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Methods to assess the authenticity and traceability of wines have been extensively studied as enhancers of food quality, allowing producers to obtain market recognition and premium prices. Among analytical techniques, the volatilome profile attained by gas chromatography coupled with mass spectrometry is acquiring more and more attention by the scientific community, together with the use of chemometrics

The volatilome profile of three varieties of blanc wines from the Collio area (namely Ribolla Gialla, Malvasia and Friulano) between Italy and Slovenia, was determined by head space-solid phase micro extraction-gas chromatography-mass spectrometry, enhancing the carbonyl compounds identification with O-(2, 3, 4, 5, 6-pentafluorobenzyl)-hydroxylamine with the aim of identifying the autochthonous Friulano variety.

A two-step chemometric approach based on an unsupervised technique (PCA) followed by a supervised one (PLS-DA) allowed to identify possible markers for discriminating the Friulano Collio variety from the others, in particular two chemical classes were identified by PCA (ketones and long chain esters). PLS-DA showed 87% accuracy in classification. A correct classification (i.e. non-Friulano Collio) of a group of wines obtained from the same grape variety but produced in an extra-Collio area was obtained as well. The results confirmed the benefits of using a derivatization step prior to volatile organic compounds analysis.

Among methods to assess the authenticity and traceability of wines, volatilome profile of wines determined by head space-solid phase micro extraction-gas chromatography-mass spectrometry, enhanced by the carbonyl compound identifications with O-(2, 3, 4, 5, 6-pentafluorobenzyl)-hydroxylamine, may have a key role in conjunction with chemometrics and, in particular with principal component analysis and partial least square discriminant analysis.

Among methods to assess the authenticity and traceability of Friulano wine, volatilome profile of wines determined by head space-solid phase micro extraction-gas chromatography-mass spectrometry, enhanced by the carbonyl compound identifications with O-(2, 3, 4, 5, 6-Pentafluorobenzyl)Hydroxylamine hydrochloride, may have a key role in conjunction with chemometrics.

Few works investigated both wine traceability with a volatilome enhancer and chemometrics of the Friulano wine variety obtaining such an improvement in this wine variety discrimination.

Consumption of game meat is growing when compared to other meats. It is susceptible to adulteration because of its cost and availability. Spectroscopy may lead to rapid methodologies for detecting adulteration. The purpose of this study is to detect the adulteration of wild fallow deer (Dama dama) meat with domestic goat (G) (Capra aegagrus hircus) meat, for samples stored for different periods of time using Fourier transform infrared (FTIR) spectroscopy coupled with chemometric.

Meat was cut and mixed in different percentages, transformed into mini-burgers and stored at 3°C from 12 to 432 h and periodically examined for FTIR, pH and microbial analysis. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were applied to detect adulteration.

The PCA model, applied to the spectral region from 1,138 to 1,180, 1,314 to 1,477, 1,535 to 1,556 and from 1,728 to 1,759 cm⁻¹, describes the adulteration using four principal components which explained 95 per cent of variance. For the levels of Adulteration A1 (pure meat), A2 (25 and 50 %w/wG) and A3 (75 and 100 %w/wG) for an external set of samples, the correlation coefficients for prediction were 0.979, 0.941 and 0.971, and the room mean square error were 8.58, 12.46 and 9.47 per cent, respectively.

The PLS-DA model predicted the adulteration for an external set of samples with high accuracy. The proposed method has the advantage of allowing rapid results, despite the storage time of the adulterated meat. It was shown that FTIR combined with chemometrics can be used to establish a methodology for the identification of adulteration of game meat, not only for fresh meat but also for meat stored for different periods of time.

The purpose of this paper is to guide the choice of consumers, putting on the label an additional claim, which can provide more information on the sensory profile and the nutritional and preservation features of the marketed extra virgin olive oil.

In order to define the concept of global quality, the following parameters were considered: fruity, bitter, pungency, 1-penten-3-one, phenolic substances, tocopherols, peroxide value, free acidity, palmitic acid, stearic acid oleic acid linoleic acid, and the campesterol/stigmasterol ratio. The study was carried out on 143 commercial extra virgin olive oils.

The Global Quality Index was calculated as the square root of the sum of the squares of the individual local indices, according to three different algorithms. The computation obtained was recognised by chemometric analysis.

A legislative amendment on the labelling could be proposed through an additional claim that safeguards the consumers on the health profile, inducing them to a more targeted purchase.

Three different global quality levels “excellent”, “good”, and “sufficient” have been determined. This clustering has also been recognised with a statistical approach. Since in the market, consumers can find extra virgin olive oils of different overall quality levels, it is possible to guide the choice of customers through an additional claim on the label, able to give more information on the sensory profile and the nutritional and preservation features of the product.

The purpose of this paper is to predict the aquatic toxicity (LC50) of 92 substituted benzenes derivatives in Pimephales promelas.

Quantitative structure-activity relationship analysis was performed on a series of 92 substituted benzenes derivatives using multiple linear regression (MLR), artificial neural network (ANN) and support vector machines (SVM) methods, which correlate aquatic toxicity (LC50) values of these chemicals to their structural descriptors. At first, the entire data set was split according to Kennard and Stone algorithm into a training set (74 chemicals) and a test set (18 chemical) for statistical external validation.

Models with six descriptors were developed using as independent variables theoretical descriptors derived from Dragon software when applying genetic algorithm – variable subset selection procedure.

The values of Q2 and RMSE in internal validation for MLR, SVM, and ANN model were: (0.8829; 0.225), (0.8882; 0.222); (0.8980; 0.214), respectively and also for external validation were: (0.9538; 0.141); (0.947; 0.146); (0.9564; 0.146). The statistical parameters obtained for the three approaches are very similar, which confirm that our six parameters model is stable, robust and significant.

Analytical Abstracts is a valuable literature tool for information scientists and chemists. It became available on CDROM two years ago. This article will show how to search the CDROM version in detail by working through five worked examples. Between them, these examples will illustrate most of the features available on the disc.

The purpose of this paper is to predict the retention times of 84 pesticides or toxicants.

Quantitative structure – retention relationship analysis was performed on a set of 84 pesticides or toxicants using a hybrid approach genetic algorithm/multiple linear regression (GA/MLR).

A model with six descriptors was developed using as independent variables. Theoretical descriptors derived from Spartan and Dragon softwares when applying GA/MLR approach.

A six parameter linear model developed by GA/MLR, with R² of 90.54, Q² of 88.15 and S of 0.0381 in Log value. Several validation techniques, including leave-many-out cross-validation, randomization test, and validation through the test set, illustrated the reliability of the proposed model. All of the descriptors involved can be directly calculated from the molecular structure of the compounds, thus the proposed model is predictive and could be used to estimate the retention times of pesticides or toxicants.

Within the abundant and not always unanimous body or research on conceptual and methodological approaches to consumer value in services, there are two areas of relative consensus: the multidimensional nature of value (intra-variable approach) and the existence of causal relations with other constructs (inter-variable approach). This work aims to contribute additional knowledge in both areas, with a joint approach in a structural model tested for hospitality services.

The study proposes four scales of intrinsic values (entertainment, aesthetics, ethics and spirituality as relaxation), based on Holbrook’s (1999) value typology, and a casual model to be used to measure the relationships between these four values and overall perceived value, satisfaction and loyalty. The model is tested with PLS on a sample of 585 hotel guests on the island of Sardinia (Italy).

The psychometric properties of all four value scales, created ad hoc, are tested and approved. Results on the causal model show contrasted links on the intra-variable approach, entertainment, aesthetics and spirituality (measured as relaxation), are positive antecedents of perceived value, while the path ethics-overall value is not confirmed. The value–satisfaction–loyalty chain is fully confirmed, with strong linkages.

The authors acknowledge the use of a convenience sample, of mainly leisure tourists.

The implications for managers are derived on the need of considering extra drivers (intrinsic and therefore fully experiential) of satisfaction and loyalty.

Research on value has been qualified as not univocal and controversial. This study adds knowledge on the use of four less common value types (intrinsic ones) and sheds light on their nature as antecedents of the well-known value–satisfaction–loyalty chain.

In the fertile line of research on consumer value from the services literature, a gap exists between theoretical and empirical knowledge, in particular regarding Holbrook’s conceptual value framework. The purpose of this paper is to find construct validity for a multidimensional value scale based on Holbrook’s proposal.

Based on a literature review, a qualitative phase, and consultation with an expert, eight value scales (efficiency, service quality, play, aesthetics, status, esteem, ethics, and escapism as an adaptation of spirituality) are tested on a sample of 585 hotel customers and are further analyzed with simple and partial correlations, multiple regressions, and structural modeling.

Following the literature on the merits of Holbrook’s value typology, results are presented in three concatenated phases: validation of Holbrook’s eight value scales corresponding to his eight value types; interrelationships between these value types showing a predominance of the extrinsic-intrinsic and self-other dimensions; and construction of six indices based on the 2×2×2 matrix (self, other, extrinsic, intrinsic, active, and reactive) and a value index as a higher-order representation. The results support Holbrook’s typology, thereby supporting construct validity for the multidimensional scales.

Implications for further conceptual research on value are presented. Meanwhile, the empirical study is context-specific, i.e. related to a hospitality experience.

Although Holbrook’s typology has gained widespread attention, to the best of the authors’ knowledge, no previous research has tested all eight value types simultaneously in the same empirical work.

The purpose of this paper is to propose a predictive model that could replace lawyers’ annual performance rankings and inform talent management (TM) in law firms.

Eight years of performance rankings of a sample of 140 lawyers from one law firm are used. Artificial neural networks (ANNs) are used to model and simulate performance rankings over time. Multivariate regression analysis is used to compare with the non-linear networks.

With a lag of one year, performance ranking changes are predicted by the networks with an accuracy of 71 percent, over performing regression analysis by 15 percent. With a lag of two years, accuracy is reduced by 4 percent.

This study contributes to the literature of TM in law firms and to predictive research. Generalizability would require replication with broader samples.

Neural networks enable extended intervals for performance rankings. Reducing the time and effort spent benefits partners and lawyers alike, who can instead devote time to in-depth feedback. Strategic planning, early identification of the most talented and avenues for tailored careers become open.

This study pioneers the use of ANNs in law firm TM. The method surpasses traditional static study of performance through its use of non-linear simulation and prediction modeling.

World imports of Italian sparkling wines fell by 9% in value and 5% in quantities. In view of this, the quality characterisation of these products is desirable to increase their market value and restore their global visibility.

For this purpose, in this paper, heavy metals (Cd, Co, Cr, Cu, Fe, Ga, Hf, Hg, Mn, Mo, Nb, Ni, Pb, Re, Sb, Sn, Ta, Th, Tl, U, W, V, Zn, Zr), rare Earth elements (REEs) (Ce, Dy, Er, Eu, Gd, Ho, La, Lu, Nd, Pr, Sm, Tb, Tm, Yb) and isotopes ratio (208Pb/206Pb, 207Pb/206Pb, 206Pb/204Pb, 208Pb/207Pb, 87Sr/86Sr) were analysed in Italian sparkling wines with Protected Designation of Origin (PDO) certification by High Resolution Inductively Coupled Plasma Mass Spectrometry (HR-ICP-MS) and MultiCollector Inductively Coupled Plasma Mass Spectrometer (MC-ICP-MS). The samples were produced in the Veneto region, and they were compared to white and red wines from the same area.

Sparkling wines present a characteristic elemental pattern compared to white and red ones, with lower content of heavy metals and higher content in REEs. The ratio 87Sr/86Sr resulted in a powerful micro-scale geographical origins marker while Pb ratios as winemaking process one, both useful to prevent possible frauds. Multivariate data analyses, such as PCA and PLS-DA, were used to develop a model of recognition of Venetian sparkling wines.

The good classification of sparkling wines was achieved (95%), proving the suitable use of these analytes as markers for recognising sparkling wines and their geographical origin verification. To the best of the authors’ knowledge, this is the first study investigating heavy metals, REEs and isotopes in Venetian sparkling wine for their recognition.