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AI in winemaking: Dr. Marinda Kruger

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Dr. Marinda Kruger creates magic with her excellent combination of data science skills applied to winemaking


If you were a skilled winemaker, and could now look at it from a data-driven perspective, you would get a lot more information about the wine you are making and why. That is exactly what Dr. Marinda Kruger is able to do. 

When did you first get involved in wine? Tell us about your winemaking career.

After obtaining my Bachelor’s degree in Food Science at Stellenbosch University, I worked as Laboratory and Quality Manager for a very large winery in South Africa. The whole winemaking process had my full attention from the start! 

I did a lot of problem-solving in the winery and read so much about the subject matter and realizing the influence of the winemaker on the process, I decided to continue and do my Masters in Wine biotechnology. I had this urge to learn more and immerse myself in Viticulture and Oenology. It was different then, there were not many women in the wine industry, and I had the drive to prove myself. Also, winemaking suited my creative spirit well as I could not see myself forever in a laboratory, but it laid a very solid foundation and opened many opportunities, for which I will always be very grateful.

I was very interested in the fact that grape composition plays a role in wine quality. My Master's was mainly on assessing grape composition and grape quality and using FT-MIR spectroscopy (then a very new application in this research field). After my Masters, I was promoted to red winemaker for the same winery and later became the Research & Quality Manager as well.

My PhD study followed a few years after the above and by now I was making wine for an international wine company. I was their South African winemaker and had the amazing opportunity to explore the global wine industry.  I stayed with the international wine company for 8 years. Thereafter I joined a producer focusing on higher premium wine, as a business manager and winemaker.

It is with great gratitude that I can say that I am an experienced winemaker who has worked with diverse wine regions around the world, each with its own unique terroir and grape varietals. Further specializing in wine research specifically infrared spectroscopy as an application from grape to bottle as well as the acquired skill set of data analytics and data science.

What prompted your move to Napa? What attracted you to your role at Firstleaf?

This was an opportunity presented to me that I knew only comes once in a lifetime. My experience, skill set, and research have steered me in this direction. I am an experienced winemaker with a high academic qualification using multivariate data analysis (data science). I never thought I would ever use my PhD research knowledge, and that was okay. To my surprise, this position as Director of Winemaking fitted all my years of work like a glove. How could I pass this up? Lucky that the heart of Firstleaf is centered in Napa.

Describe your role at Firstleaf.

I head the winemaking team.  Firstleaf is very different from any wine company I know of. They use data science for customer profiling and match wine styles to fit the profile of each customer. The algorithm has been patented (they have already registered 4 patents). My job here will be to bring the data science team (they are not winemakers) and wine science/winemaking closer together. Using machine learning and AI is all part of this very exciting opportunity. Through using data-driven winemaking and my global winemaking experience I give direction/strategy to the wine portfolio and wine styles and continuous wine quality improvement.


What do you bring to your role at Firstleaf?

Experience, knowledge, maturity.

What are some of the challenges of your job? What are some of the surprises?

My surprise was the extent of technology that Firstleaf uses. It is really a modern high-tech wine company.

Producing high-quality world-class wine on the one side is not a surprise but always keeping a watchful, interpretive analytical data mindset on customer feedback and behaviors, and with great effort circling that back to the primary stage of the business.

Can you describe a typical day at Firstleaf?

There is no typical day. The environment is fast-paced with an innovative culture. We do many wine trails and blending exercises to ensure we offer the best wines for our customers.

What is the process used to select wines for Firstleaf?

It is a long process that starts with the grape grower and producers.  Building mutual trust and solid business relationships is so important.  Transparency in wine production and conveying that to our customers is one of my core values. We source from producers from 12 international countries as well as various wine-making regions in the US.  I am fortunate to know how to establish and build those relationships as this is what I have done in my career.

Your PhD was based on applying data visualization to the winemaking process to predict the optimal stage of fermentation for quality and wine style. Could you please explain that in layman’s terms?

I developed the visualization of alcoholic fermentation using data science techniques and spectroscopy. This enables a quick visual picture of the process. I also demonstrated that one can predict wine quality and or wine style at a very early stage of fermentation. See my resume summary as well.

What is next on the horizon for you?

I want to do groundbreaking data-driven winemaking for Firstleaf which will mean a fully integrated winemaking strategy built on craftsmanship integrated with data science. Fortunate to say we are on our way.

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