Phosphite (Phi) and phosphate (Pi) share the same root uptake system, but Phi acts as a biostimulant that modulates plant growth and disease resistance in a species‑ and Pi‑dependent manner. In Arabidopsis, Phi induces hypersensitive‑like cell death and enhances resistance to Plectosphaerella cucumerina, while in rice it counteracts Pi‑induced susceptibility to Magnaporthe oryzae and Fusarium fujikuroi, accompanied by extensive transcriptional reprogramming.

The authors applied semi‑supervised deep‑learning to super‑resolution images of modern and fossil grass pollen, training convolutional neural networks to extract abstract morphological features. These features were used to quantify past grass community diversity and C3:C4 ratios in a 25,000‑year lake‑sediment record, revealing a marked diversity loss during the last glacial and a gradual decline of C4 grasses in the Holocene.

The authors introduce AdaPoinTr, a geometry-aware transformer that predicts the alpha‑shape of coniferous tree crowns from incomplete terrestrial or mobile laser‑scanning point clouds, focusing on crown reconstruction rather than full tree completion. Trained on synthetically generated partial crowns, the model consistently improves crown shape similarity and reduces height estimation bias across three diverse forest datasets, providing a cost‑effective solution for enhanced 3D forest structural monitoring.

The study identifies the circadian clock component ELF3 as a temporal gatekeeper that limits hormone‑induced pericycle proliferation and lateral root development in Arabidopsis thaliana. Time‑resolved transcriptomics, imaging, and genetic analyses show that ELF3 maintains rhythmic expression of key regulators via LNK1 and MADS‑box genes, and that loss of ELF3 disrupts this rhythm, enhancing callus growth and accelerating root organogenesis.

The study reveals that the thermosensor and circadian regulator ELF3 interacts with the PLT3 transcription factor in Arabidopsis root stem cell niches, forming subcellular condensates that sustain quiescent centre and columella stem cell fate. ELF3’s intrinsically disordered prion‑like domains drive condensate formation with PLT3, and PIF3/4 act as nuclear shuttles recruiting ELF3 to nuclear condensates, linking environmental cues to stem cell maintenance.

The study reveals that the microtubule-associated protein MAP70-2 integrates mechanical and biochemical signals to guide division plane orientation during early lateral root primordium formation in Arabidopsis thaliana. Dynamic MAP70-2 localization to cell corners and the cortical division zone precedes cytokinesis, and loss of MAP70-2 results in misoriented divisions and malformed lateral roots, highlighting its role in three‑dimensional differential growth under mechanical constraints.

The study examined how DNA methylation influences cold stress priming in Arabidopsis thaliana, revealing that primed plants exhibit distinct gene expression and methylation patterns compared to non-primed plants. DNA methylation mutants, especially met1 lacking CG methylation, showed altered cold memory and misregulation of the CBF gene cluster, indicating that methylation ensures transcriptional precision during stress recall.

The study uncovers how arbuscular mycorrhizal (AM) fungi induce lateral root formation in maize by activating ethylene‑responsive transcription factors (ERFs) that regulate pericycle cell division and reshape flavonoid metabolism, lowering inhibitory flavonols. It also shows that the rhizobacterium Massilia collaborates with AM fungi, degrading flavonoids and supplying auxin, thereby creating an integrated ethylene‑flavonoid‑microbe signaling network that can be harnessed to improve nutrient uptake and crop sustainability.

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 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.