Location: Plant Science ResearchTitle: Phenotyping seedlings for selection of root system architecture in alfalfa (Medicago sativa L.)
|BUCCIARELLI, BRUNA - University Of Minnesota|
|AO, SAMADANGLA - University Of Minnesota|
|CAO, YUANYUAN - University Of Minnesota|
|MONTEROS, MARIA - Noble Research Institute|
|TOPP, CHRISTOPHER - Danforth Plant Science Center|
|Samac, Deborah - Debby|
Submitted to: Plant Methods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/30/2021
Publication Date: 12/7/2021
Citation: Bucciarelli, B., Xu, Z., Ao, S., Cao, Y., Monteros, M., Topp, C., Samac, D.A. 2021. Phenotyping seedlings for selection of root system architecture in alfalfa (Medicago sativa L.). Plant Methods. 7:125. https://doi.org/10.1186/s13007-021-00825-3.
Interpretive Summary: Roots of plants are vital for taking up water and nutrients from the soil and in alfalfa they are important for nitrogen fixation and for storing carbohydrates that are needed for regrowth in spring and after each harvest. Previous work showed that increasing the number of roots in alfalfa increases herbage yield. However, identifying plants with the desired type of root system is time-consuming and subject to human error. A method was developed that reduces the time required to distinguish root types from 22 weeks to 2 weeks. Several specific root characteristics were associated with a root system with more branched roots that can be increased through selective breeding. This method will be useful for plant breeders to develop plants for particular environmental conditions, for enhancing carbon sequestration, and for enhancing productivity in elite cultivars.
Technical Abstract: 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 we developed methods 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. 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. Our 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.