Thesis (MscAgric (Viticulture and Oenology))--University of Stellenbosch, 2007. / The rapid expansion of the world wine industry has increased the pressure on wine producers to
produce high quality, distinguishable wines. The use of sensory evaluation alone as a tool to
distinguish between wines is limited by its subjective nature. Chemical characterisation using
analytical methods and data analysis techniques are increasingly being used in conjunction with
sensory analysis for comprehensive profiling of wine. Analytical chemistry and chemometric
techniques are important and inextricable parts of the chemical characterisation of wine. Through
this process insight into the inherent composition of wines, be it in a general sense or related to a
particular wine category is gained. Data generated during chemical characterisation are typically
compiled into electronic databases. The application of such information towards wine quality
control includes the establishment of industry benchmarks and authentication.
The current project is part of The South African Young Wine Aroma Project, a long term
research initiative funded by the South African Wine Industry with the ultimate aim to establish a
comprehensive, up-to-date, database of the volatile composition of young wines. The data
generated during this thesis represent the first contribution towards realising this ambition.
Three clearly defined aims were set for this project, the first of which is the chemical
characterisation of South African young wines in terms of selected volatile and non-volatile
compounds and Fourier transform infrared spectra, with particular focus on the volatile
composition. FTMIR spectra are information rich and non-specific instrumental signals that could
provide invaluable information of the inherent composition of the wines. The second aim is the
evaluation of the analytical methods used to generate the data and in the last instance, the
optimisation of FTMIR spectroscopy for rapid quantification of major wine parameters and volatile
compounds.
The concentrations of 27 volatile compounds in South African young wines were determined
by gas chromatography coupled to flame ionisation detection (GC-FID) using liquid-liquid
extraction of the analytes. Wine samples of the 2005 and 2006 vintages produced from six of the
most important cultivars in the South African wine industry, namely Sauvignon blanc, Chardonnay,
Pinotage, Cabernet Sauvignon, Merlot and Shiraz were used. The producing cellars were from four
major South African wine producing regions, namely Stellenbosch, Paarl, Robertson and
Worcester. The data captured made a significant contribution to the establishment of the Aroma
Project Database. Univariate statistics showed wide variations in the chemical composition of the
wines. Red wines were generally characterised by high levels of higher alcohols and white wines
by high levels of esters. Most of the differences between vintages were cultivar dependent and
phenological differences between cultivars were suggested as a possible cause. Fusel alcohols,
iso-acids and esters of fusel alcohols were particularly responsible for differences between red
wines. A combination of fatty acids and higher alcohols were responsible for differences between
production regions. However, using univariate statistics alone was limited in identifying
characteristic features of the chemical composition of the wines. In order to explore the correlations between the volatile components, FTMIR spectra and nonvolatile
components the data were further investigated with multivariate data analysis. Principal
component analysis was successfully employed to distinguish between wines of different vintages
and cultivars. The role of the volatile composition was more influential in the separation of vintage
and red wine cultivar groupings than the non-volatile components or the FTMIR spectra. Almost all
the individual volatile components contributed to the separation between the vintages and cultivars,
thereby highlighting the multivariate nature required to establish the distinguishing features
pertaining to each of these categories. The FTMIR spectra and the non-volatile components were
more important than the volatile components to characterise the differences between the white
cultivars. It was not surprising that both the volatile components and the FTMIR spectra were
needed to distinguish between both red and white cultivars simultaneously. It was of interest the
full spectrum, including all wavenumbers were required for a powerful classification model. This
finding supports the initial expectation that the non-selective but information rich signal captured in
the FTMIR spectra is indispensable. No distinction could be made between the production regions,
which was not surprising since the wines used in this study was not of guaranteed origin.
Furthermore, no clear correlation could be established between the chemical composition or the
FTMIR spectra and the quality ratings of the wines. Limitations in the dataset were pointed out that
must be taken into account during further investigations in the future.
The liquid-liquid extraction method used during the analysis of the volatile components was
evaluated for precision, accuracy and robustness. Generally good precision and accuracy were
observed. There were slight indications of inconsistencies in the recoveries of analytes between
the red and white wine matrices. Certain parameters of the protocol, namely sample volume,
solvent volume, sonication temperature and sonication time, were identified as factors that had a
major influence on quantification. The results obtained in this study made a major contribution
towards establishing this technique for routine GC-FID analysis in our environment.
Due to the high sample throughput in wine laboratories, the use of rapid quantitative analytical
methods such as FTMIR spectroscopy is becoming increasingly important. Enzymatic-linked
spectrophotometric assays and high performance liquid chromatography (HPLC) methods were
evaluated for their suitability to serve as reference methods for optimising and establishing FTMIR
calibrations for glucose, fructose, malic acid, lactic acid and glycerol. Pigmented and phenolic
compounds were identified as sources of interference in the determination of organic acids in red
wines with both enzymatic assays and HPLC. The use of fining treatments for the decolourisation
of red wine samples was investigated. Activated charcoal was more efficient in terms of colour
removal than polyvinyl polypyrrolidone (PVPP), but neither were compatible with the specific
enzymatic method used in this study. Solid phase extraction (SPE), a method commonly used
during sample clean-up prior to HPLC analysis of organic acids in wine, and PVPP fining were
evaluated as sample preparation methods for HPLC analysis to optimise the quantification of
organic acids in red wine. Four different types of SPE cartridges were evaluated and the SPE
method was optimised in order to recover the maximum amount of organic acids. However, low
recoveries, in some instance less than 50%, for the organic acids in wine were reported for the
optimised SPE method. In this respect one was the worst. On average, excellent recoveries were observed for the organic acids using the PVPP method that were in excess of 90%. This method
therefore provides a very valuable and simple alternative to SPE for sample-cleanup prior to HPLC
analysis. One aspect that still needs to be investigated is the reproducibility of the method that
should still be optimised. In general, enzymatic analysis was more suitable for the determination of
glucose and fructose, while HPLC analysis were more suitable for the quantification of organic
acids. Efficient glycerol quantification was observed with both enzymatic and HPLC analysis,
although a lower measurement error was observed during the HPLC analysis.
Apart from reliable reference methods, successful FTMIR calibrations also rely on the
variability present in the reference sample set. The reference sample set used to establish FTMIR
calibrations must ideally be representative of the samples that will be analysed in the future.
Commercial, or so-called global, FTMIR calibrations for the determination of important wine
parameters were evaluated for their compatibility to a South African young wine matrix. The
prediction pH, titratable acidity, malic acid, glucose, fructose, ethanol and glycerol could be
improved by establishing a brand new FTMIR calibration, thereby clearly indicating that the South
African young wine matrices were significantly different from the samples of European origin that
were used to establish the commercial calibrations. New preliminary calibration models were
established for a young wine sample matrix and were validated using independent test sets. On
average the prediction errors were considered sufficient for at least screening purposes. The effect
of wavenumber selection was evaluated. Relatively successful models could be established for all
the compounds except glucose. Wavenumber selection had an influence on the efficiency of the
calibration models. Some models were more effective using a small amount of highly correlated
wavenumbers, while others were more effective using larger wavenumber regions.
Preliminary FTMIR calibration models for the screening of volatile compound groups in young
wines were evaluated. Compound groups were compiled based on chemical similarity and flavour
similarity. Good linearity were observed for the “total alcohol”, “total fatty acids”, “esters” models
while an interesting polynomial trend was observed for the “total esters” model. Relatively high
prediction errors indicated the possibility of spectral interferences, but the models were
nevertheless considered suitable for screening purposes. These findings are a valuable
contribution to our environment where fermentation flavour profiles must often be examined.
The important role sound and validated analytical methods to generate high quality analytical
data, and the subsequent application of chemometric techniques to model the data for the purpose
of wine characterisation has been thoroughly explored in this study. After a critical evaluation of the
analytical methods used in this study, various statistical methods were used to uncover the
chemical composition of South African young wines. The use of multivariate data analysis has
revealed some limitations in the dataset and therefore it must be said that wine characterisation is
not just reliant on sophisticated analytical chemistry and advanced data analytical techniques, but
also on high quality sample sets.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/2562 |
| Date | 12 1900 |
| Creators | Louw, Leanie |
| Contributors | Van Rensburg, Pierre, Nieuwoudt, Helene, University of Stellenbosch. Faculty of Agrisciences. Dept. of Viticulture and Oenology. |
| Publisher | Stellenbosch : University of Stellenbosch |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 1147257 bytes, application/pdf |
| Rights | University of Stellenbosch |
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