WINETECH Technical Yearbook 2019

variability associated with this important component of the grape juice matrix. A ‘Big Data’ approach to wine research, and specifically YAN, would be ideal to enable a holistic and integrated understanding of such a complex system. However, by reviewing the characteristics of Big Data, it becomes clear that the current velocity of YAN data generation (through traditional methods), may not be adequate to allow for a realistic ‘Big Data’ approach. Therefore, to facilitate further value creation, it is necessary to use methods which will enable high-velocity data generation. Due to the simple, rapid and cost-effective nature of spectroscopy and the recent developments in IR instrumentation and chemometrics, the ability of IR technology to accurately measure grape juice YAN

was investigated. Due to the sampling and validation strategies employed, it was clear that the proposed models would be capable of providing accurate results in a practical scenario where samples from different cultivars, vintages and origins need to be analysed. Therefore, this research provides not only a technique for effective Big Data collection, but also a more rapid and cost-effective method for winemakers to obtain timely information. Therefore, from a ‘Big Data’ point of view, IR spectroscopy is capable of providing value by means of collecting a high volume of a variety of data at a high velocity. Future success of this technology in the context of Big Data will be spurred on by the development of accurate calibrations on portable hand-held devices providing the means of on-line and real-time data collection.

juice matrix, we looked into maximising the information output of the surveyed data using various descriptive and exploratory statistical techniques. Furthermore, the data was used to build robust quantitative models using IR spectroscopy for the measurement of total YAN, FAN and ammonia for more rapid and cost-effective analysis and qualitative models to discriminate between cultivars based on amino acid composition. These aspects will be presented in a series of WineLand articles. REFERENCE Petrovic, G. 2018. A survey of the YAN status of SA grape juices and exploration of multivariate data analysis techniques for spectrophotometric calibration and cultivar discrimination purposes. MSc Thesis, Stellenbosch University.

SUMMARY The term ‘Big Data’ has become a part of modern-day vocabulary, most commonly used in the field of business to facilitate the understanding of consumers. Nevertheless, the so-called ‘Big-Data revolution’ is just as indispensable to scientific research, providing the possibility of more data- driven and informed decision-making and hypothesis generation. Recently, there has been a vast amount of work done at the Department of Viticulture and Oenology (DVO), which focused on addressing some of these issues (Petrovic, 2018). The main aim of the work was to gain insight into the YAN status of South African grape juices currently used for commercial winemaking. To help provide a more comprehensive understanding of the YAN status of the grape

– For more information, contact Astrid Buica at abuica@sun.ac.za.