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)
- Parameters:
- 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)
- Context:
- Used to extract fv/fm per identified plant pixel.
- Generates histogram of fv/fm data.
- Generates fv/fm image.
- Example use:
- Output data stored: Data ('fvfm_hist', 'fvfm_hist_peak', 'fvfm_median', 'fdark_passed_qc') automatically gets stored to the
Outputs
class when this function is ran. These data can always get accessed during a workflow (example below). Summary of Output Observations
Fdark image
Fmin image
Fmax image
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)
# Access data stored out from fluor_fvfm
fvfm_median = pcv.outputs.observations['fvfm_median']['value']
# Store the two images
fv_im g= fvfm_images[0]
fvfm_his = fvfm_images[1]
# 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.