Journal of Scientific Research and Reports

Plant pathogens and pests pose a critical threat to global food security, necessitating early, accurate and cost-effective diagnostic tools. Conventional methods such as visual inspection, microscopy and molecular assays, while accurate, are often labor-intensive, expensive and unsuitable for large-scale field deployment. Recent advances in volatile organic compound (VOC) profiling have enabled the development of electronic nose (E-Nose) technology, which replicates the mammalian olfactory system through arrays of chemical sensors and pattern recognition algorithms. E-Noses offer rapid, non-invasive and non-destructive detection of plant stress and disease at pre-symptomatic stages, providing an essential advantage for timely intervention. Beyond disease diagnostics, E-Noses are increasingly applied in pest detection, crop quality monitoring, fertilizer and pesticide management and environmental surveillance, aligning closely with the objectives of precision agriculture. The integration of artificial intelligence, nanotechnology and machine learning has enhanced system accuracy and robustness, while challenges such as sensor drift, standardization and field-level validation remain. Overall, E-Nose technology holds significant promise as a practical and sustainable tool for advancing plant health management, promoting environmental sustainability and strengthening the resilience of modern agricultural systems.