Institute for Wine Biotechnology

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Browsing Institute for Wine Biotechnology by browse.metadata.advisor "Aleixandre-Tudo, Jose Luis"

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    In-Line Monitoring of Red Wine Fermentation
    (Stellenbosch : Stellenbosch University, 2021-03) Lambrecht, Kiera Nareece; Aleixandre-Tudo, Jose Luis; Du Toit, Wessel J.; Nieuwoudt, Helene; Stellenbosch University. Faculty of AgriSciences. Dept. of Viticulture and Oenology. Institute for Wine Biotechnology.
    ENGLISH ABSTRACT: Phenolic compounds may only account for a small percentage of the final composition of a finished red wine but are vital to its sensory attributes. During red wine making, extraction of these phenolic compounds takes place, whereby there is mass transfer from the solids of the grape into the liquid phase. The rate and the extent to which this extraction occurs is dependent on many factors. There are many different methods employed in the wine industry which can influence the composition of the wine. These techniques are varied and can involve manipulating process conditions such as temperature or the addition of certain oenological products. As the final composition of the wine is a major contributing factor to the quality of the wine, it is vital to be able to monitor and control this process. It has been demonstrated through a variety of studies that the use of infrared spectroscopy along with chemometrics provides an avenue for implementation of monitoring and control systems in wineries. However, the limiting factors in these studies are the extensive sample pre-treatment to remove solids before scanning as well as their discrete and off-sight sampling. In the contents of the first research chapter (Chapter 3), a system was designed for the purpose of automatic sampling directly from vessels containing fermenting wines. This was an extensive design process which required separate sampling pumps and sampling lines which delivered samples to a single instrument. Another requirement was automation of different components and synchronisation of these in an individual system. The resulting design was put through a series of stress tests to ensure functionality and reliability. The results showed that the automated system was capable of full-time operation without experiencing component failures and, therefore, it was applied to actual fermentations. For this, 24 hours of real time monitoring was achieved. The turbidity remained a challenge as a perfectly clarified sample was not achievable. This led to the development of partial least squares (PLS) calibrations for three different spectroscopy techniques where the samples used incorporated differing degrees of sample pre-treatment to reduce turbidity. The results of this endeavour compiled in Chapters 4 and 5 showed favourable results for samples with different levels of turbidity as well as for contactless methods of conducting analysis. With further optimisation of the models using spectral pre-processing and wavenumber selection, it was possible to develop models suitable for application in an industrial setting. Finally, in Chapter 6, these models were deployed for use with a series of fermentations, where the ability to monitor phenolic extraction of fermentations receiving different treatments was explored. The results show that the system can be used to monitor trends in phenolic extraction in an industrial set-up. In addition to this, the system has the capacity for updated models and different methods of process control, thereby allowing it to be tailored to each unique scenario.
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    A survey of the YAN status of South African grape juices and exploration of multivariate data analysis techniques for spectrometric calibration and cultivar discrimination purposes.
    (Stellenbosch : Stellenbosch University, 2018-12) Petrovic, Gabriella; Buica, Astrid; Aleixandre-Tudo, Jose Luis
    ENGLISH ABSTRACT: Yeast assimilable nitrogen (YAN) has been identified as one of the main drivers of wine quality, influencing the production of various aromas and ensuring a successful fermentation to dryness. Due to the number of factors affecting YAN concentration and composition, paired with the complexities of yeast metabolism, more data is required to enable a comprehensive understanding of this important component of the grape juice matrix. Thus, there is a need for simple, rapid, and cost-effective methods to measure YAN status. The main aims of this research were to gain insight into the nitrogen status of grape juices used for commercial winemaking in the South African wine industry, and subsequently, to assist in a more comprehensive understanding of grape juice nitrogen status. Therefore, in Chapter 3, an unsupervised survey of the YAN, FAN, and ammonia concentrations of 805 grape juice samples of various (industrially relevant) cultivars and geographical origins are reported. Subsequently, an overall average of 191 ± 64 mg N/L, 138 ± 46 mg N/L and 53 ± 24 mg N/L was observed for YAN, FAN, and ammonia, respectively. Trends of nitrogen deficiency and excess could be found for various cultivars and geographical origins. Analysis of variance tests and exploratory data analysis techniques such as hierarchical agglomerative clustering and CART analysis established ‘cultivar’ as the most important factor in determining the YAN concentration and composition of the resulting grape juice. In Chapter 4, using the data collected in Chapter 3, plus an additional vintage (2018), the viability of infrared (IR) spectroscopy for the accurate quantification of YAN, FAN, and ammonia was tested. IR spectroscopies compared included: Fourier-transform infrared (FT-IR), Fourier-transform near infrared (FT-NIR) and attenuated total reflection mid-infrared (ATR-MIR) spectroscopy. FT-IR and FT-NIR were found to outperform ATR-MIR in a variety of tasks assigned to each instrument and were deemed robust and capable of accurate quantification as RPDVAL > 2.5 were repeatedly obtained for both spectroscopies. The achievement of accurate calibration models is owed to the large amount of variability included in both the calibration and validation sets and the application of proper external validation strategies. Thus, both industry and research are presented with a simple, rapid and cost-effective method to measure this important component of the grape juice matrix. In Chapter 5, a deeper look into the FAN component of YAN was conducted by quantifying individual amino acids. Overall, proline, arginine, glutamine, alanine, tryptophan and GABA were found to be the most abundant while glycine, lysine, methionine and, ornithine were found to be the least abundant. Subsequently, the discriminatory power of the amino acid profile of the various cultivars were tested. This was done to identify key differences in amino acid profiles which could possibly serve as the basis for further research investigating yeast metabolism and aroma production during fermentation. The results of this research have contributed a wealth of information regarding the nitrogen status of various cultivars of Vitis vinifera, together with a rapid and easy-to-use method for the quantification of the nitrogen status of the grape juice matrix. This was done in hope of furthering the research efforts in this field to aid the production of quality wines, capable of meeting consumer demands.