Analyze PSII Signal¶
Extract Fv/Fm data of objects.
plantcv.fluor_fvfm(fdark, fmin, fmax, mask, bins=256)
returns PSII analysis images (Fv image, Fv/Fm histogram)
- fdark - image object, grayscale
- fmin - image object grayscale
- fmax - image object, grayscale
- mask - binary mask of selected contours
- bins - number of grayscale bins (0-256 for 8-bit images and 0 to 65,536), if you would like to bin data, you would alter this number (default bins=256)
- Used to extract fv/fm per identified plant pixel.
- Generates histogram of fv/fm data.
- Generates fv/fm image.
- Data automatically gets stored into the Outputs class. Users can look at the data collected at any point during the workflow by using pcv.print_results which prints all stored data to a .json file.
- Example use:
- Output data stored: Summary of Output Observations
from plantcv import plantcv as pcv # Set global debug behavior to None (default), "print" (to file), # or "plot" (Jupyter Notebooks or X11) pcv.params.debug = "print" # Analyze Fv/Fm fvfm_images = pcv.fluor_fvfm(fdark, fmin, fmax, kept_mask, 256) # Store the two images fv_im g= fvfm_images fvfm_his = fvfm_images # Pseudocolor the Fv/Fm image pseudo_img = pcv.pseudocolor(gray_img=fv_img, mask=kept_mask)
Histogram of Fv/Fm values
Pseudocolored output image based on Fv/Fm
The grayscale Fv/Fm image (returned to analysis_image) can be used with the pcv.visualize.pseudocolor function which allows the user to pick a colormap for plotting.