PreviouslyI have looked at flow parameters for how they correlate with a good espresso image. I didn’t find anything new, but then I made a breakdown of the type of shot and started seeing interesting variables. One of the confusing variables in my data is in many types of layers, and they have a difference in flow.
I use two metrics to assess the differences between the techniques: the end result and the coffee intake.
The final result on Average 7 scorecard scorecard (sharp, rich, syrupy, sweet, sour, bitter, and aftertaste). These scores were subjective, of course, but they were calibrated to my taste and helped me improve my shots. There is some variation in the points. My goal was to be consistent across every meter, but sometimes accuracy was difficult.
Total insoluble solids (TDS) is measured with a refractometer, and this figure, combined with the starting weight of the shot and the feed weight of the coffee, is used to determine the percentage of coffee extracted into the cup.
I’ve put together some metrics that I thought were interesting for flow. I divided the pre-infusion (PI) and the infusion. I was not looking at the pulsating pressure, but the smoothed flow.
Before the infusion, I cut it in half because typically the PI starts slowly and then accelerates. For the infusion, I looked at the upward and downward trends, as shown below, like my lever machine, actively regulating the flow throughout the shot.
In addition, I looked at the time to get 1 g of coffee as well as 2, 3, 4, 5, 6, 7, and 8 grams.
Filter cover time (TCF) and T10 (time to 10 ml) are two variables that I have used for almost a year to monitor flow differences at a higher level. There is a good correlation between them and a good espresso picture.
In me previous work, I explained the variables that I derived from the flow logs. The most important metric used in this work is correlation.
Correlation is a metric to say how similar two variables are to each other. A high correlation does not mean that one variable causes another variable, but that both variables go up or down as things change. The correlation can be positive (same trend) or negative (inverse trend). 0 means no correlation.
Here is the first breakdown by shot type: