The study demonstrates that hyperspectral imaging can non‑destructively differentiate active nitrogen‑fixing root nodules from non‑fixing nodules and root tissue based on distinct spectral signatures. By integrating deep‑learning models, the authors created an automated nodule counting pipeline that works across multiple legume species and growth conditions, eliminating labor‑intensive manual counting and reliably detecting nodules within dense root systems.

The study generated deep proteome and phosphoproteome datasets from guard cell‑enriched tissue to examine how phosphorylation regulates stomatal movements. Comparative analysis revealed increased phosphorylation of endomembrane trafficking and vacuolar proteins in closed stomata, supporting a role for phospho‑regulated trafficking in stomatal dynamics.

The study examined seed maturation and germination in the endangered legume Paubrasilia echinata using proteomic and polyamine analyses at 4, 6, and 8 weeks post-anthesis, identifying over 2,000 proteins and linking specific polyamines to developmental stages. Mature seeds (6 weeks) showed elevated proteasome components, translation machinery, LEA proteins, and heat shock proteins, while polyamine dynamics revealed putrescine dominance in early development and spermidine/spermine association with desiccation tolerance and germination. These findings uncover dynamic molecular shifts underlying seed development and provide insights for conservation and propagation.

The study genotyped 1,013 hard red spring wheat lines using SNP arrays and targeted KASP markers to track changes in genetic diversity and the distribution of dwarfing Rht alleles over a century of North American breeding. It found shifts from Rht‑D1b to Rht‑B1b dominance, identified low‑frequency dwarf alleles at Rht24 and Rht25 that have increased recently, and revealed gene interactions that can fine‑tune plant height, along with evidence of recent selection for photoperiod sensitivity.

The study provides a comprehensive proteomic analysis of seed mitochondria from white lupin, revealing fully assembled OXPHOS complexes ready for immediate energy production upon imbibition. Quantitative mass‑spectrometry identified 1,162 mitochondrial proteins, highlighting tissue‑specific transporter and dehydrogenase profiles and dynamic remodeling during early germination, while many uncharacterized proteins suggest novel legume‑specific functions.

The study introduces the Botanical Spectrum Analyzer (BSA), a GUI that incorporates a modified U‑Net deep neural network for accurate segmentation of plant images from RGB and hyperspectral (VNIR and SWIR) data. BSA was tested on wheat, barley, and Arabidopsis datasets, achieving >99% accuracy and F1‑scores above 98%, and markedly outperformed commercial tools on root segmentation tasks.

The study examined how prior light‑acclimation influences the fitness and rapid photoprotective reprogramming of Chlamydomonas during transitions between low and high diurnal light intensities. While high‑light‑acclimated cells struggled to grow and complete the cell cycle after shifting to low light, low‑light‑acclimated cells quickly remodeled thylakoid ultrastructure, enhanced photoprotective quenching, and altered photosystem protein levels, recovering chloroplast function within a single day. Transcriptomic and proteomic profiling revealed swift induction of stress‑response genes, indicating high flexibility in diurnal light acclimation.

The study presents an optimized Agrobacterium-mediated transformation protocol for bread wheat that incorporates a GRF4‑GIF1 fusion to enhance regeneration and achieve genotype‑independent transformation across multiple cultivars. The approach consistently improves transformation efficiency while limiting pleiotropic effects, offering a versatile platform for functional genomics and gene editing in wheat.

The study introduces a native‑condition method combining cell fractionation and immuno‑isolation to purify autophagic compartments from Arabidopsis, followed by proteomic and lipidomic characterisation of the isolated phagophore membranes. Proteomic profiling identified candidate proteins linked to autophagy, membrane remodeling, vesicular trafficking and lipid metabolism, while lipidomics revealed a predominance of glycerophospholipids, especially phosphatidylcholine and phosphatidylglycerol, defining the unique composition of plant phagophores.

The study introduces a deep‑learning based image analysis pipeline that scores blackleg disease severity from stem cross‑section images of canola species, achieving greater consistency than median expert raters while preserving comparable heritability of susceptibility traits. This standardized scoring method aims to improve selection of resistant varieties in breeding programs.