Sorry -- upon further reflection, I think my suggestion is a bit out of context. The question from mikeoz about the 4th order polynomials got me to thinking about "the spreadsheet" and the math. To which I of course agree -- the curve fit and the polynomial expression is not the model.

My suggestion was in reference to the curve fitting polynomial formula that is used in your google docs spreadsheet at

https://docs.google.com/spreadsheet/ccc?key=0AuvMQbzk5INUdGZScWx6U2lYSEtZVkJuVGJiR19NaXc#gid=0 which translates your model's experimental data into a formula that calculates the percentage completion of fermentation for a series of time and temp steps. That spreadsheet has inputs for up to 10 time/temp steps and then uses the "best fit curve" math for each step to sum up to a total percentage completion and solves for how much starter you need to get there.

I used that same math to make a similar spreadsheet that sums up the percentage completion of time/temp steps from the temperature output of a real time dough temp monitoring probe, so you could track the progress percent to completion and then calculate the remaining predicted time to completion at a given temp based on actual progress since starting the ferment. Data from first trial run here:

https://www.pizzamaking.com/forum/index.php?topic=49858.msg502822#msg502822In this monitoring spreadsheet -- I took one of the constants from the math in the google docs spreadsheet that is used to calculate the percent of starter quantity required and turned it into a variable, calling it "Target Completion Factor" (and using the constant as a default setting). That Target Completion Factor seems to be determining how many times the percent added starter must double in order to grow to that level of fermentation completion. For my first trial run, I used a different starter culture than was used in building the original model -- and noticed that the pH bottomed out at 95% completion and stayed there for the next three hours until it reached 100% completion.

So if on the next trial dough run, I wanted to experiment and adjust my time to completion to hit the point where my pH starts to bottom out (maybe signaling that LAB function is declining -- and maybe the flavor contribution to the dough), I could adjust down that Target Completion Factor to 95% of the default factor and basically reset my completion target in the spreadsheet.

Likewise, my suggestion about being able to change constants in the curve fit polynomials from the monitoring spreadsheet into variables is along those same lines. In the event that someone else has a different set of experimental data, using a different set of starting conditions (like the starter type, or flour type that is malted, or less/more salt, etc) -- they could adjust the variables for the polynomial to match the best fit curve from their own experimental data and the monitoring spreadsheet would automatically adapt its calculation of percent completion to match (without changing the spreadsheet formulas).

I am not suggesting anything to change the model, your spreadsheet or question the underlying math. My experiment in real time monitoring is simply adapting your math and your work to provide feedback from the actual progress and dough temps over time during the fermentation.