4D Structural root architecture modeling from digital twins by X-Ray Computed Tomography.

ABSTRACT:

Background

Breakthrough imaging technologies may challenge the plant phenotyping bottleneck regarding marker-assisted breeding and genetic mapping. In this context, X-Ray CT (computed tomography) technology can accurately obtain the digital twin of root system architecture (RSA) but computational methods to quantify RSA traits and analyze their changes over time are limited. RSA traits extremely affect agricultural productivity. We develop a spatial-temporal root architectural modeling method based on 4D data from X-ray CT. This novel approach is optimized for high-throughput phenotyping considering the cost-effective time to process the data and the accuracy and robustness of the results. Significant root architectural traits, including root elongation rate, number, length, growth

SUBMITTER: Herrero-Huerta M 

PROVIDER: S-EPMC8642944 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature