Pollen Flow Cytometry Datasets and Classification Models

This database contains flow cytometry measurements for pollen grains from 97 species across 34 genera.
The pollen grains come from floral units collected directly from trees and herbaceous plants in urban area of Montreal, QC, Canada.
Measurements were performed with a CytoFLEX cytometer (Beckam Coulter, Inc.), equipped with three excitation lasers, in blue (λ=488nm), red (λ=640nm) and violet (λ=405nm), 10 dichroic mirrors, bandpass filters and detectors in different wavelength ranges (λ=450/45, 525/40, 610/20, 585/42, 525/40, 690/50, 780/60, 660/10, 712/25 and 780/60 nm) with their respective names: PB450, KO525, Violet610, PE, FITC, PC5.5, PC7, APC, APC-A700, APC-A750. Two other detectors were also used for the size (forward scatter, FSC) and granularity (side scatter, SSC).

Short description of each file :

trainingdataset_genus: Flow cytometry measurements used to train the genus-level classification modeltrainingdataset_species: Flow cytometry measurements used to train the species-level classification modelModelRF_genus: Random Forest classification model trained at the genus level.ModelRF_species: Random Forest classification model trained at the species level.
These data are linked to this article : (link to come when preprint will be published)
Linked Github repository : https://github.com/SarahTardif/Pollen-classification-model