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 identifies the extended NT‑C2 domain of Plastid Movement Impaired 1 (PMI1) as the main membrane‑binding module that interacts with PI4P and PI(4,5)P2, requiring basic residues for plasma‑membrane association. Calcium binding by the NT‑C2 domain modulates its phosphoinositide preference, and cytosolic Ca2+ depletion blocks blue‑light‑induced PMI1 redistribution, indicating that both the NT‑C2 domain and adjacent intrinsically disordered regions are essential for PMI1’s role in chloroplast movement.

The study reveals that REMORIN protein evolution is primarily driven by diversification of their conserved C-terminal domain, defining four major clades. Structural bioinformatics predicts a common membrane‑binding interface with diverse curvatures and lengths, and suggests that some REMs can form C‑terminal‑mediated oligomers, adding complexity to membrane organization.

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 reveals that rice perceives Xanthomonas oryzae pv. oryzae outer membrane vesicles through a rapid calcium signal that triggers plasma‑membrane nanodomain formation and the re‑organisation of defence‑related proteins, establishing an early immune response. Without this Ca2+ signal, OMVs are not recognized and immunity is weakened.

The complete chloroplast genome of the endemic fruit species Dillenia philippinensis was sequenced, assembled, and annotated, revealing a 161,591‑bp quadripartite structure with 113 unique genes. Comparative analyses identified simple sequence repeats, codon usage patterns, and phylogenetic placement close to D. suffroticosa, providing a genomic resource for future breeding and conservation efforts.

The authors compiled and standardized published data on Rubisco dark inhibition for 157 flowering plant species, categorizing them into four inhibition levels and analyzing phylogenetic trends. Their meta‑analysis reveals a complex, uneven distribution of inhibition across taxa, suggesting underlying chloroplast microenvironment drivers and providing a new resource for future photosynthesis improvement efforts.