Hi! I wonder when I should calibrate the rotator and stir? For the stir bar, I think I should calibrate it every time before the experiment, since I took the vial for the autoclave. For waste and media rotators, I guess I don’t need to calibrate except for taking the tubes from the rotators, even though I took out the charge.
With all calibrations it’s a question of when you anticipate it will have gone out of calibration. So there isn’t a fixed time interval. Measuring how far each system goes out of calibration by when should help determine optimal calibration intervals for the future.
I would suggest that for simple calibrations, like the stirrer, you may as well do it before starting each experiment. If you note down the different values each time, and find that they never change, you could probably then increase the calibration interval. You would certainly need to do it again if you change anything significant. For the stirrer this would include changing the magnetic flea, vial, fan height, power supply to the Raspberry Pi or Pioreactor Hat, etc.
For the peristaltic pumps and other more involved calibrations. I would, at least initially, do the same and calibrate before every experiment. If you find that your calibration curves don’t change between experiments, then you could perhaps increase the interval. Unfortunately my experience isn’t going to be of much use here, as we moved from silicone tubing to Flexeline 135C. But yes, if you take the tubing out of the peristaltic pump, you should always recalibrate. Additionally, if you have a particularly long run, you should check the calibration at the end of the experiment, so you can determine if tubing wear has impacted it during the course of the experiment.
The good news is that, since this CARMA Hub project is all about repeatability, your calibration checks could actually be publishable data. A key point of investigation could be system variability. So if you check calibration before and after each run, you can get data that may be able to show causes or instability, or demonstrate stability. This could result in identification of potential improvements to increase repeatability.