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In recent years, the variety and volume of data acquired by modern analytical instruments in order to conduct a better authentication of food has dramatically increased. Several pattern recognition tools have been developed to deal with the large volume and complexity of available trial data. The most widely used methods are principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), soft independent modelling by class analogy (SIMCA), k-nearest neighbours (kNN), parallel factor analysis (PARAFAC), and multivariate curve resolution-alternating least squares (MCR-ALS). Nevertheless, there are alternative data treatment methods, such as support vector machine (SVM), classification and regression tree (CART) and random forest (RF), that show a great potential and more advantages compared to conventional ones. In this paper, we explain the background of these methods and review and discuss the reported studies in which these three methods have been applied in the area of food quality and authenticity. In addition, we clarify the technical terminology used in this particular area of research., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Second-order data acquired using liquid chromatography coupled to a diode array detector were used to classify extra virgin olive oils samples according to their cultivars. The chromatographic fingerprints from the epoxidised fraction were obtained using normal-phase liquid chromatography. To reduce the data matrices two strategies were employed: (1) multivariate curve resolution-alternating least squares (MCR-ALS) and (2) a new strategy proposed in this work based on the fusion of the mean data profiles in both spectral and time domains. Several conventional chemometric tools were then applied to both raw and reduced data: principal component analysis (PCA), partial least-squares-discriminant analysis (PLS-DA), soft independent modelling of class analogies (SIMCA) and n-way partial least-squares-discriminant analysis (NPLS-DA). Furthermore, an emergent multivariate classification method known as random forest (RF) has been first applied to second-order data. It was shown that RF is more efficient than conventional tools. Indeed, the obtained sensibility, specificity and accuracy are 1.00, 0.92 and 0.95 respectively; these performance metrics are significantly better than the values found for the other methods., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: There are two products in which infliximab is the active pharmaceutical ingredient. These are Remicade ® (INF; reference product) and Remsima™/Inflectra™ (CT-P13; infliximab biosimilar). Remsima™/Inflectra™ are bioidentical products. Different recommendations have been made for the clinical solutions of each brand (Remicade ® or Remsima™/Inflectra™) despite the manufacturer of the biosimilar claiming high levels of similarity to the innovator., Objective: The objective of this study was to assess and compare stability against degradation and over time of different clinical infliximab solutions prepared from Remicade ® and from Remsima™/Inflectra™ using a suitable set of characterization methods in line with the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) recommendations., Methods: Reconstituted solutions of INF and CT-P13 and dilutions as used in hospital were stored in glass vials (10 and 2 mg/mL) or in polyolefin infusion bags (0.4 mg/mL) refrigerated between 2 and 8 °C for 2 weeks. Regarding the physicochemical properties, the distribution of the particulates were studied over a range of 0.001-1 µm by dynamic light scattering (DLS) and oligomers up to 8 monomer were analyzed by native size-exclusion ultra-high-performance liquid chromatography with ultraviolet (UV)-visible detection coupled to (native) mass spectrometry (SE/UHPLC-UV-(native) MS); mass spectrometry was also used to evaluate natural aggregates and isoform profile; DLS was also employed to detect gross conformational changes by tracking the hydrodynamic radius (HR). The secondary structure of the proteins was studied by far UV circular dichroism (CD). The tertiary structure was investigated by intrinsic tryptophan fluorescence (IT-F). Reverse-phase ultra-high-performance liquid chromatography with UV detection (RP/UHPLC-UV) was used to analyze intact INF and CT-P13 for quantification purposes. Functionality was evaluated via the biological activity measured by the extension of the immunological reaction of the INF and the CT-P13 with its antigen, i.e., the tumor necrosis factor-α by enzyme-linked immunosorbent assay (ELISA)., Results: The stress applied to INF and CT-P13 solutions showed similar levels of aggregate formation, structural variation, and chemical modifications. The only noteworthy difference between INF and CT-P13 was detected in their behavior to freeze-thaw cycles, in which CT-P13 showed slightly more robustness. INF and CT-P13 showed identical CD spectra, similar to those reported for IgG1 in which there is dominance in β sheet secondary structures; this typical conformation remained unmodified over time in INF and CT-P13. No significant changes were detected in the tertiary structure and no aggregates process was noticed over the time studied. Polydispersity slightly increased for the most concentrated solutions, while there were no meaningful differences in the HR in the solutions over time. The concentration of INF and CT-P13 also remained constant. Differences in the native isoform MS profile were detected, as expected by the different glycosylation pattern, with no important modification over time. Functionality was maintained over the test period (60 days) and was similar in all the solutions tested, with no differences between INF and biosimilar solutions., Conclusions: High levels of similarity were noticed in the behavior of INF and CT-P13 when subjected to stress. When stored refrigerated at between 2 and 8 °C and prepared as normally used in the hospital pharmacy, all solutions showed physicochemical and functional stability for all the concentrations tested and all containers, at least for the 14-day test period.

In this study, a specific sensory panel was created and qualified for sensory assessment of Spanish dry-cured ham. A strict control was carried out in order to recruit, select, train and qualify the assessors. At the beginning, 29 candidates to assessors were considered and at the end only 9 candidates satisfied the conditions required to be qualified as expert assessors of the sensory panel. Furthermore, the precision and trueness of each expert assessor were determined by the repeatability index (Ri a ), and intermediate precision index (IPi a ), and the deviation index (Di a ). In the same way, the panel precision was also evaluated by a proper repeatability index (Ri p ) and an intermediate precision (IPi p ) index. The provided results were satisfactory and the sensory panel was correctly validated. Currently, the sensory panel continues performing sensory analysis of dry-cured ham., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Monoclonal antibodies (mAbs) are one of the most important types of biopharmaceutics and have proved enormously successful in the treatment of cancers and autoimmune diseases. In this paper, we present a fast, straightforward reversed phase (RP)UHPLC-UV-(HESI/Orbitrap) MS method for the separation and identification of five of the most commonly used mAbs, i.e. bevazizumab (BEV), cetuximab (CTX), infliximab (INF), rituximab (RTX) and trastuzumab (TTZ) in mixtures. The RP mAbs separation was performed in a divinylbenzene-based monolithic column, after statistical design of the experiments with a novel approach for optimizing chromatographic conditions called the heteroscedasticity function. Results led us to split the initial mixture of five mAbs into two mixtures with four mAbs each, one containing RTX and the other TTZ. The method was validated for quantification using the signal from the UV detector and identification by (HESI-Orbitrap)MS. Direct MS characterization of the intact isoform profile of each mAb was also obtained. Advantages and disadvantages of the use of trifluoroacetic acid or formic acid as ion pairing agents for mass spectrometric analysis and chromatographic separation are discussed. Validation was performed using an internal protocol based on well-known international guidelines such as the International Conference on Harmonization (ICH) guideline, the US Food and Drugs Administration (FDA) guideline and the United Stated Pharmacopeia (USP) guideline. Performance parameters such as linearity, accuracy (precision and trueness), detection limits, quantification limits and robustness were evaluated. Robustness was established by studying the total and one-sided effects of four selected variables: column temperature, trifluoroacetic acid content in the mobile phases, initial proportion of eluent B and gradient. The results indicated the suitability of this method for quantifying these five mAbs in mixtures, as well as its robustness, reproducibility and sensitivity., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The aim of the present study was to develop suitable and reliable method for quantification three of the most worldwide used therapeutic monoclonal antibodies (mAbs) -bevazizumab (BVZ), infliximab (INF) and trastuzumab (TTZ)- to be used in long-term stability studies. Reverse phase (RP) was selected by its greater sensibility and reproducibility comparing with other chromatographic modes. Then a high performance liquid chromatography with diode array detection (RP)HPLC/DAD method was checked. Since the three mAbs represent the active ingredient in the medicines in which they are formulated, the selected method was validated for each one in accordance with the International Conference on Harmonization (ICH) guidelines for pharmaceuticals for human use. Then method was validated in terms of linearity, accuracy, precision, (repeatability, intermediate precision) specificity (by forced degradation studies), robustness and system suitability. Spectral peak purity analysis strategy was used to test mAb degradations. Comparative study of the results indicated similar behavior for the three mAbs. Forced degradation studies also provided deep knowledge of these important bio-macromolecules. At last the method was successfully used to quantify BVZ, INF and TTZ in long-term stability studies performed under hospital conditions of use and they showed great stability regarding quantification during the time of the study., (Copyright © 2018 Elsevier B.V. All rights reserved.)

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 T 2 -statistic and Q 2 -statistic has been proposed as another similarity index. © 2018 Society of Chemical Industry., (© 2018 Society of Chemical Industry.)

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., (© 2018 Society of Chemical Industry.)

Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknès and Tyout (Morocco); and Priego de Córdoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H 3 O + , NO + and O 2 + as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90-100%) and prediction accuracy (96.70-100% accuracy for cross validation and 97.30-100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases)., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

A new method for differentiation of olive oil (independently of the quality category) from other vegetable oils (canola, safflower, corn, peanut, seeds, grapeseed, palm, linseed, sesame and soybean) has been developed. The analytical procedure for chromatographic fingerprinting of the methyl-transesterified fraction of each vegetable oil, using normal-phase liquid chromatography, is described and the chemometric strategies applied and discussed. Some chemometric methods, such as k-nearest neighbours (kNN), partial least squared-discriminant analysis (PLS-DA), support vector machine classification analysis (SVM-C), and soft independent modelling of class analogies (SIMCA), were applied to build classification models. Performance of the classification was evaluated and ranked using several classification quality metrics. The discriminant analysis, based on the use of one input-class, (plus a dummy class) was applied for the first time in this study., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.

A new analytical method for the quantification of olive oil and palm oil in blends with other vegetable edible oils (canola, safflower, corn, peanut, seeds, grapeseed, linseed, sesame and soybean) using normal phase liquid chromatography, and applying chemometric tools was developed. The procedure for obtaining of chromatographic fingerprint from the methyl-transesterified fraction from each blend is described. The multivariate quantification methods used were Partial Least Square-Regression (PLS-R) and Support Vector Regression (SVR). The quantification results were evaluated by several parameters as the Root Mean Square Error of Validation (RMSEV), Mean Absolute Error of Validation (MAEV) and Median Absolute Error of Validation (MdAEV). It has to be highlighted that the new proposed analytical method, the chromatographic analysis takes only eight minutes and the results obtained showed the potential of this method and allowed quantification of mixtures of olive oil and palm oil with other vegetable oils., (Copyright © 2016 Elsevier B.V. All rights reserved.)

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., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Cetuximab (CTX) is a potent chimeric mouse/human monoclonal antibody (mAb) approved worldwide for treatment of metastatic colorectal cancer. Among the various biological and physical analyses performed for full study on this biopharmaceutic, the determination of the concentration preparations throughout manufacturing and subsequent handling in hospital is particularly relevant. In the present work, the study and validation of a method for quantifying intact CTX by reverse-phase high-performance liquid chromatography with diode array detection ((RP)HPLC/DAD) is presented. With that end, we checked the performance of a chromatographic method for quantifying CTX and conducted a study to validate the method as stability-indicating in accordance with the International Conference on Harmonization guidelines (ICH) for biotechnological drugs; therefore, we evaluated linearity, accuracy, precision, detection and quantification limits, robustness and system suitability. The specificity of the method and the robustness of the mAb formulation against external stress factors were estimated by comprehensive chromatographic analysis by subjecting CTX to several informative stress conditions. As demonstrated, the method is rapid, accurate, and reproducible for CTX quantification. It was also successfully used to quantify CTX in a long-term stability study performed under hospital conditions.

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., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The authentication of packing oil from commercial canned tuna and other tuna-like fish species was examined by means of attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) and chemometrics. Using partial least squares discriminant analysis (PLS-DA), it was possible to differentiate olive oil from seed oils. Discrimination of olive oil from high-oleic sunflower oil was possible, despite the latter having a degree of unsaturation more similar to olive oil than to sunflower oil. However, in the samples analyzed, sunflower oil could not be differentiated clearly from those labeled with the generic term "vegetable oil". Furthermore, the authentication of extra virgin olive oil, although more difficult, could be achieved using ATR-FTIR spectroscopy. The method could be applied regardless of fish type, without interference from fish lipids., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

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.

Herein we present the development of a powerful CE-UV method able to detect and quantify an important number of phenolic acids in 13 varieties of avocado fruits at 2 ripening stages. All the variables involved in CE separation were exhaustively optimized and the best results were obtained with a capillary of 50 μm i.d. × 50 cm effective length, sodium tetraborate 40 mM at a pH of 9.4, 30 kV, 25 °C, 10s of hydrodynamic injection (0.5 psi) and UV detection at 254 nm. This optimal methodology was fully validated and then applied to different avocado samples. The number of phenolic acids determined varied from 8 to 14 compounds; in general, they were in concentrations ranging from 0.13 ppm to 3.82 ppm, except p-coumaric, benzoic and protocatechuic acids, which were found at higher concentrations. Principal component analysis (PCA) was applied to highlight the differences between varieties and ripening degrees, looking for the most influential analytes., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

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%., (© 2013 Elsevier B.V. All rights reserved.)

We studied the quantification of an intact therapeutic monoclonal antibody (mAb), rituximab (RTX), using (reversephase) high-performance liquid chromatography with diode array detection ((RP)HPLC/DAD). To this end, we developed a chromatographic method and validated it as stabilityindicating in accordance with the International Conference on Harmonization guidelines (ICH). A 300-Å C8 column (250 mm×4.6 mm, 5 μm) was used to perform the analysis, and the temperature was maintained at 70 °C. Although only one mAb was analyzed, it was necessary to apply a gradient to elute it with a complex organic mixture. Chromatograms were registered at several wavelengths, with λ =214 nm employed for quantification purposes. The method was developed to quantify marketed RTX under typical hospital administration conditions. Further dilution was avoided in order to prevent additional mAb modification, and in this way the method was shown to be linear from 60 to 5000 mg/L. The precision of the method (repeatability and intermediate precision, estimated as the relative standard deviation, RSD %), was less than 1.0 %. Accuracy, specificity, robustness, and system suitability were also evaluated as specified in the ICH guidelines.We conducted a comprehensive chromatographic analysis by submitting RTX to several informative stress conditions. These forced degradation studies were conducted for two reasons: to estimate the specificity of the method, and to evaluate the robustness of the mAb formulation against external stress factors when handling it in preparation for administration. Thus, we investigated the effects of acid, base, oxidation, ionic strength, temperature, and UV light. Although a slight modification to the intact mAb could not be distinguished chromatographically in the stress studies we conducted, the procedure proposed here to evaluate peak purity enabled us to detect it with a satisfactory level of confidence. The proposed method could therefore be considered stability-indicating for quantyfying the intact mAb since it is qualified to detect its degradation/modification. Finally, the method was used to evaluate RTX in a long-term stability study performed under hospital conditions of use.

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., (Copyright © 2012 Elsevier B.V. All rights reserved.)

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., (Copyright © 2012 Elsevier B.V. All rights reserved.)

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.

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., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Calibration is an operation whose main objective is to know the metrological status of a measurement system. Nevertheless, in analytical sciences, calibration has special connotations since it is the basis to do the quantification of the amount of one or more components (analytes) in a sample, or to obtain the value of one or more analytical parameters related with that quantity. Regarding this subject, the aim of analytical calibration is to find an empiric relationship, called measurement function, which permits subsequently to calculate the values of the amount (x-variable) of a substance in a sample, from the measured values on it of an analytical signal (y-variable). In this paper, the metrological bases of analytical calibration and quantification are established and, the different work schemes and calibration methodologies, which can be applied depending on the characteristic of the sample (analyte+matrix) to analyse, are distinguished and discussed. Likewise, the different terms and related names are clarified. A special attention has been paid to those analytical methods which use separation techniques, in relation with its effect on calibration operations and later analytical quantification.

A new strategy is proposed for verifying if recovery factor is constant and independent of the real analyte content of samples. A signal-recovery function has been developed on the basis of measurement of spiked test samples before and after a pre-treatment step and considering, as starting point, a recent IUPAC recommendation which distinguishes between two terms--recovery factor, R, and apparent recovery, R*. Apparent recovery includes recovery factor and a new recovery term proposed in a previous paper by the authors, named calibration recovery, R(C). The signal-recovery function is obtained directly from the measured analytical signals instead of from the concentrations, simplifying the calculations. A linear signal-recovery curve indicates that the recovery factor is constant in the analyte concentration range studied experimentally and, in this way, a single recovery factor can be calculated. The usefulness of the proposed method has been shown by quantification of the pesticide carbaryl by two different flow-injection analysis methods with chemiluminescent detection based on the luminol and TCPO systems. Good results were obtained from both methods.

The determination of stoichiometries and stability constants of complexes by means of UV-visible spectrophotometry applying traditional methods does not evaluate the quality of the values obtained, since the classic application of these methods does not provide coverage intervals. However, the use of chemometric techniques in different steps of the application of these methods makes it possible to obtain not only a real value of the characteristics of the complexes but a validation of such a value. In this paper a methodology is proposed that combines some traditional methods, three different regression models (LMSR, LSR and LSPR) and a small number of mathematical algorithms. This methodology is able to estimate, in a simple and rigorous way, the stoichiometry and stability constant of a complex and its corresponding uncertainties.

A new formal strategy in the multidimensional optimisation of the experimental variables affecting the chemiluminescence (CL) detection in flow injection analysis (FIA) is proposed here. The strategy implies several steps, being the most significant: selection of the variables to be studied and their experimental domain; use of a screening design to detect significant variables and interactions into the experimental region; study of the main effect of variables and second-order interactions; and finally application of a Draper-Lin small composite design (orthogonal) to obtain the optimum values of the significant variables. The methodology is applied to the determination of methylamine by FIA based on the use of the peroxyoxalate CL (PO-CL) reaction. Considering the high number of experiments required due to the different chemical and instrumental variables to be taken account and their adequate compatibility to obtain maximum sensitivity, the methodology offers a rigorous study of the main effects and interactions, achieving a reduction of experimental work.

Robustness experiments are performed in analytical chemistry to assess the behaviour of an analytical procedure under conditions slightly different from those of the experimental optimum. This work presents a study of robustness applied to a previously proposed fluorescent methodology using two replicated 2(7-4) saturated fractional factorial designs. A comparison is established between three different ways to test the significance of the effects of the variables involved on the response signal. Critical discussions about the most appropriate threshold to be introduced when testing for significance of the factors and the influence of the time necessary to carry out the experiments are included.

Sequential response surface methodology is a general procedure to re-optimize common analytical methods on the basis of the application of the response surface methodology and of a new approach to the steepest ascent method. This procedure, which is easy to apply, consists of estimating an analytical function relating the response with the experimental parameters by means of a second-degree polynomial. Thus, a 2nd order design covering the total experimental domain is used and when a maximum is obtained, the characteristics of the response surface are confirmed using a new design, which is obtained contracting the first one. In the proposed methodology, Box-Behnken designs are used because they offer advantages in comparison with second order designs more frequently used in the steepest ascent method (central composite designs), i.e. fewer experiments are needed, they are more efficient, they can be moved through the experimental domain and they can even be easily contracted or expanded.

Two methodologies have been proposed for a simple statistical estimation of the detection limits in microbore-HPLC and CE techniques. Due to the impossibility to measure the blank, by using the extrapolated or approximated expressions it is possible to obtain a straightforward approach of the detection limits from the study of the residuals of the calibration data set, avoiding tedious treatment of the signals. The utility of these expressions has been checked on the data from an experimental microbore HPLC system.