How to interpret data correctly from field?

General Discussion

The parameters (Phi2, PhiNPQ, PhiNO) are dependent on the level of lighting. If you measure plant in the field for several hours, for example from 10 am to 1 pm . (Fore example: Option 1 - in 10.00 am; Option 2 - in 10.20 am .... Option 10 - in 1 pm et all. ) How to correctly interpret data for option 1 and 10? PAR in 10.00 am - 600, but in 1 pm 1600 unit . Phi2 in10 am - 0,45: after 1 pm - 0,25. How to find out the influence of the factor, not the level of illumination?

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Dan TerAvest

Jul 2017

Great question! That is one of the most critical points in any PhotosynQ experiment. Generally speaking, it is best to approach the analysis and interpretation of this data by doing 2 things:

  1. Before analyzing data, you need to set up your data collection so that you collect MultispeQ data from a given plant population over a range of light intensities. This video will provide you with some tips on how to do that.
  2. After you collect your data, you should use a statistical model that accounts for co-variates like light intensity and time of day. Personally, I use a multiple linear regression, a tutorial including the model (in R) and an explanation can be found here. You can also use a mixed effects model

We also have developed packages to download data directly from the PhotosynQ website into R or Python and have R markdown files available for download.

I watched the video. Perhaps more effective will be an attempt to combine, group, and accordingly, compare variants that do not have a statistical difference in the values of the level of illumination (FAR). Or measurements on a sunny or cloudy day). And more. If I shaded them for 20 minutes, will I receive the maximum photosynthetic effect?

Thank you, Dan. Yes, I also use this approach. I think such questions are of interest to all researchers and project participants.