From Infection to Adaptation: Sclerotium rolfsii-Induced Stress and Defense in Tomato

Tomato (Solanum lycopersicum) is a globally important horticultural crop, with Asia contributing 60. 45% of total production, followed by the Americas at 13. 36%. Tomato productivity is increasingly constrained by southern blight, a destructive disease responsible for yield losses ranging from 30 to 90% and annual economic damage of 10–20 million. The causal pathogen, Sclerotium rolfsii, infects the stem base and induces reddish-brown cankers through secretion of oxalic acid (OA) and cell wall-degrading enzymes, which girdle tissues, impair water transport, and result in rapid plant wilting and death. Its persistence in soil via sclerotia, broad host range, and adaptability make the disease difficult to manage. Recent advances in genomics, transcriptomics, proteomics and other multi-omics approaches have substantially improved understanding of pathogen virulence factors, host defense responses and disease epidemiology. These studies have revealed key roles of OA, carbohydrate-active enzymes, effector proteins, and sclerotial melanization in pathogenesis, while highlighting the activation of salicylic acid (SA) -, jasmonic acid (JA) -, and ethylene (ET) -mediated defense pathways in tomato. Although cultural, biological, and chemical measures are available, these measures often provide inconsistent protection when used alone. Promising strategies include the use of biocontrol agents, hypovirulence-inducing mycoviruses, and chemical fungicides such as carboxamides and quinone outside inhibitors (QoIs), though fungicide resistance remains a risk factor. Integrated Disease Management (IDM) approaches, such as combining biocontrol agents with fungicides, demonstrate enhanced efficacy. This review also evaluates progress in resistance breeding, grafting, RNA interference (HIGS and SIGS), CRISPR-based genome editing, and exploitation of wild genotypes for durable resistance. Furthermore, emerging precision agriculture tools, including hyperspectral imaging, machine learning-assisted disease detection and climate-resilient management strategies, were discussed as new components of sustainable disease management.