A robot-assisted imaging pipeline for tracking the growths of maize ear and silks in a high-throughput phenotyping platform.

Nicolas BrichetChristian FournierOlivier TurcOlivier StraussSimon ArtzetChristophe PradalClaude WelckerFrançois Tardieu Llorenç Cabrera-Bosquet

Published in: Plant methods (2017)

The pipeline presented here, which combines computer vision, machine learning and robotics, provides a powerful tool for large-scale genetic analyses of the control of reproductive growth to changes in environmental conditions in a non-invasive and automatized way. It is available as Open Source software in the OpenAlea platform.

Keyphrases

high throughput
robot assisted
machine learning
minimally invasive
single cell
high resolution
deep learning
human health
big data
copy number
risk assessment
climate change
mass spectrometry
photodynamic therapy
fluorescence imaging