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bioRxiv · 10.1101/2023.01.18.524552

Early root phenotyping in sweetpotato (Ipomoea batatas L.) uncovers insights into root system architecture variability

Abstract

BackgroundWe developed a novel, non-destructive, expandable, ebb and flow soilless phenotyping system to deliver a capable way to study early root system architectural traits in stem derived adventitious roots of sweetpotato (Ipomoea batatas L.). The platform was designed to accommodate up to 12 stems in a relatively small area for root screening. This platform was designed with inexpensive materials and equipped with an automatic watering system. MethodsTo test this platform, we designed a screening experiment for root traits using two contrasting sweetpotato genotypes, Covington and NC10-275. We monitored and imaged root growth, architecture, and branching patterns every five days up to 20 days. ResultsWe observed significant differences in both architectural and morphological root traits for both genotypes tested. After 10 days, root length, surface root area, and root volume were higher in NC10-275 compared to Covington. However, average root diameter and root branching density were higher in Covington. ConclusionThese results validated the effective and efficient use of this novel root phenotyping platforming for screening root traits in early stem-derived adventitious roots. This platform allowed for monitoring and 2D imaging root growth over time with minimal disturbance and no destructive root sampling. This platform can be easily tailored for abiotic stress experiments, permit root growth mapping and temporal and dynamic root measurements of primary and secondary adventitious roots. This phenotyping platform can be a suitable tool for examining root system architecture and traits of clonally propagated material for a large set of replicates in a relatively small space. SubjectsPlant Science, Agricultural Science

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BibTeXRIS

Duque, L. O.. 2023-01-18. Early root phenotyping in sweetpotato (Ipomoea batatas L.) uncovers insights into root system architecture variability. https://doi.org/10.1101/2023.01.18.524552

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