Ayurveda classifies medicinal herbs based on the concept of Rasa (taste), which plays a significant role in determining their therapeutic properties. Traditionally, Rasa identification is performed through human sensory perception, which is subjective, non-quantitative, and varies from person to person. To address this limitation, the present project proposes the design and development of a low-cost Electronic Tongue (E-Tongue) system for preliminary Rasa identification of Ayurvedic herbal extracts. The system integrates a pH sensor, Total Dissolved Solids (TDS) sensor, turbidity sensor, and temperature sensor interfaced with an ESP32 microcontroller. The measured physicochemical parameters are processed using rule-based logic to classify the probable Rasa category. A stepper motor mechanism is incorporated to automate sample handling, and the ESP32's built-in WiFi capability enables real-time monitoring through a web-based dashboard. The prototype was tested on selected herbal powders such as turmeric, neem, amla, and ginger, and distinct variations in sensor readings were observed corresponding to their expected taste characteristics. The developed system demonstrates an economical, portable, and objective approach to bridging traditional Ayurvedic knowledge with modern embedded and IoT technologies, providing a practical solution for academic research and preliminary herbal analysis.
Shervegar et al. (Thu,) studied this question.