The study introduces an in-soil fiber Bragg grating (FBG) sensing system that continuously records three-dimensional strain from growing pseudo-roots, enabling non‑destructive monitoring of root architecture. Using two ResNet models, the system predicts root width and depth with over 90% accuracy, and performance improves to 96‑98% after retraining on data from actual corn (Zea mays) roots over a 30‑day period. This prototype demonstrates potential for scalable, real‑time root phenotyping and broader soil environment sensing.

The study profiled the Arabidopsis apoplastic proteome during pattern‑triggered immunity induced by the flg22 peptide, using apoplastic washing fluid with minimal cytoplasmic contamination followed by LC‑MS/MS. Results showed consistent PTI‑specific enrichment and depletion of peptides, a bias toward ectodomain peptides of receptor‑like kinases, and increased abundance of the exosome marker tetraspanin 8, indicating heightened exosome levels during PTI.