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Coffee Data Science

Fully Extracting Coffee from Espresso

Interesting data in preparation for another experiment

4 min readApr 26, 2022

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As I was preparing for an experiment, I was curious if I could fully extract a puck. My aim was to produce spent coffee for another experiment, but previous experiments always showed some solubles were still left. So I took some measurements as I made this spent coffee and put a lot of water through the puck.

Equipment/Technique

Espresso Machine: Decent Espresso Machine

Coffee Grinder: Niche Zero

Coffee: Home Roasted Coffee, medium (First Crack + 1 Minute)

Shot Preparation: Staccato Tamped

Pre-infusion: Long, ~25 seconds

Infusion: Pressure Pulsing

Filter Basket: 20g VST

Other Equipment: Atago TDS Meter, Acaia Pyxis Scale

Shots

I started with a shot:

All images by author

Then I ran a flat flow profile of 2, 4, 6, and 8 ml/s in four stages poured into 3 cups.

The results looked creamy.

Three cups and their progressions

The final product looked like a few light beers.

The puck looked very strange. Usually, the color is even, but now, the color on top was darker than on the bottom.

Upside-down spent puck.

So I put this puck back into the basket, and I ran more water through it.

Less water came out of course.

So I took the puck out, mixed it up, and tamped it back into the basket.

All of this was aimed to get all of the solubles out of the coffee.

However, the results were strange.

Collecting Data

I collected TDS for each stage.

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).

This measure can tell us how much coffee was extracted. Typically, 30% of coffee is soluble, but more kept coming out of the puck.

I thought about continuing, but I didn’t need to for my experiments. I was down to 0% TDS, and I wanted to move onto the bigger experiment. However, this data was so interesting and compelling because it went against what I assumed was the maximum extraction. The data also suggests that there are microchannels causing some pieces of coffee to not be exposed to enough water flow for extraction.

If you like, follow me on Twitter, 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 Future Book

My Links

Collection of Espresso Articles

A Collection of Work and School Stories

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TDS Archive
TDS Archive

Published in TDS Archive

An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

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.

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