Functional Disease Phenotyping for Multidisease Resistance Profiling in Wheat

ABSTRACT

Wheat leaf rust (LR), powdery mildew (PM) and tan spot (TS) are important foliar fungal diseases of wheat. Cultivar susceptibility is commonly classified at a single time‐point, although disease progress curves (DPCs) capture multiple components of partial resistance. We evaluated functional disease phenotyping (based on DPCs) to characterize resistance phenotypes and identify cultivars with resistance to multiple diseases. Multi‐environment assessments of LR, PM and TS took place across six municipalities in Paraná and São Paulo State, Brazil (2019–2025) and included 25 cultivars. A hierarchical beta‐regression generalized additive model was fitted to Zadoks‐anchored DPCs, and functional similarity among cultivars was quantified using trajectory‐based distances and hierarchical clustering. Epidemic descriptors included the Zadoks stage when disease reached 5% severity ( Z ₅ ) and maximum disease progress rate along the phenological scale ( Rzmax ). Multidisease resistance (MDR) was assessed using an MDR index and Pareto front analysis. Agreement with final severity classification was low for TS (Adjusted Rand Index = 0.50) and LR (ARI = 0.42), but complete for PM (ARI = 1). Susceptible cultivars showed earlier epidemic onset and higher Rzmax . Stages most informative for functional classification were Zadoks 65–70 (TS), after Zadoks 80 (LR) and around Zadoks 75 (PM). One third of cultivars exhibited balanced resistance across diseases and were Pareto‐optimal, whereas others were resistant to only one or two diseases. The framework identifies informative phenological stages for disease assessment while preserving temporal epidemic dynamics, providing a biologically meaningful characterization of resistance beyond scalars and improving genotype classification for breeding and management.