Environmentally safe in vitro biocontrol strategies for the sustainable management of Curvularia lunata leaf spot of rice: current advances and future perspectives

Abstract

Rice (Oryza sativa L.), a cornerstone of global food security and trade, is increasingly threatened by the emerging fungal pathogen Curvularia lunata, which causes brown leaf spot, grain discoloration, kernel rot, and substantial yield and grain quality losses. This review synthesizes current knowledge on the biology, epidemiology, pathogenicity, diagnosis, and integrated management of C. lunata, with particular emphasis on its increasing importance under changing climatic conditions. The pathogen survives in infected seed, crop residues, and alternate grass hosts, while warm temperatures, prolonged leaf wetness, and high relative humidity favor rapid disease development and repeated secondary infection cycles. Advances in molecular diagnostics, including internal transcribed spacer (ITS) sequencing, multilocus sequence typing, and loop-mediated isothermal amplification (LAMP), have substantially improved the rapid and accurate identification of C. lunata. The review further highlights the extensive pathogenic and genetic variability of the pathogen, which complicates disease surveillance and resistance breeding. Sustainable management requires an integrated disease management approach combining certified disease-free seed, field sanitation, residue and weed management, balanced nutrient and silicon application, optimized planting practices, biological control using Trichoderma spp., Bacillus spp., Pseudomonas fluorescens, and antagonistic yeasts, botanical extracts, and the judicious use of fungicides through seed treatment and timely foliar applications. Climate change is expected to further expand the geographical distribution and epidemic potential of C. lunata, emphasizing the need for climate-resilient disease management strategies. Future research should prioritize pathogen population genomics, host resistance, rapid diagnostics, biological control optimization, and precision disease forecasting to safeguard rice productivity, grain quality, and global food security.