Omics-guided understanding of nonthermal plasma seed treatment: from surface modification to germination and stress resilience.

This review links plasma-induced seed-surface modification and redox signaling with emerging multi-omics responses associated with germination and stress resilience, while emphasizing that a unified causal sequence remains unproven. Nonthermal plasma (NTP) seed treatment has emerged as a promising chemical-free strategy for improving germination, seedling establishment, and stress resilience. Despite the expansion of plasma agriculture, reviews have largely focused on plasma engineering, individual physiological responses, or descriptive summaries of agronomic outcomes, leaving the mechanistic continuum linking plasma-derived signals to molecular reprogramming and stress-resilient phenotypes fragmented. Here, we provide an omics-guided and systems-level synthesis of NTP seed treatment by integrating evidence from both direct plasma treatment and plasma-activated water within a unified conceptual framework. We evaluate NTP-generated reactive species, ultraviolet photons, and transient electric fields as upstream signals contributing to biological responses across multiple organizational levels, while recognizing that their relative contributions and causal ordering remain unresolved. We synthesize evidence linking plasma exposure with seed-surface remodeling, redox and hormonal signaling, and transcriptomic, proteomic, metabolomic, and locus-specific epigenetic responses. However, these layers have largely been examined across different species, tissues, developmental stages, and experimental systems and therefore do not establish a unified causal chain for germination or stress adaptation. By integrating surface-level effects with molecular evidence, this review frames NTP seed treatment as a dose-dependent redox intervention that may transiently reconfigure conserved signaling networks, while direct cross-scale mechanistic validation remains limited. Finally, we identify critical challenges, including the lack of standardized plasma dosimetry, source variability, and limited cross-scale mechanistic integration, and propose a roadmap toward precision plasma agriculture through multi-omics-guided biomarker discovery, real-time plasma diagnostics, artificial intelligence-assisted optimization, and customized plasma treatments aimed at improving crop establishment and stress resilience.