Characterization of Greek Wines by Ultraviolet–Visible Absorption Spectroscopy and Statistical Multivariate Methods

Philippidis, Aggelos; Poulakis, Emmanouil; Basalekou, Marianthi; Strataridaki, Argiro; Καλλιθράκα, Σταματίνα; Velegrakis, Michalis

doi:10.1080/00032719.2016.1255748

Cited by 11 publications

(10 citation statements)

References 37 publications

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“…From this figure it is obvious that for white wine varieties ( Figure 1 a), absorption bands occur in the ultraviolet region (268–280 nm and 320 nm), while for the red ( Figure 1 b), there is an extra absorption band in the visible region (500–524 nm). The chemical fingerprint of the specific Greek wine varieties has been discussed in a previous work [ 26 ]. Briefly, the absorption band at 280 nm is related to different types of phenolic compounds, while the absorption band at 320 nm is correlated to flavones and/or to nonflavonoid compounds.…”

Section: Resultsmentioning

confidence: 99%

“…Moreover, the samples of Mandilari variety are more confined than the Kotsifali ones. Τhis is possibly due to the initial high concentration of the total phenolic content for the specific red wine variety [ 26 , 34 ], which resulted in the lower contribution of aging time in the classification between Mandilari samples. This reflects the oenological behavior of these varieties since it is known that Mandilari has a higher phenolic content than Kotsifali [ 13 , 31 ].…”

Section: Resultsmentioning

confidence: 99%

“…In a previous work, we employed absorption spectroscopy for the analysis of Greek wines [ 26 ]. A total of 12 red and 10 white wines, all cultivated in Crete and matured for 3 months in various barrels, were analyzed by UV-Vis absorption spectroscopy.…”

Section: Introductionmentioning

confidence: 99%

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Application of Ultraviolet-Visible Absorption Spectroscopy with Machine Learning Techniques for the Classification of Cretan Wines

Philippidis

Poulakis

Kontzedaki

et al. 2020

Foods

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The present study was aimed at the identification, differentiation and characterization of red and white Cretan wines, which are described with Protected Geographical Indication (PGI), using ultraviolet–visible absorption spectroscopy. Specifically, the grape variety, the wine aging process and the role of barrel/container type were investigated. The combination of spectroscopic results with machine learning-based modelling demonstrated the use of absorption spectroscopy as a facile and low-cost technique in wine analysis. In this study, a clear discrimination among grape varieties was revealed. Moreover, a grouping of samples according to aging period and container type of maturation was accomplished, for the first time.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Application of Ultraviolet-Visible Absorption Spectroscopy with Machine Learning Techniques for the Classification of Cretan Wines

Philippidis

Poulakis

Kontzedaki

et al. 2020

Foods

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“…The absorption at 320 nm is related to flavones and to non-flavonoid compounds. 46 Inspection of the UV absorption spectra (Fig. 2) shows that thyme and honeydew honeys have higher absorbance than the multi-floral honey.…”

Section: Uv Absorption Spectroscopy (200-400 Nm)mentioning

confidence: 99%

Optical spectroscopy methods combined with multivariate statistical analysis for the classification of Cretan thyme, multi‐floral and honeydew honey

Orfanakis

Markoulidakis²,

Philippidis

et al. 2021

J Sci Food Agric

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BACKGROUND: The botanical origin of honey attracts both commercial and research interest. Consumers' preferences and medicinal uses of particular honey types drive the demand for the determination of their authenticity with regard to their botanical origin. This study presents the discrimination of thyme, multi-floral. and honeydew honeys by Fourier-transform infrared (FTIR) and ultraviolet (UV) absorption spectroscopy combined with multivariate statistical analysis. UV absorption spectroscopy was applied without any dilution of the sample using a custom-made cuvette. FTIR and UV absorption spectroscopic data were processed by means of the orthogonal partial least squares discriminant analysis. RESULTS:The optimal classification of floral and honeydew honeys was accomplished with UV spectroscopy with a successful estimation of 92.65% for floral honey and 91.30% for honeydew honey. The discrimination of thyme versus the multi-floral honey was best achieved with FTIR, with a correct classification of 95.56% and 100% for multi-floral and thyme honey respectively. Furthermore, our findings revealed the region of 2400-4000 cm −1 of the FTIR spectra as the most significant for this discrimination.CONCLUSION: This work demonstrates that optical spectroscopic techniques in combination with multivariate statistical analysis can be a rapid, low-cost, easy-to-use approach for the determination of the botanical origin of honey without sample pretreatment.

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“…Both targeted and untargeted techniques have been previously combined with machine learning methods, such as PLS-DA, SVMs, Neural Networks etc. Indicatively, various agricultural products such as honey [19,20] and wine [21][22][23][24][25][26] have been investigated, considering a wide range of issues and authentication purposes such as their quality, variety and geographical and botanical origin.…”

Section: Introductionmentioning

confidence: 99%

Comparative Evaluation of Different Targeted and Untargeted Analytical Approaches to Assess Greek Extra Virgin Olive Oil Quality and Authentication

et al. 2022

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Extra virgin olive oil (EVOO) is a key component of the Mediterranean diet, with several health benefits derived from its consumption. Moreover, due to its eminent market position, EVOO has been thoroughly studied over the last several years, aiming at its authentication, but also to reveal the chemical profile inherent to its beneficial properties. In the present work, a comparative study was conducted to assess Greek EVOOs’ quality and authentication utilizing different analytical approaches, both targeted and untargeted. 173 monovarietal EVOOs from three emblematic Greek cultivars (Koroneiki, Kolovi and Adramytiani), obtained during the harvesting years of 2018–2020, were analyzed and quantified as per their fatty acids methyl esters (FAMEs) composition via the official method (EEC) No 2568/91, as well as their bioactive content through liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) methodology. In addition to FAMEs analysis, EVOO samples were also analyzed via HRMS-untargeted metabolomics and optical spectroscopy techniques (visible absorption, fluorescence and Raman). The data retrieved from all applied techniques were analyzed with Machine Learning methods for the authentication of the EVOOs’ variety. The models’ predictive performance was calculated through test samples, while for further evaluation 30 commercially available EVOO samples were also examined in terms of variety. To the best of our knowledge, this is the first study where different techniques from the fields of standard analysis, spectrometry and optical spectroscopy are applied to the same EVOO samples, providing strong insight into EVOOs chemical profile and a comparative evaluation through the different platforms.

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Characterization of Greek Wines by Ultraviolet–Visible Absorption Spectroscopy and Statistical Multivariate Methods

Cited by 11 publications

References 37 publications

Application of Ultraviolet-Visible Absorption Spectroscopy with Machine Learning Techniques for the Classification of Cretan Wines

Application of Ultraviolet-Visible Absorption Spectroscopy with Machine Learning Techniques for the Classification of Cretan Wines

Optical spectroscopy methods combined with multivariate statistical analysis for the classification of Cretan thyme, multi‐floral and honeydew honey

Comparative Evaluation of Different Targeted and Untargeted Analytical Approaches to Assess Greek Extra Virgin Olive Oil Quality and Authentication

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