Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2023 Oct 2;5:0098. doi: 10.34133/plantphenomics.0098

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

Copyright © 2023 Junfeng Chen et al.

Exclusive licensee Nanjing Agricultural University. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY 4.0).

PMC Copyright notice

Fig. 2. — Phenotyping of S. miltiorrhiza root based on scanning images of the whole root system. (A) The workflow used for root phenotyping and data analysis. High-throughput imaging data from the WinRHIZO scanning system were imported and processed using WinRHIZO and RhizoVision. The extracted phenotypic traits were further evaluated for biomass estimation and RSA study. (B) The distribution of parameters related to the biomass of S. miltiorrhiza roots. (C) Linear regression analysis between real biomass (Fresh weight and Dry weight) and extracted parameters (Total Length, Total Surface, and Total Volume). (D) K-means clustering of S. miltiorrhiza roots samples (n = 92) according to the diameter ranges of each root branch. The root model represented the typical root structure among each cluster. The bar represented the size of each root model. (E) The importance evaluation of phenotypic traits according to the K-means clustering using the random forest model.