RPT: An integrated root phenotyping toolbox for segmenting and quantifying root system architecture.

Abstract

Summary The dissection of genetic architecture for rice root system is largely dependent on phenotyping techniques, and high‐throughput root phenotyping poses a great challenge. In this study, we established a cost‐effective root phenotyping platform capable of analysing 1680 root samples within 2 h. To efficiently process a large number of root images, we developed the root phenotyping toolbox (RPT) with an enhanced SegFormer algorithm and used it for root segmentation and root phenotypic traits. Based on this root phenotyping platform and RPT, we screened 18 candidate (quantitative trait loci) QTL regions from 219 rice recombinant inbred lines under drought stress and validated the drought‐resistant functions of gene OsIAA8 identified from these QTL regions. This study confirmed that RPT exhibited a great application potential for processing images with various sources and for mining stress‐resistance genes of rice cultivars. Our developed root phenotyping platform and RPT software significantly improved high‐throughput root phenotyping efficiency, allowing for large‐scale root trait analysis, which will promote the genetic architecture improvement of drought‐resistant cultivars and crop breeding research in the future.

Plant phenotyping relevance

根系画像のセグメンテーションと形質定量を行う高スループット基盤およびRPTソフトウェアの開発が研究の中心であり、植物フェノタイピング手法に該当する。

Code and data availability

The paper explicitly states that the RPT source code is publicly available on GitHub and the root training label images are available on Google Drive, both with explicit availability language and URLs matching allowed_urls entries.