The study used Weighted Gene Correlation Network Analysis (WGCNA) and GENIE3 to construct co‑expression modules and gene regulatory networks (GRNs) in barley subjected to Fusarium head blight and drought stress. Integration of these approaches highlighted overlapping regulatory patterns, pinpointing WRKY transcription factors as central to FHB response, while bHLH and NAC family members showed stress‑specific roles. Promoter motif enrichment further validated predicted TF‑target interactions, offering candidate regulators for future functional validation.

Four barley genotypes were examined under simultaneous Fusarium culmorum infection and drought, revealing genotype-dependent Fusarium Head Blight severity and largely additive transcriptomic responses dominated by drought. Co‑expression and hormone profiling linked ABA and auxin to stress‑specific gene modules, and a multiple linear regression model accurately predicted combined‑stress gene expression from single‑stress data, suggesting modular regulation.

The authors created a fast‑cycling, isogenic barley line (GP‑rapid) by introgressing the wild‑type Ppd‑H1 allele from Igri into the Golden Promise cultivar and performing two backcrosses to limit the donor genome, achieving a 25% reduction in generation time under speed‑breeding conditions while retaining high transformation efficiency. CRISPR/Cas9‑mediated editing of Ppd‑H1 showed regeneration and transformation rates comparable to the original Golden Promise, establishing GP‑rapid as a rapid platform for transgenic and gene‑edited barley research.

The study used chlorophyll fluorescence imaging to map non-photochemical quenching (NPQ) gradients along barley leaf axes and found heat stress attenuates NPQ induction, revealing spatial heterogeneity in stress responses. Genome‑wide association and transcriptomic analyses identified candidate genes, notably HORVU.MOREX.r3.3HG0262630, that mediate region‑specific heat responses, highlighting pathways for improving cereal heat resilience.

The authors applied time‑resolved high‑throughput phenotyping to six barley (Hordeum vulgare) lines grown under well‑watered and drought conditions, using RGB, thermal infrared, chlorophyll fluorescence, and hyperspectral imaging. Temporal phenomic models accurately classified drought‑stressed plants (R² ≥ 0.97) and predicted harvest‑related traits such as total biomass and spike weight, with early canopy temperature depression and later RGB‑derived plant size identified as key predictors. Pooled‑treatment models outperformed single‑treatment models and remained robust when applied early in the experiment, highlighting the utility of phenomics for rapid selection of drought‑resilient genotypes.