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 performed transcriptome profiling of Cryptomeria japonica individuals from different geographic origins grown in three common gardens across Japan, assembling 77,212 transcripts guided by the species' genome. Using SNP-based genetic clustering and weighted gene co‑expression network analysis, they identified gene modules whose expression correlated with genetic differentiation, revealing that defense‑related genes are up‑regulated in Pacific‑side populations while terpenoid metabolism genes are higher in Sea‑of‑Japan populations, indicating local adaptation via regulatory changes.

A biparental Vicia faba mapping population was screened under glasshouse conditions for resistance to a mixture of Fusarium avenaceum and Fusarium oxysporum, revealing several families with moderate to high resistance. Using the Vfaba_v2 Axiom SNP array, a high-density linkage map of 6,755 SNPs was constructed, enabling the identification of a major QTL on linkage group 4 associated with partial resistance to foot and root rot.