Multivariate approaches for stability control of the olive oil reference materials for sensory analysis - part II: applications.

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.

Multivariate approaches for stability control of the olive oil reference materials for sensory analysis - part I: framework and fundamentals.

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.

Homogeneity assessment of reference materials for sensory analysis of liquid foodstuffs. The virgin olive oil as case study.

Sensory properties are critical characteristics that determine quality and can be evaluated by trained tasting panels. The panels function as multi-sensor measuring instrument and need the use of reference materials (RMs) for training. The homogeneity between units packaged from a batch of RM can be evaluated by gas chromatography coupled to flame ionization detection (GC-FID), using this instrumental technique as an alternative to sensory analysis. For this purpose, the fingerprint methodology is applied, taking into account that the homogeneity assessment will be based on evaluating the similarity between the fingerprints of the fraction of volatile organic compounds acquired from samples representative of the batch. The proposed methodology is applied with good results to evaluate the homogeneity of several RMs for sensory analysis of virgin olive oil samples, using similarity indices, control charts and exploratory analysis of multivariate data to observe the grouping RM and fingerprint regions representative of each defect.

Chromatographic fingerprinting: An innovative approach for food 'identitation' and food authentication - A tutorial.

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.

Combined untargeted and targeted fingerprinting with comprehensive two-dimensional chromatography for volatiles and ripening indicators in olive oil.

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.