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 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 study reports the creation and validation of a high‑density Axiom SNP array for Solanum tuberosum, based on 10X Genomics sequencing of 108 diverse clones and integration of existing Illumina markers. The array demonstrated high reproducibility and, after filtering, provided 206,616 informative markers for population structure analysis, GWAS of polyphenol oxidase activity, and genomic prediction with accuracies up to 0.86.

The study examined how soil phosphorus and nitrogen availability influence wheat root-associated arbuscular mycorrhizal fungal (AMF) communities and the expression of mycorrhizal nutrient transporters. Field sampling across two years combined with controlled pot experiments showed that P and N jointly affect AMF colonisation, community composition (with Funneliformis dominance under high P), and regulation of phosphate, ammonium, and nitrate transporters. Integrating metabarcoding and RT‑qPCR provides a framework to assess AMF contributions to crop nutrition.

The study investigated unexpected leaf spot symptoms in Psa3‑resistant kiwifruit (Actinidia) germplasm, finding that Psa3 was detectable by qPCR and metabarcoding despite poor culturing. Metabarcoding revealed distinct bacterial community shifts in lesions versus healthy tissue, and whole‑genome sequencing identified diverse Pseudomonas spp. that, while not individually more pathogenic, could enhance Psa3 growth, suggesting pathogenic consortia on resistant hosts.