Greetings!

I hope you are doing well and in the full swing of summer.  Not sure about you, but it's hard for me to believe we are knocking on the door of August.

Below are the details of the August 4th AgBioData webinar, we look forward to seeing you and hope your schedule allows you to join us next Wednesday!

Darwin Campbell, AgBioData coordinator
on behalf of the AgBioData steering committee

Jacqueline Campbell
Ethalinda Cannon
Laurel Cooper
Lisa Harper
Eva Huala
Sook Jung
Dorrie Main
Monica Poelchau
Meg Staton
Leonore Reiser
Marcela K. Tello-Ruiz
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Wednesday, August 4th, 2021
1 hour | 1P ET | 12P CT | 11A MT | 10A PT
Find your local time: https://bit.ly/3acKzjB

https://iastate.zoom.us/j/91906292999?pwd=NlZrK0lUNjlPRVZxZ0JBSlB4ZXF0QT09
Or, go to https://iastate.zoom.us/join and enter meeting ID: 919 0629 2999 and password: 294711
 
Join from dial-in phone line:
    Dial: +1 312 626 6799 or +1 646 876 9923
    Meeting ID: 919 0629 2999
    +13126266799,,91906292999,,,,,,0#,,294711
    +16468769923,,91906292999,,,,,,0#,,294711
    Participant ID: Shown after joining the meeting
    International numbers available: https://iastate.zoom.us/u/aJkMOd9A

Interactions between the phenomics and database communities

Noah Fahlgren and Malia Gehan
Donald Danforth Plant Science Center

High-throughput phenotyping has emerged as a promising area in plant, animal, and agricultural sciences that brings together researchers from life sciences, engineering, computer science, data science, mathematics, and other research fields to develop technologies for rapidly and accurately measuring phenotypes using robotics, imaging, and other tools. High-throughput phenotyping can be done at different scales, from cellular to ecological, typically using image-based approaches for data collection and analysis. The development of computer vision and machine learning approaches to extract biologically meaningful measurements from images, including physical, physiological, morphological, and qualitative properties of crops and livestock, is a major activity within the field. Phenotype datasets can be used for a variety of purposes, but in conjunction with large genomic datasets, are a powerful tool for linking phenotype to genotype, training genomic prediction models, and other approaches that integrate genetic, phenotypic, and environmental datasets. 

We will introduce our efforts to develop PlantCV (https://plantcv.danforthcenter.org/), an open-source platform for image-based plant phenotyping, and discuss opportunities for collaboration between the phenomics and database communities.

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Past webinars can be found here.