{"title":"Phenotyping of <i>Salvia miltiorrhiza</i> Roots Reveals Associations between Root Traits and Bioactive Components.","authors":"Junfeng Chen, Yun Wang, Peng Di, Yulong Wu, Shi Qiu, Zongyou Lv, Yuqi Qiao, Yajing Li, Jingfu Tan, Weixu Chen, Ma Yu, Ping Wei, Ying Xiao, Wansheng Chen","doi":"10.34133/plantphenomics.0098","DOIUrl":null,"url":null,"abstract":"<p><p>Plant phenomics aims to perform high-throughput, rapid, and accurate measurement of plant traits, facilitating the identification of desirable traits and optimal genotypes for crop breeding. <i>Salvia miltiorrhiza</i> (Danshen) roots possess remarkable therapeutic effect on cardiovascular diseases, with huge market demands. Although great advances have been made in metabolic studies of the bioactive metabolites, investigation for <i>S</i>. <i>miltiorrhiza</i> roots on other physiological aspects is poor. Here, we developed a framework that utilizes image feature extraction software for in-depth phenotyping of <i>S</i>. <i>miltiorrhiza</i> roots. By employing multiple software programs, <i>S. miltiorrhiza</i> roots were described from 3 aspects: agronomic traits, anatomy traits, and root system architecture. Through <i>K</i>-means clustering based on the diameter ranges of each root branch, all roots were categorized into 3 groups, with primary root-associated key traits. As a proof of concept, we examined the phenotypic components in a series of randomly collected <i>S</i>. <i>miltiorrhiza</i> roots, demonstrating that the total surface of root was the best parameter for the biomass prediction with high linear regression correlation (<i>R</i><sup>2</sup> = 0.8312), which was sufficient for subsequently estimating the production of bioactive metabolites without content determination. This study provides an important approach for further grading of medicinal materials and breeding practices.</p>","PeriodicalId":20318,"journal":{"name":"Plant Phenomics","volume":null,"pages":null},"PeriodicalIF":7.6000,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545446/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Phenomics","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.34133/plantphenomics.0098","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
Abstract
Plant phenomics aims to perform high-throughput, rapid, and accurate measurement of plant traits, facilitating the identification of desirable traits and optimal genotypes for crop breeding. Salvia miltiorrhiza (Danshen) roots possess remarkable therapeutic effect on cardiovascular diseases, with huge market demands. Although great advances have been made in metabolic studies of the bioactive metabolites, investigation for S. miltiorrhiza roots on other physiological aspects is poor. Here, we developed a framework that utilizes image feature extraction software for in-depth phenotyping of S. miltiorrhiza roots. By employing multiple software programs, S. miltiorrhiza roots were described from 3 aspects: agronomic traits, anatomy traits, and root system architecture. Through K-means clustering based on the diameter ranges of each root branch, all roots were categorized into 3 groups, with primary root-associated key traits. As a proof of concept, we examined the phenotypic components in a series of randomly collected S. miltiorrhiza roots, demonstrating that the total surface of root was the best parameter for the biomass prediction with high linear regression correlation (R2 = 0.8312), which was sufficient for subsequently estimating the production of bioactive metabolites without content determination. This study provides an important approach for further grading of medicinal materials and breeding practices.
期刊介绍:
Plant Phenomics is an Open Access journal published in affiliation with the State Key Laboratory of Crop Genetics & Germplasm Enhancement, Nanjing Agricultural University (NAU) and published by the American Association for the Advancement of Science (AAAS). Like all partners participating in the Science Partner Journal program, Plant Phenomics is editorially independent from the Science family of journals.
The mission of Plant Phenomics is to publish novel research that will advance all aspects of plant phenotyping from the cell to the plant population levels using innovative combinations of sensor systems and data analytics. Plant Phenomics aims also to connect phenomics to other science domains, such as genomics, genetics, physiology, molecular biology, bioinformatics, statistics, mathematics, and computer sciences. Plant Phenomics should thus contribute to advance plant sciences and agriculture/forestry/horticulture by addressing key scientific challenges in the area of plant phenomics.
The scope of the journal covers the latest technologies in plant phenotyping for data acquisition, data management, data interpretation, modeling, and their practical applications for crop cultivation, plant breeding, forestry, horticulture, ecology, and other plant-related domains.