
Asunto(s)
Grasas/análisis , Análisis de los Alimentos/métodos , Aceites/análisis , Triglicéridos/análisis , Cromatografía de Gases , Cromatografía Líquida de Alta Presión , Cromatografía en Capa Delgada , Análisis Discriminante , Espectrometría de Masas , Análisis de Componente PrincipalRESUMEN
A reliable procedure for the identification and quantification of the adulteration of olive oils in terms of blending with other vegetable oils (sunflower, corn, seeds, sesame and soya) has been developed. From the analytical viewpoint, the whole procedure relies only on the results of the determination of the triacylglycerol profile of the oils by high temperature gas chromatography-mass spectrometry. The chromatographic profiles were pre-treated (baseline correction, peak alignment using iCoshift algorithm and mean centering) before building the models. At first, a class-modeling approach, Soft Independent Modeling of Class Analogy (SIMCA) was used to identify the vegetable oil used blending. Successively, a separate calibration model for each kind of blending was built using Partial Least Square (PLS). The correlation coefficients of actual versus predicted concentrations resulting from multivariate calibration models were between 0.95 and 0.99. In addition, Genetic algorithms (GA-PLS), were used, as variable selection method, to improve the models which yielded R(2) values higher than 0.90 for calibration set. This model had a better predictive ability than the PLS without feature selection. The results obtained showed the potential of this method and allowed quantification of blends of olive oil in the vegetable oils tested containing at least 10% of olive oil.
Asunto(s)
Contaminación de Alimentos/análisis , Cromatografía de Gases y Espectrometría de Masas/métodos , Aceites de Plantas/química , Triglicéridos/análisis , Aceite de Oliva , Control de CalidadRESUMEN
The ability of multivariate analysis methods such as hierarchical cluster analysis, principal component analysis and partial least squares-discriminant analysis (PLS-DA) to achieve olive oil classification based on the olive fruit varieties from their triacylglycerols profile, have been investigated. The variations in the raw chromatographic data sets of 56 olive oil samples were studied by high-temperature gas chromatography with (ion trap) mass spectrometry detection. The olive oil samples were of four different categories ("extra-virgin olive oil", "virgin olive oil", "olive oil" and "olive-pomace" oil), and for the "extra-virgin" category, six different well-identified olive oil varieties ("hojiblanca", "manzanilla", "picual", "cornicabra", "arbequina" and "frantoio") and some blends of unidentified varieties. Moreover, by pre-processing methods of chemometric (to linearise the response of the variables) such as peak-shifting, baseline (weighted least squares) and mean centering, it was possible to improve the model and grouping between different varieties of olive oils. By using the first three principal components, it was possible to account for 79.50% of the information on the original data. The fitted PLS-DA model succeeded in classifying the samples. Correct classification rates were assessed by cross-validation.
Asunto(s)
Cromatografía de Gases y Espectrometría de Masas/métodos , Aceites de Plantas/análisis , Aceites de Plantas/clasificación , Triglicéridos/análisis , Análisis Discriminante , Cromatografía de Gases y Espectrometría de Masas/estadística & datos numéricos , Análisis Multivariante , Aceite de Oliva , Análisis de Componente PrincipalRESUMEN
A pressurised liquid extraction (PLE) method for extraction and quantification of total fat and oil in bread and derivatives products has been proposed. Parameters implied in the extraction process; such us temperature, static time, number of extraction cycles, purge time and flush volume; have been optimised using a formal methodology based on statistical experimental design in order to obtain the best results. Moreover, this method has been validated using homemade bread elaborated in the laboratory which contained 9.64 g of olive oil in 100g dry weight. The production and use of an "ad hoc" in-house reference material is just one of the most relevant aspects of this study. The uncertainty estimation has been carried out taking into account all the uncertainty components of the process and it was stated as 4.2%. Finally, the proposed method has been applied to six different Spanish bread derivatives products with different olive oil contents (5-20%) to determine the fat content.