Medicinal Plants used in Kumaun Vedic Practices (Agnihotra) and their Influence on Aeromicroflora

This study investigated the antimicrobial efficacy of Agnihotra (Havan ), an ancient Vedic ritual involving the combustion of medicinal plants, against pathogenic aeromicroflora in the Kumaun Himalayan region of India. Specifically, it examined the impact of aromatic smoke on airborne fungal spores and bacteria, while assessing seasonal variations across five distinct periods: summer, monsoon, autumn, winter, and spring. Experiments were conducted in both indoor and outdoor settings at the Department of Botany. Microbial samples were collected using two types of culture media (i) PDA for fungi and (ii) Nutrient Agar (NA) for bacteria under three conditions: (i) control (before Agnihotra ), (ii) during Agnihotra (exposed to medicinal smoke) and (iii) immediately after Agnihotra . All petri dishes were incubated at 25±1°C to promote optimal microbial growth. The results revealed 14 distinct fungal species. Notably, some pathogenic species were completely absent in the smoke-exposed samples. These results indicate that the volatile compounds released during Agnihotra possess potent antimicrobial properties capable of suppressing a broad spectrum of airborne microorganisms, including several known human pathogens. Seasonal analysis confirmed the consistency of this antimicrobial effect throughout the year, although the degree of efficacy varied with environmental conditions. This study provides scientific validation for the antimicrobial potential of Agnihotra smoke, signifying its applicability in modern microbial control strategies. Such eco-friendly and culturally rooted practices hold promise for use in healthcare facilities, agricultural environments, and other settings where airborne pathogen reduction is critical.

@article{archana2026,
  author  = {Archana Kandpal, Neha Pantola and Balwant Kumar*},
  title   = {{Medicinal Plants used in Kumaun Vedic Practices (Agnihotra) and their Influence on Aeromicroflora}},
  journal = {Journal of Bioresearch},
  year    = {2026},
  volume  = {5},
  number  = {1},
  pages   = {39-51},
  doi     = {https://doi.org/10.5281/zenodo.17272901},
}