The biocontrol potential of endophyte Bacillus velezensis to reduce post-harvest tomato infection caused by Rhizopus microsporus

Summary

Researchers tested a naturally occurring bacteria called Bacillus velezensis as a safe alternative to chemical fungicides for protecting tomatoes from rot-causing mold. The bacteria produces special compounds that can kill or slow down the growth of Rhizopus microsporus, a fungus that commonly spoils tomatoes after harvest. While the results show promise, the effectiveness varied depending on which specific strain of bacteria and mold was used, suggesting more research is needed to fine-tune the approach.

Background

Rhizopus microsporus is a necrotrophic post-harvest pathogen causing significant economic losses in agriculture. Chemical fungicides used for post-harvest disease control pose health and environmental risks. Endophytic bacteria, particularly Bacillus velezensis, show promise as biological control agents through production of antimicrobial compounds.

Objective

To investigate the biocontrol potential of two Bacillus velezensis strains (KV10 and KV15) against three R. microsporus strains through in vitro and in vivo experiments. The study aimed to examine antagonistic mechanisms including direct inhibition, volatile organic compound production, and efficacy in reducing post-harvest tomato spoilage.

Results

B. velezensis demonstrated strain-specific antifungal activity with inhibition rates varying across R. microsporus strains. VOC analysis identified antifungal compounds including ethyl-hexanols, undecanone, 1-dodecanol, and 2-tridecanone. In vivo studies showed variable spoilage reduction across treatments, with exocarp peel inoculation revealing fungal colonization at stem scars rather than inoculation sites.

Conclusion

B. velezensis shows promise as a biocontrol agent for reducing R. microsporus post-harvest infections in tomatoes through production of secondary metabolites and volatile organic compounds. However, biocontrol efficacy is strain-specific and variable, requiring optimization of application methods and increased replication in future studies for sustainable post-harvest disease management.
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