New Zealand's Pinot Noir wines are famous for their unique flavors and how they change based on where they are grown. This makes them perfect for figuring out where a wine comes from. The goal is to create a system that can accurately trace the origins of these wines. This helps protect the reputation and value of New Zealand's Pinot Noir.

To do this, researchers looked at 116 samples from three different regions. They used two main methods: examining the chemical makeup of the wines and analyzing their infrared spectra. The infrared spectra, especially between 3050 and 1950 centimeters, were linked to the key compounds in the wines. This connection was strong, with accuracy rates ranging from 75% to 99%.

Several advanced techniques were used to analyze the data. These included Linear Discriminant Analysis (LDA), Partial Least Squares Discriminant Analysis (PLS-DA), Artificial Neural Networks (ANN), and Random Forest (RF). Some of these methods used only the chemical data, while others used only the spectral data, and some combined both. The LDA and ANN methods stood out as the best at correctly identifying the wine's origin.

The chemical makeup of the wine gives detailed information about what's in it. The infrared spectra provide a broader view of the wine's chemistry. By combining these two methods, researchers can more accurately determine where a wine comes from. This reduces the chances of mistakes that can happen when using only one method.

In the end, these methods proved to be quick and effective ways to trace the origins of New Zealand's Pinot Noir wines. This is important for maintaining the quality and reputation of these wines. However, it's crucial to keep in mind that while science can help, the final judgment on wine quality often comes down to personal taste.

MULTIVARIATE DATA ANALYSIS METHODS

Unmasking New Zealand's Pinot Noir: The Science Behind Wine's True Home

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