IVAS 2022 banner
IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Influence of oak species on the differentiation of aged brandies using chemometrics approach based on phenolic compounds UHPLC fingerprints

Influence of oak species on the differentiation of aged brandies using chemometrics approach based on phenolic compounds UHPLC fingerprints

Abstract

Oak is the main material used in cooperage for making barrels and wood chips destined to aged spirits and wines. Quercus alba L., Quercus petraea L. and Quercus robur L. are three of the most commonly used oak species in cooperage companies. The geographical origin and botanical species influence the composition of the wood and the subsequent impact on the sensory profile of the product aged in the wooden barrels. Depending on the type of oak in which the wines and spirits are aged, the final products obtained are very different. Phenolic compounds are the main components extracted from the wood during ageing, and they depend on many factors. Botanical species, toasting level, barrel dimension and ageing time are parameters that affect the type and amount of polyphenols that the wood releases into the wines and distillates.
Combining instrumental fingerprints with Chemometrics, known as fingerprinting methodology, is a novel strategy that allows information about the composition of brandy samples to be obtained in a non-selective way, as it is not necessary to identify or quantify the compounds present in the sample. Through a chemometric study of the instrumental fingerprint, it is possible to identify known or unknown areas of the chromatograms characteristic of a particular type of sample. Ultra-High-Performance Liquid Chromatography (UHPLC) was used to acquire the instrumental fingerprints of the phenolic profile at 280 nm and 320 nm of aged brandy samples. The chromatographic fingerprints of more than 100 samples of brandies produced from different distillates and aged in 350-litre barrels from three different oaks, Quercus alba L., Quercus robur L., and Quercus petraea L.; with two different degrees of toasting, medium and light; and during 14 and 28 months were recorded and pre-processed for the chemometric approach centred on patterns recognition.
Unsupervised patterns recognition techniques such as principal component analysis (PCA) and hierarchical cluster analysis (HCA) were applied. The results of these analyses revealed the influence of distillate type, ageing time and toasting level on the natural grouping of samples, being the first one the variable that most affects the natural grouping of samples. Nevertheless, for the same type of distillate, ageing time and toasting level, variables that influence the ageing process, groupings of the samples were observed depending on the type of wood in which they were aged. This methodology is very interesting, since it is not necessary to know or identify all the compounds that appear in the chromatographic profile to determine in this case, whether the brandy is aged in one or another type of oak. The application of the results obtained could lead in the future to a model for the discrimination/classification of brandies, based on the type of oak in which it is aged.

DOI:

Publication date: June 23, 2022

Issue: IVAS 2022

Type: Poster

Authors

Guerrero-Chanivet, María1,2, Ortega-Gavilán Fidel3, Bagur-González M. Gracia3, García-Moreno M. Valme1, Butrón-Benítez Daniel1,2, Guillén-Sánchez Dominico A.1 and Valcárcel-Muñoz Manuel J.2

1Department of Analytical Chemistry, Faculty of Science, IVAGRO, Campus of Puerto Real, University of Cádiz
2Bodegas Fundador, S.L.U.
3University of Granada

Contact the author

Keywords

Brandy, oak, ageing, fingerprint, phenolic compounds

Tags

IVAS 2022 | IVES Conference Series

Citation

Related articles…

An analytical framework to site-specifically study climate influence on grapevine involving the functional and Bayesian exploration of farm data time series synchronized using an eGDD thermal index

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

Effect of fertigation strategies to adapt PGI Côtes de Gascogne production to hot vintage

The development of fertigation could be a possible solution to adapt PGI Côtes de Gascogne (south-western France) wine production to climate change. The goal would be to limit the negative effects of water stress on yield performance expectation (around 15 tons per hectare) and to make the use of fertilizers more efficient. This study aimed to compare the effects of three strategies of water and minerals supply on grapes and wines qualities. Two fertigation practices were compared to a rainfed control which is the current standard of the local grape growing production. The fertilizers (nitrogen and potassium) were (i) fully brought by irrigation pipe during the season, (ii) partially brought by irrigation pipe and partially on the soil or (iii) fully brought on the soil at the beginning of the season for the non-irrigated control (local standard). The trial was run on cv. Colombard trained on spur pruned with vertical shoot positioning system on a sandy-silty-clay soil over the 2020 vintage which was particularly hot for the region. Moderate to strong water deficit appeared during the growing period of the berries and held on after veraison. Irrigation strategies allowed for maintaining grapevine without water deficit and being significantly different from the control water status. Grapevine with fully or partial fertigation strategies produced 25% more yield mainly due to the increase of the bunch weight. Also, the fully fertigation showed the best ratio between yield and maturity and brought 30% less of fertilizers (both nitrogen and potassium) than the two other strategies. Finally, the analysis of aromatic compounds in Colombard wines, varietal thiols family, showed the same level of concentrations for the 3 treatments, confirming that the yield performance did not impact the aromatic potential in this trial.

Sustaining wine identity through intra-varietal diversification

With contemporary climate change, cultivated Vitis vinifera L. is at risk as climate is a critical component in defining ecologically fitted plant materiel. While winegrowers can draw on the rich diversity among grapevine varieties to limit expected impacts (Morales-Castilla et al., 2020), replacing a signature variety that has created a sense of local distinctiveness may lead to several challenges. In order to sustain wine identity in uncertain climate outcomes, the study of intra-varietal diversity is important to reflect the adaptive and evolutionary potential of current cultivated varieties. The aim of this ongoing study is to understand to what extent can intra-varietal diversity be a climate change adaptation solution. With a focus on early (Sauvignon blanc, Riesling, Grolleau, Pinot noir) to moderate late (Chenin, Petit Verdot, Cabernet franc) ripening varieties, data was collected for flowering and veraison for the various studied accessions (from conservatory plots) and clones. For these phenological growing stages, heat requirements were established using nearby weather stations (adapted from the GFV model, Parker et al., 2013) and model performances were verified. Climate change projections were then integrated to predict the future behaviour of the intra-varietal diversity. Study findings highlight the strong phenotypic diversity of studied varieties and the importance of diversification to enhance climate change resilience. While model performances may require improvements, this study is the first step towards quantifying heat requirements of different clones and how they can provide adaptation solutions for winegrowers to sustain local wine identity in a global changing climate. As genetic diversity is an ongoing process through point mutations and epigenetic adaptations, perspective work is to explore clonal data from a wide variety of geographic locations.

VINIoT – Precision viticulture service

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).

How distinctive are single vineyard Gewürztraminer musts and wines from Alto Adige (Italy) based on untargeted analysis, sensory profiling, and chemometric elaboration?

Vitis vinifera L. ‘Gewürztraminer’ is a historical grape variety of Alto Adige (Südtirol), Italy, which is widely grown in the area of Tramin an der Weinstraße, but is also grown globally. It produces highly aromatic wines that are strongly influenced by the terroir of the vineyard sites where they are grown. This study looked at musts and young wines from ‘Gewürztraminer’ grapes harvested in seven distinct vineyards near Tramin and then processed at Cantina di Termeno, minimizing winemaking protocol variability. Samples were profiled using bidimensional gas chromatography–time-of-flight mass spectrometry, liquid chromatography coupled to electrochemical detection, and near-IR spectrometry. The data were subjected to Principle Component Analysis and Hierarchical Clustering Analysis. Sensory discriminant testing was undertaken using the sorting method with a semi-trained panel, and the data were processed using Multidimensional Scaling. Seven must/wine pairs could be distinguished based on their untargeted volatilome profiles and on sensory evaluation. As expected, there were greater differences in the volatile compounds between the wines than between the musts. The wines from vineyards 4 and 5 were nonetheless quite homogenous in terms of chemical and sensory analyses, as were the wines from vineyards 1 and 3. For the phenolic profile, differences were noted between the musts and wines of vineyards 2, 3, and 4, but the musts from vineyards 5 and 7 were similar. Sensory analysis showed the wines from vineyards 6 and 7 to be distinct from the rest. These results reinforce that the composition of ‘Gewürztraminer’ musts and wines is strongly determined by vineyard site, even in a small geographic area with high variability of the terroir (soil and microclimate), and that these differences are apparent in the flavours and aromas of the finished wines. Further confirmation would require a larger sample of wines, preferably from several vintages.