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Coffee Data Science

Fast vs Slow Auger for Coffee Grinding

Bean feed data

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I wanted to look at the slow and fast augers for the Zerno grinder. From the data I pulled, I prefer the slow auger.

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Slow Auger in Black, Fast Auger in Silver

Metrics of Performance

I used two sets of metrics for evaluating the differences between techniques: Final Score and Coffee Extraction.

Final score is the average of a scorecard of 7 metrics (Sharp, Rich, Syrup, Sweet, Sour, Bitter, and Aftertaste). These scores were subjective, of course, but they were calibrated to my tastes and helped me improve my shots. There is some variation in the scores. My aim was to be consistent for each metric, but some times the granularity was difficult.

Total Dissolved Solids (TDS) is measured using a refractometer, and this number combined with the output weight of the shot and the input weight of the coffee is used to determine the percentage of coffee extracted into the cup, called Extraction Yield (EY).

Shot Data

I pulled 19 shot pairs across 15 roasts, and the data showed the fast auger under performed on taste.

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I looked at adjusting the grind setting slightly down to 175 um burr gap instead of my usual 200 um, but the results were a wash.

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The slow auger won across the board of taste metrics.

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There wasn’t much difference on TDS or EY, but those being nearly constant is good.

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All the taste differences were statistically significant using a two-tailed paired t-test.

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These tests have helped identify the optimal auger, and now I can move forward with some burr testing.

If you like, follow me on YouTube and Instagram where I post videos of espresso shots on different machines and espresso related stuff. You can also find me on LinkedIn. You can also follow me on Medium and Subscribe.

Further readings of mine:

My Second Book: Advanced Espresso

My First Book: Engineering Better Espresso

My Links

Collection of Espresso Articles

A Collection of Work and School Stories

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Robert McKeon Aloe
Robert McKeon Aloe

Written by Robert McKeon Aloe

I’m in love with my Wife, my Kids, Espresso, Data Science, tomatoes, cooking, engineering, talking, family, Paris, and Italy, not necessarily in that order.