Article Information
History
- December 3, 2021.
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Author Information
- 1Division of Plant and Crop Science, School of Biosciences, University of Nottingham, Sutton Bonington Campus, LE12 5RD
- 2Advanced Data Analysis Centre, University of Nottingham, Sutton Bonington Campus, LE12 5RD
- ↵*Corresponding author: erik.murchie{at}nottingham.ac.uk
Author contributions: SBC project conception, acquisition of stomatal peels and microscopy images, image annotation for machine learning training set, statistical analysis and biological advice for HS. HS generation of automated stomatal counting algorithm and software.
EHM and SM project conception, guidance and advice.
Posted December 03, 2021.
Stomata Detector: High-throughput automation of stomata counting in a population of African rice (Oryza glaberrima) using transfer learning
