Coffee Data Science
Center vs Side Espresso Extraction Data
A dense dataset to dissect
Recently, a sizable data became available across a larger variety of espresso shots and grinders where the author collected 57 shot pairs across two grinders, two filter baskets, two groupheads, and two shot profile types with multiple shots for each variant.
I previously looked at the filtered vs unfiltered TDS samples from this dataset, and now I look at the rest of the data to see what insights could be made.
Definitions
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). Typically, one aims for 18% to 22% extraction or some times higher, but it is difficult to get more than 30% EY.
Traditional vs Turbo
The author compared a traditional shots compared to turbo shots. Turbo shots were faster (15 seconds at a coarser grind) while traditional shots were slower (40 seconds at a finer grind). Some of the data is lower in EY, but some is on par. It is difficult to draw any insight here.
Filter Baskets
He compared an Sworks basket to a VST18 basket, and these results were similar in being mixed.
Puck Screen
He compared putting a puck screen on top or not, but we can look at this data another way.
By pairing the best shots with the best shots, we can look at just EY and split the data across the baskets. For the Sworks, the puck screen didn’t seem to impact results, but for VST, the results got worse.
Grouphead
The general data for grouphead had similar issues. There was Teflon (the new Decent grouphead) and the original Brass.
We can also pair these shots with the best performers for each subset paired with each other. The Teflon looks to do better.
Outside vs Center Cut
He used cookie cutters to cut the center of the spent puck from the outside. He then dried both of these for 24 hours at 250F. He then used a routine with boiling water to measure how many solubles were still left, and from here, he could calculate how much the center contributed to extraction vs the side.
The aim is to answer the question: are the sides extracting faster than the center.
For all of these shots, a scatter plot is a great way to represent the data.
For the Superjolly M64, it seems the outside and center extracted similarly. For the Niche Zero, it seems the outside was under extracted.
This data set was so interesting to me because there are not too many big shot data sets with lots of variables to explore. More cuts can be made to this data, and I’m sure some of the more interesting experiments can be replicated at a larger scale.
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Further readings of mine:
My Second Book: Advanced Espresso
My First Book: Engineering Better Espresso
