Variation of phenotypic and physiological traits of Robinia pseudoacacia L. from 20 provenances

PLoS One. 2022 Jan 5;17(1):e0262278. doi: 10.1371/journal.pone.0262278. eCollection 2022.

Abstract

To select elite Robinia pseudoacacia L. germplasm resources for production, 13 phenotypes and three physiological indicators of 214 seedlings from 20 provenances were systematically evaluated and analyzed. The leaf phenotypic and physiological coefficients of variation among the genotypes ranged from 3.741% to 19.599% and from 8.260% to 42.363%, respectively. The Kentucky provenance had the largest coefficient of variation (18.541%). The average differentiation coefficients between and within provenances were 34.161% and 38.756%, respectively. These close percentages showed that R. pseudoacacia presented high genetic variation among and within provenances, which can be useful for assisted migration and breeding programs. Furthermore, based on the results of correlations, principal component analysis and cluster analysis, breeding improvements targeting R. pseudoacacia's ornamental value, food value, and stress resistance of were performed. Forty and 30 excellent individuals, accounting for 18.692% and 14.019%, respectively, of the total resources. They were ultimately screened, after comprehensively taking into considering leaf phenotypic traits including compound leaf length, leaflet number and leaflet area and physiological characteristics including proline and soluble protein contents. These selected individuals could provide a base material for improved variety conservation and selection.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Kentucky
  • Phenotype
  • Plant Breeding / methods
  • Plant Leaves / genetics
  • Plant Leaves / metabolism
  • Plant Leaves / physiology
  • Robinia / genetics*
  • Robinia / metabolism
  • Robinia / physiology*
  • Seedlings / genetics
  • Seedlings / physiology

Grants and funding

Qi Guo: Youth Science Foundation of Henan Province (202300410136), Yun Li: National Nature Science Foundation of China (31570677), Yun Li: National Key R&D Program of China (2017YFD0600503), Yun Li: National Forestry and Grassland Administration of Science and Technology Development Center Project (2016007).