Genetius

The study compared heat stress responses in diploid (T. monococcum), tetraploid (T. turgidum), and hexaploid (T. aestivum) wheat, finding that the tetraploid retained the highest grain yield under severe heat while the hexaploid showed the most extensive transcriptional changes. Transcriptome and splicing analyses revealed ploidy‑dependent regulatory reprogramming, including a heat‑induced exon‑skipping event in a NF‑YB transcription factor unique to hexaploid wheat, highlighting distinct strategies for heat tolerance across wheat ploidy levels.

The authors present a hexagonal T‑FACE warming system that meets UK/EU health‑safety standards and uses real‑time temperature‑responsive control to maintain a set temperature difference between heated and ambient plots. Field tests on a winter wheat crop demonstrated that the system reliably altered phenology and morphology (heading date, plant height, spike length, spikelet number), highlighting its utility for climate‑change research under realistic conditions.

Using a bread wheat (Triticum aestivum) varietal mixture, the authors showed that root‑derived chemical interactions lower leaf susceptibility to Septoria tritici blotch by triggering phenolic‑mediated signaling and extensive transcriptional and metabolic reprogramming. Disrupting these root interactions abolished both the disease‑reduction effect and the associated molecular responses, linking root signals to enhanced leaf defense.

A genome-wide association study of 187 bread wheat (Triticum aestivum) genotypes identified 812 significant SNPs linked to 25 spectral vegetation indices under rain‑fed drought conditions, revealing high heritability (H² = 0.19‑0.95). A major QTL hotspot on chromosome 2A, tagged by wsnp_Ex_c36049_44083089, was associated with 17 indices and explained up to 20% of phenotypic variance, co‑localizing with candidate LEA/NDR1‑like and lectin receptor‑like kinase genes involved in stress signaling. These findings demonstrate that vegetation indices are heritable digital traits useful for selecting drought‑resilient wheat.

The study presents a hybrid framework that integrates a logistic ordinary differential equation with an LSTM network to form a physics‑informed neural network (PINN) for modeling wheat plant height dynamics. Using only time and temperature as inputs, the PINN outperformed traditional ODE and machine‑learning models, achieving the lowest average RMSE and reduced variability across random initialisations. The results highlight that embedding biological growth constraints into data‑driven models can substantially improve longitudinal trait predictions, especially with limited training data.

The study examined the timing of the juvenile‑to‑adult (JA) phase transition in winter and spring wheat varieties and found it varies among genotypes but is independent of the vernalization gene VRN1. Analyses of shoot apex morphology, leaf traits, and expression of miR156 and miR172 showed later JA transitions are linked to greater phenotypic plasticity, offering insights for breeding.

The study presents AGIcam, an open-source IoT camera system that continuously captures RGB and NoIR images for in-field phenotyping of wheat, achieving >85% uptime across 18 deployments. Time-series vegetation indices derived from the imagery were used in random forest and LSTM models to predict yield, with the LSTM attaining mean errors of 3.41% for spring wheat and 1.62% for winter wheat. The results demonstrate that IoT‑based platforms can provide high‑resolution, real‑time data for scalable crop phenotyping and yield prediction.

The study generated single-nucleus RNA‑seq atlases of wheat grains at 4 and 8 days after pollination, identifying 16 cell populations across seed tissues and revealing a transcriptional shift from growth‑related pathways to nutrient accumulation. Functional analyses showed that the transcription factors TaMADS58 and TaJEKLL regulate pericarp cell number, protein content, and nucellar projection development, providing targets to decouple yield from quality traits.

The review discusses how wheat spikelet number per spike (SNS) is determined by the production rate of spikelet meristems and the timing of the inflorescence meristem's transition to a terminal spikelet, both regulated by meristem identity genes and florigen transport. It also examines genetic strategies—such as supernumerary spikelet formation and allele combinations—that can increase SNS without compromising fertility, highlighting recent spatial transcriptomics and multi‑omics advances that facilitate discovery of new SNS regulators.

The study used 42 years of spring wheat yield data from 255 sites to assess how rising daily minimum temperatures affect grain filling and overall yield. It found that each 1 °C increase in minimum temperature during grain filling reduces yield by about 0.5 t ha⁻¹, accounting for up to 10% loss across test sites, likely due to shortened grain filling periods and increased nocturnal respiration. Improving wheat adaptation to warmer nights could substantially boost global wheat production.