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…

Bioclimatic shifts and land use options for Viticulture in Portugal

Land use, plays a relevant role in the climatic system. It endows means for agriculture practices thus contributing to the food supply. Since climate and land are closely intertwined through multiple interface processes, climate change may lead to significant impacts in land use. In this study, 1-km observational gridded datasets are used to assess changes in the Köppen–Geiger and Worldwide Bioclimatic (WBCS)

Climate modeling at local scale in the Waipara winegrowing region in the climate change context

In viticulture, a warming climate can have a very significant impact on grapevine development and therefore on the quality and characteristics of wines across different spatial scales, ranging from global to local. In order to adapt wine-growing to climate change, global climate models can be used to define future scenarios, but only at the scale of major wine regions. Despite the huge progress made over the last ten years in terms of the spatial resolution of climate models (now downscaled to a few square kilometres), they are not yet sufficiently precise to account for the local climate variability associated with such parameters as local topography, in spite of these parameters being decisive for vine and wine characteristics. This study describes a method to downscale future climate scenarios to vineyard scale. Networks of data loggers have been used to collect air temperature at canopy level in the Waipara winegrowing region (New Zealand) over five growing seasons. These measurements allow the creation of fine-scale geostatistical models and maps of temperature (at 100 m resolution) for the growing season. In order to model climate change at pilot site scale, these geostatistical models have been combined with regional climate change predictions for the periods 2031-2050 and 2081-2100 based on the RCP8.5 climate change scenario. The integration of local climate variability with regionalized climate change simulations allows assessment of the impacts of climate change at the vineyard scale. The improved knowledge gained using this methodology results from the increased horizontal resolution that better addresses the concerns of winegrowers. The results provide the local winegrowers with information necessary to understand current processes, as well as historical and future viticulture trends at the scale of their site, thereby facilitating decisions about future response strategies.

Better understand the soil wet bulb formation with subsurface or aerial drip irrigation in viticulture

The gradual change in rainfall patterns experienced in the south of France vineyards, especially around the Mediterranean sea, means that the vines are increasingly subject to summer drought. The winegrowers developped the use of irrigation techniques to ensure the maintenance of competitive yields in the production of wines under Protected Geographical Indication label. In practice, drip irrigation pipes can be installed above the ground or buried into the soil as well as at different distances from the vine row. The objective of this study was to examine the profiles of the wet bulbs of the soil obtained from two drip irrigation systems : aerial drip located under the vine row and subsurface drip placed in the middle of the inter-row. This experiment took place over two consecutive seasons (2020-2021) on a 3.4 ha Viognier plot in the Mediterranean region (PGI Oc, France) on sandy clay soil. The annual rainfalls were less than 400 mm. Soil water content probes were installed at different depths (20 – 40 – 60 – 80 cm) and at different lateralities from the vine row (30 – 60 – 90 – 120 cm) to control the formation of the soil wet bulb during irrigation. The mapping and the analysis of the data allowed a better understanding and differentiation of the water percolation when irrigating with subsurface or aerial drip. For the same amount of water and without differences of vine water status, it is shown that in a subsurface drip irrigation situation, the size of the wet bulb formed is larger than in aerial drip irrigation system.

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.

Impact of yeast derivatives to increase the phenolic maturity and aroma intensity of wine

Using viticultural and enological techniques to increase aromatics in white wine is a prized yet challenging technique for commercial wine producers. Equally difficult are challenges encountered in hastening phenolic maturity and thereby increasing color intensity in red wines. The ability to alter organoleptic and visual properties of wines plays a decisive role in vintages in which grapes are not able to reach full maturity, which is seen increasingly more often as a result of climate change. A new, yeast-based product on the viticultural market may give the opportunity to increase sensory properties of finished wines. Manufacturer packaging claims these yeast derivatives intensify wine aromas of white grape varieties, as well as improve phenolic ripeness of red varieties, but the effects of this application have been little researched until now. The current study applied the yeast derivative, according to the manufacture’s instructions, to the leaves of both neutral and aromatic white wine varieties, as well as on structured red wine varieties. Chemical parameters and volatile aromatics were analyzed in grape musts and finished wines, and all wines were subjected to sensory analysis by a tasting panel. Collective results of all analyses showed that the application of the yeast derivative in the vineyard showed no effect across all varieties examined, and did not intensify white wine aromatics, nor improve phenolic ripeness and color intensity in red wine.