Computer vision and machine learning enabled soybean root phenotyping pipeline
Abstract Background Root system architecture (RSA) traits are of interest for breeding selection; however, measurement of these traits is difficult, resource intensive, and results in large variability. The advent of computer vision and machine learning (ML) enabled trait extraction and measurement...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2020-01-01
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Series: | Plant Methods |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13007-019-0550-5 |