The Use of Image Analysis and Sensory Analysis for the Evaluation of Cultivar Differentiation of Freeze-Dried and Lacto-Fermented Beetroot (Beta vulgaris L.)

The aim of the research was to compare the possibility of distinguishing the cultivars of processed beetroots using image analysis technique and sensory evaluation. The differentiation of processed samples was tested for freeze-dried beetroot ‘Czerwona Kula’ and ‘Cylindra’, lacto-fermented beetroot ‘Czerwona Kula’ and ‘Cylindra’, freeze-dried lacto-fermented beetroot ‘Czerwona Kula’ and ‘Cylindra’. The textures from the images of quarters of root slices, as well as sensory attributes evaluated by expert sensory assessors, were determined. The differences in the means of selected textures from color spaces Lab, RGB and XYZ for different cultivars of raw and processed beetroots were observed. The raw beetroots ‘Czerwona Kula’ and ‘Cylindra’ were discriminated with the accuracy of up to 94.5% for models built based on selected texture from color space RGB. In the case of processed beetroots ‘Czerwona Kula’ and ‘Cylindra’, the accuracy reached 96% (color space Lab) for freeze-dried beetroots, 99% (color space Lab) for lacto-fermented beetroots, 98.5% (color space Lab) for freeze-dried lacto-fermented beetroots. In the case of sensory attributes, no statistically significant differences were observed between the beetroot samples.

The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples

In the present study, volatile compound analysis of olive oil samples belonging to ten Greek cultivars was carried out. A total of 167 olive oil samples collected from two consecutive harvest years were analyzed by Head Space-Solid Phase Microextraction-Gas Chromatography/Mass Spectrometry (HS-SPME-GC/MS). Volatile compound data were combined with chemometric methods (Multivariate Analysis of Variance (MANOVA) and Linear Discriminant Analysis (LDA)) with the aim not only to differentiate olive oils but also to identify characteristic volatile compounds that would enable differentiation of botanical origin (marker compounds). The application of Stepwise LDA (SLDA) effectively reduced the large number of statistically significant volatile compounds involved in the differentiation process, and thus, led to a set of parameters, the majority of which belong to compounds that are highly dependent on variety. In addition, the use of these marker compounds resulted in an increased correct classification rate (85.6%) using the cross-validation method indicating the validity of the model developed despite the use of a large number of dependent variables (cultivars).

Application of fluorescence spectroscopy using classical right angle technique in white wines classification

The potential of excitation - emission matrices (EEM) measurements using classical right angle technique, in conjunction with chemometrics, was prospected for white wine classification with respect to their cultivar and geographical origin. For this purpose, wines belonging to four cultivars (Chardonnay, Pinot Gris, Riesling and Sauvignon) from two different countries (Romania and France) were investigated. The excitation – emission matrices were statistically processed using parallel factor analysis (PARAFAC). According to Soft Independent Modeling Classification Analogy (SIMCA) model, for cultivar differentiation, only 3 out of 107 wine samples (1 Pinot Gris (Romania); 1 Riesling (Romania) and 1 Sauvignon (France)) were misclassified while for geographical origin assessment, only 2 wines (1 Romania and 1 France) were misclassified. This study demonstrates the potential of excitation – emission fluorescence matrices spectroscopy using the classical right angle technique in wine authentication, without sample dilution.

Measuring Thiols in Single Cultivar South African Red Wines Using 4,4-Dithiodipyridine (DTDP) Derivatization and Ultraperformance Convergence Chromatography-Tandem Mass Spectrometry

Wine varietal thiols are important contributors to wine aroma. The chemical nature of thiols makes them difficult to measure due to low concentrations, high sensitivity to oxidation, and low ionization. Methods for the measurement of thiols usually consist of multiple steps of sample preparation followed by instrumental measurement. Studies have collected large datasets of thiols in white wine but not in red wine, due to the lack of availability of suitable methods. In this study, for the first time, convergence chromatography was used to measure thiols in red wine at ultratrace levels with improved sensitivity compared to previous methods. Performance parameters (selectivity, linearity, limits of detection, precision, accuracy) were tested to demonstrate the suitability of the method for the proposed application. Red wine thiols were measured in South African Pinotage, Shiraz, and Cabernet Sauvignon wines (n = 16 each). Cultivar differentiation using the thiol profile was demonstrated.