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Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks.

Jordan R Ubbens1, Ian Stavness1

  • 1Department of Computer Science, University of SaskatchewanSaskatoon, SK, Canada.

Frontiers in Plant Science
|July 25, 2017
PubMed
Summary

Deep Plant Phenomics is an open-source tool that uses deep learning for plant phenotyping. It helps scientists analyze complex traits and bridge the genotype-to-phenotype gap with pre-trained models and custom training capabilities.

Keywords:
computer visiondeep learningmachine learningmethodsphenotyping

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Area of Science:

  • Plant biology
  • Computational biology
  • Genetics

Background:

  • Bridging the genotype-to-phenotype knowledge gap is crucial in plant science.
  • High-throughput phenotyping requires advanced tools to handle large datasets from imaging sensors.
  • Measuring complex phenotypic traits necessitates innovative computational approaches.

Purpose of the Study:

  • Introduce Deep Plant Phenomics, an open-source deep learning tool for plant phenotyping.
  • Provide pre-trained neural networks for common plant phenotyping tasks.
  • Offer a user-friendly platform for plant scientists to train custom phenotyping models.

Main Methods:

  • Development of an open-source deep learning software tool named Deep Plant Phenomics.
  • Utilization of pre-trained neural networks for established phenotyping tasks.
  • Application of the tool on three plant phenotyping benchmarks for performance evaluation.

Main Results:

  • Achieved state-of-the-art performance in leaf counting tasks.
  • Presented the first published results for mutant classification in *Arabidopsis thaliana*.
  • Reported novel results for age regression tasks in *Arabidopsis thaliana*.

Conclusions:

  • Deep Plant Phenomics offers a valuable resource for plant scientists.
  • The tool facilitates high-throughput analysis of complex plant traits.
  • Enables advancements in understanding genotype-phenotype relationships through accessible deep learning.