OENO IVAS 2019 banner
IVES 9 IVES Conference Series 9 OENO IVAS 9 OENO IVAS 2019 9 Analytical developments from grape to wine, spirits : omics, chemometrics approaches… 9 Strategies for sample preparation and data handling in GC-MS wine applications

Strategies for sample preparation and data handling in GC-MS wine applications

Abstract

It is often said that wine is a complex matrix and the chemical analysis of wine with the thousands of compounds detected and often measured is proof. New technologies can assist not only in separating and identifying wine compounds, but also in providing information about the sample as a whole. 

Information-rich techniques can offer a fingerprint of a sample (untargeted analysis), a comprehensive view of its chemical composition. Applying statistical analysis directly to the raw data can significantly reduce the number of compounds to be identified to the ones relevant to a particular scientific question. More data can equal more information, but also more noise for the subsequent statistical handling. 

Therefore, strategies to reduce the some of the data can already be applied at the chemical analysis stage without loss of information. 

Using GCMS as analysis tool, an experiment was designed to evaluate on one hand different sample preparation methods, and on the other hand data handling strategies for the results. Twenty-six commercial wines from three cultivars (Chenin Blanc, Chardonnay, Sauvignon Blanc) and two winemaking styles (with and without wood contact) were subjected to three types of sample preparation (liquid/liquid extraction with three solvents, SPE on two stationary phases, HS-SPME on four fibres) before injection into GCMS. The various chemistries and polarities of the extraction solvents and stationary phases used resulted in different types of compounds being extracted from the wines. 

The TIC data was exported as a continuous signal (the chromatogram itself), as integrated peaks identified by their RTs, and as a (RT_m/z, abundance) matrix. Each type of data was submitted to PCA to underscore any natural grouping in the data. OPLS-DA and S-plots were subsequently used to determine the signals associated to cultivar discrimination and style. The raw data was revisited, and MS spectra extracted for the signals of interest, leading to the identification of the drivers (ions/compounds) for cultivars and style. 

The strategies for sample preparation and data extraction were evaluated based on their feasibility and potential for data mining. Additionally, this type of work can be of further use as a basis for developing screening or targeted analyses, based on the groups of analytes extracted during various sample preparation procedures.

DOI:

Publication date: June 23, 2020

Issue: OENO IVAS 2019

Type: Article

Authors

Astrid Buica, Cody Williams, Mpho Mafata, Andrei Medvedovici, Costel Sarbu, Lucky Mokwen 

Institute for Grape and Wine Sciences, Stellenbosch University, South Africa 
Department of Viticulture and Oenology, Stellenbosch University, South Africa 
Department of Analytical Chemistry, Faculty of Chemistry, University of Bucharest, Romania 
Department of Analytical Chemistry, Faculty of Chemistry and Chemical Engineering, University Babes-Bolyai, Cluj-Napoca, Romania 
Central Analytical Facility, Stellenbosch University, South Africa 

Contact the author

Keywords

data mining, GCMS, sample preparation, untargeted analysis

Tags

IVES Conference Series | OENO IVAS 2019

Citation

Related articles…

Modelling vine water stress during a critical period and potential yield reduction rate in European wine regions: a retrospective analysis

Most European vineyards are managed under rainfed conditions, where seasonal water deficit has become increasingly important. The flowering-veraison phenophase represents an important period for vine response to water stress, which is seldomly thoroughly evaluated. Therefore, we aim to quantify the flowering-veraison water stress levels using Crop Water Stress Indicator (CWSI) over 1986–2015 for important European wine regions, and to assess the respective potential Yield Lose Rate (YLR). Additionally, we also investigate whether an advanced flowering-veraison phase may help alleviating the water stress with improved yield. A process-based grapevine model STICS is employed, which has been extensively calibrated for flowering and veraison stages using observed data at 38 locations with 10 different grapevine varieties. Subsequently, the model is being implemented at the regional level, considering site-specific calibration results and gridded climate and soil datasets. The findings suggest wine regions with stronger flowering-veraison CWSI tend to have higher potential YLR. However, contrasting patterns are found between wine regions in France-Germany-Luxembourg and Italy-Portugal-Spain. The former tends to have slight-to-moderate drought conditions (CWSI<0.5) and a negligible-to-moderate YLR (<30%), whereas the latter possesses severe-to-extreme CWSI (>0.5) and substantial YLR (>40%). Wine regions prone to a high drought risk (CWSI>0.75) are also identified, which are concentrated in southern Mediterranean Europe. An advanced flowering-veraison phase may have benefited from cooler temperatures and a higher fraction of spring precipitation in wine regions of Italy-Portugal-Spain, resulting in alleviated CWSI and moderate reductions of YLR. For those of France-Germany-Luxembourg, this can have reduced flowering-veraison precipitation, but prevalent alleviations of YLR are also found, possibly because of shifted phase towards a cooler growing season with reduced evaporative demands. Overall, such a retrospective analysis might provide new insights towards better management of seasonal water deficit for conventionally vulnerable Mediterranean wine regions, but also for relatively cooler and wetter Central European regions.

Combining effect of leaf removal and natural shading on grape ripening under two irrigation strategies in Manto negro (Vitis vinifera L.)

The increasingly frequent heat waves during grape ripening pose challenges for high quality wine grape production. Defoliation is a common practice that can improve the control of diseases in bunches, but also it increases the exposure to sunlight. Grapes exposed to solar radiation reach temperatures over the optimum for berry development and maturation. This makes the development of irrigation and canopy management techniques of great importance to maximize yield and grape quality. A field experiment was carried out during 2021 using Manto negro wine grapes to study the effect of applied irrigation and different light exposure levels on grape quality. Two irrigation treatments were imposed based on the frequency and amount of water doses in a four-block experimental vineyard at Bodega Ribas (Mallorca). Three light exposure treatments were randomly applied in each irrigation plot. The light treatments included exposed clusters from pea size, non-exposed clusters, and shaded clusters after softening. Leaf area index and canopy porosity was estimated every 2 weeks. Midday leaf water potential was measured weekly. Additionally, apparent electrical conductivity was measured between rows to estimate the soil water content variability. Light and temperature sensors were installed at the bunch level to quantify the differences in bunch temperature and light intensity among treatments. The effect of irrigation and cluster light exposure on berry weight, TSS, TA, malic acid, tartaric acid, K+, and pH were analysed at 5 moments along grape ripening. During different heat waves, the natural shading technique decreased the maximum bunch temperature around 10 °C respect to the exposed bunches in both irrigation strategies. The combination of defoliation and shading techniques after softening decreased TSS at harvest and affected most of the quality parameters during the last stages of ripening, showing an interesting technique to delay ripening in warm viticulture areas.

The concept of terroir: what place for microbiota?

Microbes play key roles on crop nutrient availability via biogeochemical cycles, rhizosphere interactions with roots as well as on plant growth and health. Recent advances in technologies, such as High Throughput Sequencing Techniques, allowed to gain deeper insight on the structure of bacterial and fungal communities associated with soil, rhizosphere and plant phyllosphere. Over the past 10 years, numerous scientific studies have been carried out on the microbial component of the vineyard. Whether the soil or grape compartments have been taken into account, many studies agree on the evidence of regional delineations of microbial communities, that may contribute to regional wine characteristics and typicity. Some authors proposed the term “microbial terroir” including “yeast terroir” for grapes to describe the connection between microbial biogeography and regional wine characteristics. Many factors are involved in terroir including climate, soil, cultivar and human practices as well as their interactions. Studies considering “microbial terroir” greatly contributed to improve our knowledge on factors that shape the vineyard microbial structure and diversity. However, the potential impact of “microbial terroir” on wine composition has yet not received strong scientific evidence and many questions remain to be addressed, related to the functional characterization of the microbial community and its impact on plant physiology and grape composition, the origins and interannual stability of vineyard microbiota, as well as their impact on wine sensorial attributes. The presentation will give an overview on the role of microbiota as a terroir component and will highlight future perspectives and challenges on this key subject for the wine industry.

Use of a new, miniaturized, low-cost spectral sensor to estimate and map the vineyard water status from a mobile 

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

Effect of regulated deficit irrigation regime on amino acids content of Monastrell (Vitis vinifera L.) grapes

Irrigation is an important practice to influence vine quality, especially in Mediterranean regions, characterized by hot summers and severe droughts during the growing season. This study focused on deficit irrigation regime influence on amino acids composition of Monastrell grapevines under semiarid conditions (Albacete, Southeastern of Spain). In 2019, two treatments were applied: non-irrigation (NI) and regulated deficit irrigation (RDI), watered at 30% of the estimated crop evapotranspiration from fruit set to onset of veraison. Grape amino acids content was analyzed by HPLC. Berries from non-irrigated vines showed higher concentration of several amino acids, such as tryptophan (73%), arginine (70%), lysine (36%), isoleucine (27%), and leucine (21%), compared to RDI grapes. Arginine is, together with ammonium ion, the principal nitrogen source for yeasts during the alcoholic fermentation; while isoleucine, tryptophan, and leucine are precursors of fermentative volatile compounds, key compounds for wine quality. Moreover, NI treatment increased in a 14% the total amino acids content in grapes compared to RDI treatment. The reported effects might be because yield was 70% higher in RDI vines than in the NI ones and, therefore, the sink demand was increased in the irrigated vines. In addition, NI vines suffered more severe water stress and it is known that the amino acids synthesis and accumulation can be influenced by the plant response to stress. According to the results, the irrigation regime showed effect on amino acids concentration in Monastrell grapes under semiarid conditions. Grapes from non-irrigated vines showed a higher content of several amino acids relevant to the fermentative process and to the wine aroma compounds formation. It is demonstrated that the final content of nitrogen-related components in grapes is influenced by the irrigation regime. The convenience of the irrigation strategy to suggest will depend on the desired wine style and the target yield levels.