Phosphite (Phi) and phosphate (Pi) share the same root uptake system, but Phi acts as a biostimulant that modulates plant growth and disease resistance in a species‑ and Pi‑dependent manner. In Arabidopsis, Phi induces hypersensitive‑like cell death and enhances resistance to Plectosphaerella cucumerina, while in rice it counteracts Pi‑induced susceptibility to Magnaporthe oryzae and Fusarium fujikuroi, accompanied by extensive transcriptional reprogramming.

The study introduces a hybrid modeling framework that integrates a logistic ordinary differential equation with a Long Short-Term Memory neural network to form a Physics-Informed Neural Network (PINN) for predicting wheat plant height. Using only time and temperature as inputs, the PINN outperformed other longitudinal growth models, achieving the lowest average RMSE and reduced variability across multiple random initializations. The results suggest that embedding biological growth constraints within data‑driven models can substantially improve prediction accuracy for plant traits.

The study cloned the resistance genes Rmo2 and Rwt7 from barley and wheat, revealing them as orthologous tandem kinase proteins (TKPs) with an N‑terminal heavy metal‑associated (HMA) domain. Domain‑swapping experiments indicated that the HMA domain dictates effector specificity, supporting a model of TKP diversification into paralogs and orthologs that recognize distinct pathogen effectors.

The authors used a bottom‑up thermodynamic modelling framework to investigate how plants decode calcium signals, starting from Ca2+ binding to EF‑hand proteins and extending to higher‑order decoding modules. They identified six universal Ca2+-decoding modules that can explain variations in calcium sensitivity among kinases and provide a theoretical basis for interpreting calcium signal amplitude and frequency in plant cells.

Mutations in the plastid division gene PARC6 and the granule initiation gene BGC1 were combined to generate wheat plants with dramatically enlarged A-type starch granules, some exceeding 50 µm, without affecting plant growth, grain size, or overall starch content. The parc6 bgc1 double mutant was evaluated in both glasshouse and field trials, and the giant granules displayed altered viscosity and pasting temperature, offering novel functional properties for food and industrial applications.

The researchers performed a large‑scale field trial with 105 wheat (Triticum aestivum) genotypes inoculated by Fusarium culmorum, combining quantitative deoxynivalenol (DON) profiling and untargeted metabolomics to uncover molecular signatures of infection. Sesquiterpene‑derived metabolites tracked toxin accumulation, whereas glycosylated diterpene conjugates were enriched in low‑DON samples, indicating a potential defensive metabolic pathway.

The study combined high-throughput image-based phenotyping with genome-wide association studies to uncover the genetic architecture of tolerance to the spittlebug Aeneolamia varia in 339 interspecific Urochloa hybrids. Six robust QTL were identified for plant damage traits, explaining up to 21.5% of variance, and candidate genes linked to hormone signaling, oxidative stress, and cell‑wall modification were highlighted, providing markers for breeding.

The study investigates the wheat Pm3 NLR allelic series, revealing that near-identical Pm3d and Pm3e alleles confer broad-spectrum resistance by recognizing multiple, structurally diverse powdery mildew effectors. Using chimeric NLR constructs, the authors pinpoint specificity-determining polymorphisms and demonstrate that engineered combinations of Pm3d and Pm3e further expand effector recognition, showcasing the potential for durable wheat protection through NLR engineering.

The study generated the first nested association mapping (NAM) population in the outcrossing forage grass Italian ryegrass (Lolium multiflorum) to investigate seed shattering and related traits, using ddRAD sequencing of 708 F2 individuals combined with whole-genome sequencing of 24 founders to obtain over 3 million SNPs for population structure, parentage, and GWAS analyses. Seven QTL were identified for seed shattering and other agronomic traits, leading to the discovery of candidate genes, including one associated with ripening pathways that explained 10% of phenotypic variance, demonstrating the utility of NAM for dissecting complex traits in outcrossing grasses.

Regenerative agriculture using a grass-clover ley increased wheat yields and macroaggregate stability despite reduced root biomass, but did not enhance soil carbon sequestration as measured by 14C retention. Drought further decreased photosynthate allocation to roots, especially in ley soils, while genotype effects on yield were minimal.