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.

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

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?

Hello Dan, The link to the video works. However, the link to the tutorial on R and the mixed effect model is not working. I am trying hard to analyze my data. But have no luck till data. Can you suggest how should I go about preprocessing and analyzing my data?

Hi Sanjeev,

the tutorials have been moved since the original post in 2017. All the documentation is now under . Here are also some more specific links from the documentation for data analysis including analysis examples and how to use R with PhotosynQ.

I hope this helps you getting started.

~ Sebastian