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.

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.

The study evaluated 146 pigeonpea minicore accessions for resistance to Helicoverpa armigera and related agronomic traits across three field seasons, integrating phenotypic data with whole‑genome resequencing of ~500,000 SNPs for multi‑locus GWAS. Fourteen significant marker‑trait associations and candidate genes were identified, and four moderately resistant accessions were confirmed through laboratory pod bioassays, highlighting SNP markers for future breeding.

The study compared physiological, ion‑balance, and metabolic responses of two maize inbred lines—salt‑sensitive C68 and salt‑tolerant NC326—under salinity stress. Untargeted metabolomics identified 56 metabolites and, together with genetic analysis, linked 10 candidate genes to key protective metabolites, revealing constitutive and inducible mechanisms of salt tolerance.

The study performed ionomic profiling and genome-wide association studies on a diverse panel of pearl millet infield across two seasons to uncover genetic factors controlling nutrient acquisition. Soil analyses revealed stable depth-dependent patterns for phosphorus and zinc, while leaf ion concentrations showed high heritability and associations with root and agronomic traits. Integrating GWAS with gene expression data identified candidate ion transport/homeostasis genes for breeding nutrient-efficient, climate-resilient millet.