Coffee Data Science
Coffee Color Analysis by DiFluid Omni
Quantifying color
DiFluid released the Omni a few months ago, and they sent me one to play around with. It can measure both particle distribution and coffee color, specifically Agtron. This is a standard color measurement for roasters to quantify how dark a roast is, but the common tools are over a thousand dollars. At less than $1,000, the Omni has a chance to disrupt.
I haven’t had a change to compare it to other Agtron devices (coming soon), but I could compare repeatability. I’m excited that it gives a color distribution, not just one number. So let’s take a look at see how repeatable this device is.
All these tests were done using the same bean, so the device could function differently with other roasts. Each reading gives the mean, standard deviation, and then a histogram based on -30, -20, -10, 10, 20, and 30 from the mean value. This was a bit challenging because it made comparing these histograms more difficult.
Repeatability
First, I looked at repeatability tests. I explored a single dose, mixing the single dose between readings, using multiple (different) beans from the same bag, and ground coffee.
There was some variable, but not a great deal. We can look at the individual tests centered by the average.
Top vs Bottom
I wanted to understand the impact of the top vs the bottom of the bean.
These results show quite a bit of shift for the mix especially in terms of a distribution.
Grounds: Fluffy vs Tamped
I did a series of tests where I was measuring color for every shot after tamping the puck. I wanted to understand how the measurement differed compared to fluffy grounds (suggested use case by DiFluid), so I did a small sample. The average color stayed about the same, but the standard deviation (STD) was much higher for the fluffy grounds.
Looking at a single coffee grind, the tamped measurement tightens the curve.
All the data shows a similar trend of tighter distributions.
Using the Omni to measure color was very interesting and fast. I need to get another Agtron device to compare measurements because the cost of the device is very reasonable even for a home barista like me. The device has a nice size, and while I don’t like the way the data is presented using offsets from the mean, maybe the raw data exposed in a phone app would resolve that difficulty.
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Further readings of mine:
My Second Book: Advanced Espresso
My First Book: Engineering Better Espresso
Omni didn’t offer payment or even ask explicitly for a review. We have had a relationship before their two refractometers came out, and they also sent me one to test. I’m very interested in these tools for what they could contribute for coffee science, and I believe data on their performance will speak to that end. They also showed me a demo before their release of the Omni and asked for feedback. I get no financial contribution from them and no profits from their devices sold.
