Phenotyping seedlings for selection of root system architecture in alfalfa (Medicago sativa L.)

Bruna Bucciarelli, Zhanyou Xu, Samadangla Ao, Yuanyuan Cao, Maria J. Monteros, Christopher N. Topp, Deborah A. Samac

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Background: The root system architecture (RSA) of alfalfa (Medicago sativa L.) affects biomass production by influencing water and nutrient uptake, including nitrogen fixation. Further, roots are important for storing carbohydrates that are needed for regrowth in spring and after each harvest. Previous selection for a greater number of branched and fibrous roots significantly increased alfalfa biomass yield. However, phenotyping root systems of mature alfalfa plant is labor-intensive, time-consuming, and subject to environmental variability and human error. High-throughput and detailed phenotyping methods are needed to accelerate the development of alfalfa germplasm with distinct RSAs adapted to specific environmental conditions and for enhancing productivity in elite germplasm. In this study methods were developed for phenotyping 14-day-old alfalfa seedlings to identify measurable root traits that are highly heritable and can differentiate plants with either a branched or a tap rooted phenotype. Plants were grown in a soil-free mixture under controlled conditions, then the root systems were imaged with a flatbed scanner and measured using WinRhizo software. Results: The branched root plants had a significantly greater number of tertiary roots and significantly longer tertiary roots relative to the tap rooted plants. Additionally, the branch rooted population had significantly more secondary roots > 2.5 cm relative to the tap rooted population. These two parameters distinguishing phenotypes were confirmed using two machine learning algorithms, Random Forest and Gradient Boosting Machines. Plants selected as seedlings for the branch rooted or tap rooted phenotypes were used in crossing blocks that resulted in a genetic gain of 10%, consistent with the previous selection strategy that utilized manual root scoring to phenotype 22-week-old-plants. Heritability analysis of various root architecture parameters from selected seedlings showed tertiary root length and number are highly heritable with values of 0.74 and 0.79, respectively. Conclusions: The results show that seedling root phenotyping is a reliable tool that can be used for alfalfa germplasm selection and breeding. Phenotypic selection of RSA in seedlings reduced time for selection by 20 weeks, significantly accelerating the breeding cycle.

Original languageEnglish (US)
Article number125
JournalPlant Methods
Volume17
Issue number1
DOIs
StatePublished - Dec 2021

Bibliographical note

Funding Information:
This work was supported by the USDA-NIFA-AFRP (2014-70005-22543); the State Scholarship Fund of China Scholarship Council, and USDA-ARS (5062-12210-002-00D).

Funding Information:
The authors thank Melinda Dornbusch and Ted Jeo for assistance with field experiments and JoAnn Lamb for providing the alfalfa populations. This paper is a joint contribution from the USDA-ARS-Plant Science Research Unit and the Minnesota Agricultural Experiment Station. Mention of any trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U. S. Department of Agriculture. USDA is an equal opportunity provider and employer and all agency services are available without discrimination.

Publisher Copyright:
© 2021, The Author(s).

Keywords

  • Alfalfa
  • Branch root
  • Root system architecture
  • Seedling phenotyping
  • Tap root

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