Effect of Different Samples of Viruddha Ahara on Lactobacillus Inhibition-An Exploratory in vitro Study

Background

Viruddha Āhāra (incompatible food combinations) are described in Ayurveda as dietary practices that disturb digestion and metabolism, leading to doshic imbalance and disease. Though classically established, their biological basis remains poorly explored in modern terms. Since gut microbiota, especially Lactobacillus species, play a crucial role in digestion and host health, this study aimed to assess the effect of selected Viruddha Āhāra combinations on Lactobacillus plantarum growth in vitro.

Objectives

To evaluate and compare the influence of classical Viruddha Āhāra combinations and their individual components on the growth of Lactobacillus plantarum using standard microbiological techniques.

Materials and methods

Four Viruddha Āhāra categories were selected: (1) honey-ghee (Matra Viruddha), (2) unripe, ripe, and overripe mango (Sampat Viruddha), (3) tea-ice cream (Vīdhi Viruddha), and (4) milk-orange (Samyoga Viruddha). Sterile samples were inoculated with L. plantarum (0.5 McFarland standard) in MRS broth and incubated under CO₂ conditions for 48 hr. Serial dilutions were plated using the quadrant streak method, and colony-forming units (CFU) were calculated.

Results

The honey sample showed no growth, while ghee and honey-ghee (1:1) showed reduced CFU (10×10⁵ and 15×10⁵) compared to control (29×10⁵). Unripe mango supported highest growth (70×10⁵) followed by ripe (44×10⁵) and overripe (29×10⁵). Tea and ice cream combination (25×10⁵) showed slightly higher growth than control (23×10⁵). The milk-orange mixture exhibited complete inhibition (0 CFU), confirming classical āmla-kṣīra viruddha (milk-sour incompatibility).

Conclusion

The study provides preliminary experimental evidence that certain Viruddha Āhāra combinations can inhibit Lactobacillus growth, suggesting potential disruption of gut microbial balance. These findings support Ayurvedic dietary cautions and encourage further exploration using multi-strain and in vivo models.