High-Throughput Seed Phenotyping with James Clohessy

Published: June 21, 2019, 3:45 a.m.

\u201cA Low-Cost Automated System for High-Throughput Phenotyping of Single Oat Seeds\u201d with James Clohessy.

A Rube Goldberg machine is a machine intentionally designed to complete a simple task using overly complicated steps. James Clohessy and his team are doing just the opposite. Using machine learning, web cameras, open software, and photogrammetry techniques, they\u2019re developing low cost, high-throughput, high efficiency phenotyping systems. With these systems, researchers can save hours of time that would normally be spent on taking individual seed measurements by hand, such as height, width, and color, all while gaining greater detail about the seed such as volume and density.

Listen in to learn more about James\u2019 new system as well as:

  • What are phenotyping and photogrammetry?
  • What are some of the applications of knowing seed size, color, and weight?
  • What are some of the limitations of high-throughput phenotyping?
  • What are some of the future applications of these machine learning systems?

If you would like more information about this topic, this episode\u2019s paper is available here: https://doi.org/10.2135/tppj2018.07.0005\xa0

This paper is always freely available.

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Contact us at podcast@sciencesocieties.org or on Twitter @FieldLabEarth if you have comments, questions, or suggestions for show topics, and if you want more content like this don\u2019t forget to subscribe.

If you would like to reach out to James, you can find him here:
jameswclohessy@gmail.com
https://www.linkedin.com/in/jameswclohessy/
@ufifasnfrec

Resources

CEU Quiz: http://www.agronomy.org/education/classroom/classes/814\xa0

Cornell Plant Breeding and Genetics Section: https://plbrgen.cals.cornell.edu/

Paul Armstrong: https://www.ars.usda.gov/plains-area/mhk/cgahr/spieru/people/paul-armstrong/

Dr. Guo\u2019s Easy PPC program: http://park.itc.u-tokyo.ac.jp/Field-Phenomics/ninolab/PhenotypingTools/EasyPCC.html

HeatSync Labs: https://www.heatsynclabs.org/

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