Spectroscopic techniques such as near infrared (NIR) spectroscopy are used in the food industry to monitor and assess the composition and quality of products. Similar to other food industries, the wine industry has a clear need for simple, rapid and cost-effective techniques for objectively evaluating the quality of grapes, wines and spirits. Thirty years have passed since the fi rst work reported by Kaffka and Norris on the use of NIR spectroscopy to analyse wine. Since then, NIR spectroscopy has been used for grape and wine compositional analysis, fermentation monitoring and wine grading. However, the use of NIR spectroscopy in the wine industry is still in its infancy. From the analysis of the scatter information available, it appears that NIR spectroscopy is applied in different steps during the wine production. This review highlights the most recent applications of NIR spectroscopy in the grape and wine industry. Additional information is also provided on the use of mid infrared spectroscopy for wine analysis.
Real-world systems are usually multivariate and hence usually cannot be adequately described by one selected variable without the risk of serious misrepresentation. Analyzing the effect of one variable at a time by analysis of variance techniques can give useful descriptive information, but this will not give specifi c information about relationships among variables and other important relationships in the entire matrix. Multivariate data analysis was developed in the late 1960s, and used by a number of research groups in analytical and physical organic chemistry due to the introduction of instrumentation giving multivariate responses for each sample analyzed. Development of such methods was also made possible by the availability of computers. Multivariate data analysis involves the use of mathematical and statistical techniques to extract information from complex data sets. The objective of this paper is to briefl y describe and illustrate some multivariate data analysis methods used for grape and wine analysis.
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