The study assessed how well common deep learning models (ResNet, EfficientNet, Inception, MobileNet) generalize across different tomato pest and disease image datasets. While models performed well on the dataset they were trained on, they suffered substantial accuracy drops when applied to other datasets, indicating that architectural changes alone cannot overcome dataset variability. The results highlight the necessity for more diverse, representative training data to improve real-world deployment of PPD diagnostic tools.

The study investigates the wheat Pm3 NLR allelic series, revealing that near-identical Pm3d and Pm3e alleles confer broad-spectrum resistance by recognizing multiple, structurally diverse powdery mildew effectors. Using chimeric NLR constructs, the authors pinpoint specificity-determining polymorphisms and demonstrate that engineered combinations of Pm3d and Pm3e further expand effector recognition, showcasing the potential for durable wheat protection through NLR engineering.

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 demonstrates that limonene, a natural essential‑oil component, strongly inhibits Fusarium oxysporum, the causal agent of potato dry rot, by impairing colony growth, hyphal morphology, spore viability, membrane integrity, and transcription/translation processes, as well as disrupting ion homeostasis. Combined treatments reveal additive effects with mancozeb and synergistic effects with hymexazol, highlighting limonene's potential as an eco‑friendly bio‑fungicide for potato disease management.

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.

Regenerative agriculture using a grass-clover ley increased wheat yields and macroaggregate stability despite reduced root biomass, but did not enhance soil carbon sequestration as measured by 14C retention. Drought further decreased photosynthate allocation to roots, especially in ley soils, while genotype effects on yield were minimal.

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 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 compared aphid resistance and Barley Yellow Dwarf Virus (BYDV) transmission among three wheat varieties (G1, RGT Wolverine, RGT Illustrious). G1 emits the repellent 2‑tridecanone, restricts aphid phloem access, and shows reduced BYDV transmission, whereas RGT Wolverine limits systemic viral infection despite high transmission efficiency. The authors suggest breeding the two resistance mechanisms together for improved protection.

The study presents a high-quality genome assembly for the nickel hyperaccumulator Noccaea caerulescens and uses it as a reference for comparative transcriptomic analyses across different N. caerulescens accessions and the non‑accumulating relative Microthlaspi perfoliatum. It identifies a limited set of metal transporters (NcHMA3, NcHMA4, NcIREG2, and NcIRT1) whose elevated expression correlates with hyperaccumulation, and demonstrates that frameshift mutations in NcIRT1 can abolish the trait, indicating an ancient, transporter‑driven origin of nickel hyperaccumulation.