CWU Professors Pair Wine with Chemistry, Computer Science

Can a computer be taught to assess wine quality as effectively as a professional human taster? This is a question that Central Washington University professors Anne Johansen, Razvan Andonie, Szilard Vajda, Holly Pinkart, and Amy Mumma set out to answer in their study “Cost Efficient Prediction of Cabernet Sauvignon Wine Quality” to be published soon in the International Symposium Series on Computational Intelligence.

Renown taster and former director of CWU’s Global Wine Studies program Amy Mumma tasted and scored on a scale from 1 (least faulty) to 6 (most faulty) 180 wine samples that included three bottles of 60 different Washington Cabernet Sauvignon wines. Thirty biochemical features were tested in a lab for the same wines, and age and region were added to the dataset.

As Johansen (chemistry), Andonie (computer science), and Vajda (computer science) explain in this interview, the data for the 32 features were related to Amy’s ratings to come up with a computer program that can take data about a given wine and assess its quality on a scale from 1 to 6 with 60 to 70 percent accuracy. Listen here to find out which five features are most cost effective ($25) to use in order to achieve at least 60 percent accuracy in assessing quality.

This study of wine quality is unique because of its large dataset, use of Washington wines, and goal of cost minimization.

LISTEN to the interview.

Lines on Wines is an Internet talk show hosted by history professor and wine enthusiast Marji Morgan. For more on this story visit the Lines on Wines blog.

Pictured above: Anne Johansen, Razvan Andonie, and Szilard Vajda (photo credit: Nathalie Kasselis)

Media Contact: Dawn Alford, Public Affairs, 509-963-1484, dawn.alford@cwu.edu.