Integrating multivariate selection indices with weighted rank aggregation to identify drought-tolerant Populus simonii × P. nigra F1 progenies

Abstract

Background: Breeding drought-tolerant poplar cultivars necessitates efficient selection strategies that can simultaneously improve multiple traits. This study evaluated the integration of multivariate selection indices with Weighted Rank Aggregation (WRA) to identify superior genotypes in hybrid poplar progenies. Methods: We assessed 372 F1 progenies from three families of Populus simonii × P. nigra under controlled drought stress and well-watered conditions. Data on 16 growth, leaf, and photosynthetic traits were analyzed using four multivariate indices: the Smith-Hazel Index (SHI), FAI-BLUP, and two Multi-Trait Genotype-Ideal Genotype Distance Index (MGIDI) variants. The rankings were integrated using WRA. Results: Genetic parameters revealed high heritability for key growth traits. The selection indices exhibited divergent focus, with SHI showing strong directional selection for growth but sensitivity to multicollinearity, while FAI-BLUP and MGIDI enabled more balanced multi-trait improvements. Most indices were weakly correlated (Spearman’s |r| < 0.2), indicating complementary information. Venn analysis identified genotypes (e.g., C4‑246, E4‑70) performing consistently across multiple indices. The final WRA integration selected robust genotypes, including C2‑65, C4‑210, E4‑115, and E4‑70, which combine drought tolerance with desirable growth and physiological characteristics. Conclusions: Integrating multiple selection indices with WRA provides a powerful and reliable strategy for selecting drought-tolerant poplar genotypes at the seedling stage. This approach effectively balances genetic gains across traits, enhancing the efficiency of breeding programs for stress resilience.