Year: 2026
Type: article
Abstract: Introduction: Alkaline stress poses a major challenge to crop productivity, often causing more severe physiological damage than saline stress alone. Maize is particularly sensitive to alkaline conditions, which significantly inhibit germination and early growth. The establishment of accurate evaluation systems for alkali tolerance is therefore crucial for the development of resilient cultivars. Methods: A total of 42 maize germplasm accessions were evaluated under simulated alkaline stress (100 mM) during germination. A comprehensive analytical framework integrating principal component analysis, membership function analysis, stepwise regression, cluster analysis, and discriminant analysis was used to assess alkalinity tolerance. The Lindeman-Merenda-Gold method was further employed to quantify the relative contribution of each morphological trait to the comprehensive alkali tolerance score. Results: value, the maize accessions were classified into five tolerance groups. Trait contribution analyses consistently indicated the germination index (GI) and the shoot dry weight (SDW) as the strongest determinants of tolerance, with root length (RL) and root fresh weight (RFW) also playing notable roles. These indicators form a reliable basis for the screening of alkali-tolerant maize germplasm, providing a foundation for future refinement of the evaluation system through physiological or molecular approaches. Discussion: This integrated evaluation system effectively distinguishes maize germplasm by alkali tolerance level and identifies key morphological determinants. The findings provide a scientific basis for germplasm screening and breeding of alkali-tolerant maize materials, contributing to sustainable agricultural production in saline-alkaline environments.
Source: Frontiers in Plant Science
Authors: Zhuyun Pan, Zhiqiang Ge, Fengming Gao, Man Ao, Yixin Guan
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,801
Funder: Chinese Academy of Sciences
OpenAlex ID: W7122687805