<scp>RPT</scp>: An integrated root phenotyping toolbox for segmenting and quantifying root system architecture

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.

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Publication Details

Journal
Plant Biotechnology Journal
Published
2025-03-12
DOI
https://doi.org/10.1111/pbi.70040
Citations
10
Primary Topic
Rice Cultivation and Yield Improvement
Type
article
Field-Weighted Citation Impact
17.50

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article

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

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10 citations
Plant Biotechnology Journal
Rice Cultivation and Yield Improvement
17.50
article

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

Wanneng Yang, Jianglin Wang, Shouqi Xie, Yongyue Chang, Qiaojun Lou, Xin Wang, Weikun Li, Yunyu Chen, Jiawei Shi
article en
10 citations

Abstract

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 Biotechnology JournalVol. 23(6)
Huazhong Agricultural University (CN), ZheJiang Academy of Agricultural Sciences (CN), Shanghai Agrobiological Gene Center (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 1%
Rice Cultivation and Yield Improvement
17.50
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