Unlocking the potential of plant phenotyping data through integration and data-driven approaches-Reference-Cited by-同舟云学术

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Unlocking the potential of plant phenotyping data through integration and data-driven approaches

Published:2017-08 Issue: Volume:4 Page:58-63
ISSN:2452-3100
Container-title:Current Opinion in Systems Biology
language:en
Short-container-title:Current Opinion in Systems Biology

Author:

Coppens Frederik,Wuyts Nathalie,Inzé Dirk,Dhondt Stijn

Funder

European Research Council

Ghent University

European Commission

Publisher

Elsevier BV

Subject

Applied Mathematics,Computer Science Applications,Drug Discovery,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation

Reference40 articles.

1. Cell to whole-plant phenotyping: the best is yet to come;Dhondt;Trends Plant Sci,2013

2. Phenomics – technologies to relieve the phenotyping bottleneck;Furbank;Trends Plant Sci,2011

3. Lights, camera, action: high-throughput plant phenotyping is ready for a close-up;Fahlgren;Curr Opin Plant Biol,2015

4. Field high-throughput phenotyping: the new crop breeding frontier;Araus;Trends Plant Sci,2014

5. High-resolution time-resolved imaging of in vitro Arabidopsis rosette growth;Dhondt;Plant J,2014

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2. Rosette Plant Centre Detection and Tracking Using YOLO: An Efficient Deep Learning Approach;2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI);2024-04-13

3. A comparative study of plant phenotyping workflows based on three-dimensional reconstruction from multi-view images;2024-03-25

4. AgTC and AgETL: open-source tools to enhance data collection and management for plant science research;Frontiers in Plant Science;2024-02-21

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