Invasive plant species for sustainable security and agricultural biocontrol: integrating allelopathic essential oils...

Invasive plant species (IPS) and herbicide resistance pose a critical threat to biodiversity and food security, particularly in arid agroecosystems. Essential oils (EOs) offer a promising biodegradable alternative, yet their global efficacy and governing factors remain unquantified.

Following PRISMA 2020 guidelines and PROSPERO-registered protocol (ID1282253), this systematic review and meta-analysis synthesized data from 47 studies to evaluate the phytotoxic potential of IPS-derived EOs. We calculated pooled effect sizes (Hedges' g), investigated heterogeneity through meta-regression, and established structure-activity relationships.

Meta-analysis of 47 studies revealed a large, highly significant allelopathic efficacy of invasive plant-derived essential oils (EOs) on target species. Our analysis reveals a large, highly significant inhibitory effect on target species (pooled g = -1.85; 95% CI: -2.12, -1.58), corresponding to a mean 72.3% germination inhibition in laboratory conditions. Efficacy was significantly moderated by EO concentration and chemical class, with ketone-rich oils proving most potent (g = -2.34). Critically, we quantified a substantial lab-to-field efficacy gap, with field studies showing a ~32% relative decline in performance. Also demonstrated significant physiological selectivity, with dicot weeds (e.g., Brassicaceae SMD = -2.45) being far more sensitive than monocots (e.g., Fabaceae SMD = -1.23), and a promising crop safety index. These findings were robust to sensitivity analyses and controlled for publication bias.

This study provides quantitative evidence supporting a more predictive framework for allelopathic research. We leverage these data to propose the Quantitative Phytotoxicity Framework (QPF), a model integrating EO chemistry, environmental factors, and biological outcomes. As a primary application, we conceptualize the Smart Bio-Defensive Barrier (SBDB), a novel, ecologically-engineered system for proactive, landscape-level weed management. This work contributes a data-driven framework for developing sustainable herbicide alternatives, providing a data-driven blueprint for the next generation of sustainable herbicides that aligns with global climate resilience (modeled under RCP 4.5/8.5 scenarios) and circular bio-economic goals.

This model leverages invasive plant species (IPS) as a bio-resource, integrating their in-situ allelopathic potential with ex-situ Nano formulated essential oils (EOs) to create dynamic protective zones. Future implementation of SBDBs requires advances in phytochemical consistency, non-target impact studies, and long-term agroecological trials.

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD4201282253, identifier CRD4201282253.