Seed quality represents the cornerstone of agricultural productivity and food security, particularly in the face of climate change challenges. High-quality seeds possess genetic potential, physiological vigour, and phytosanitary integrity necessary for establishing robust plant populations capable of withstanding environmental stressors while delivering optimal yields. Integration of beneficial microorganisms offers a sustainable approach to enhance seed performance across multiple dimensions. This review explores how microbial intervention approaches can holistically enhance seed quality through complementary mechanisms across the crop production continuum. We have systematically documented beneficial microbial interactions including those with Pseudomonas, Bacillus, Trichoderma, and arbuscular mycorrhizal fungi and associated modes of action for seed quality improvement. Application methods including seed coating, biopriming, and pelleting are critically assessed for their efficacy across agro-ecological contexts. Evidences suggest that microbial interventions operate through multiple complementary mechanisms by optimizing nutrient acquisition, enhancing stress tolerance, suppressing pathogens, and inducing systemic resistance. The comprehensive review describes the integration of microbial interventions with other sustainable agricultural practices that provide promising pathways towards resilient and productive farming systems. Studies indicate that potential cost-effective microbe-mediated approaches when clubbed with sensors, showed substantial economic viability and environmental sustainability. Emerging technologies including artificial intelligence-powered decision support systems and Internet of Things monitoring offer significant potential to optimize microbial seed treatments within precision agriculture frameworks are presented. Such integrated holistic methods can be clubbed with the transformative agricultural practices to offer food security and soil and crop health challenges in the regime of climatic variability.
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Dhananjaya P. Singh
Ratna Prabha
Sudarshan Maurya
Discover Plants.
Banaras Hindu University
Indian Agricultural Research Institute
Indian Agricultural Statistics Research Institute
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Singh et al. (Thu,) studied this question.
www.synapsesocial.com/papers/69e320cc40886becb653fe03 — DOI: https://doi.org/10.1007/s44372-026-00530-2