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<p>Rice false smut, caused by <i>Ustilaginoidea virens</i>, is a major yield and quality limiting disease in humid rice ecologies. Breeding for durable resistance is constrained by limited stable genetic resistance sources, and is further complicated by pronounced genotype × environment interactions (GEI) and pathogen variability, which cause inconsistent field expression. We hypothesized that rigorous multi-environment evaluations using integrated multi-trait selection models could uncover stable resistance sources that do not compromise grain yield. To test this, an F₆ recombinant inbred line (RIL) population (n = 208) derived from crossing a high yielding susceptible variety (CO43) and a highly resistant donor (RG170) was systematically evaluated for agronomic performance and disease response. Initial screening revealed substantial genetic variability and high heritability (&gt; 0.60). Consequently, 31 superior RILs were advanced to replicated multi-location trials across three distinct climatic environments. The evaluations revealed that GEI accounted for 53% of single-plant yield variation, while environments with high relative humidity and continuous rainfall maximized disease incidence. Multi-trait indices predicted substantial gains in grains per panicle (+ 53.7%) alongside critical reductions in infected florets (− 20.4%), plants (− 14.5%), and tillers (− 7.5%). An UpSet consensus across six independent analytical frameworks confirmed G165 and G64 as exceptionally resilient, broadly adapted lines. These genotypes, along with G66 and G68, represent valuable donors for QTL dissection, molecular validation, and breeding pipelines targeting high-yielding, smut-resilient cultivars for Tamil Nadu agro-ecologies. Integrating multi-trait indices with stability models reveals elite lines successfully decouple high agronomic performance from the physiological yield penalty typically associated with intense disease pressure.</p> Graphical Abstract <p></p>

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Integrating multi-environment trials and multi-trait selection to identify high yielding rice lines with durable false smut (Ustilaginoidea virens) resistance

  • 期刊论文

  • 发表日期：

    2026年6月27日

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  • V. Preeti Kumari,
  • Manonmani Swaminathan,
  • Ramalingam Suresh,
  • Chellappan Gopalakrishnan,
  • Muthurajan Raveendran,
  • Mannu Jayakanthan,
  • Saraswathi Ramaswamy,
  • Pushpa Raman

摘要

Rice false smut, caused by Ustilaginoidea virens, is a major yield and quality limiting disease in humid rice ecologies. Breeding for durable resistance is constrained by limited stable genetic resistance sources, and is further complicated by pronounced genotype × environment interactions (GEI) and pathogen variability, which cause inconsistent field expression. We hypothesized that rigorous multi-environment evaluations using integrated multi-trait selection models could uncover stable resistance sources that do not compromise grain yield. To test this, an F₆ recombinant inbred line (RIL) population (n = 208) derived from crossing a high yielding susceptible variety (CO43) and a highly resistant donor (RG170) was systematically evaluated for agronomic performance and disease response. Initial screening revealed substantial genetic variability and high heritability (> 0.60). Consequently, 31 superior RILs were advanced to replicated multi-location trials across three distinct climatic environments. The evaluations revealed that GEI accounted for 53% of single-plant yield variation, while environments with high relative humidity and continuous rainfall maximized disease incidence. Multi-trait indices predicted substantial gains in grains per panicle (+ 53.7%) alongside critical reductions in infected florets (− 20.4%), plants (− 14.5%), and tillers (− 7.5%). An UpSet consensus across six independent analytical frameworks confirmed G165 and G64 as exceptionally resilient, broadly adapted lines. These genotypes, along with G66 and G68, represent valuable donors for QTL dissection, molecular validation, and breeding pipelines targeting high-yielding, smut-resilient cultivars for Tamil Nadu agro-ecologies. Integrating multi-trait indices with stability models reveals elite lines successfully decouple high agronomic performance from the physiological yield penalty typically associated with intense disease pressure.

Graphical Abstract