Human body experiences sensation in five ways. They are the knowledge of sound, touch, sight, taste and smell. The knowledge of taste can be electronically experienced as e-tongue. The e-tongue imitates human test knowledge. To get the knowledge on the taste, there have been so many methods adopted by food processing, pharmaceutical and chemical processing industries. On further, they are not only expensive but also have incompetency of giving accurate taste like sweetness, sourness and saltiness through a single sensory bud. This work is intended for an analytical and experimental method to detect taste accurately. A set of the experiment has been carried out by using most promising bio-friendly material zinc oxide (ZnO). The taste concentration can be detected by using an electrochemical method. The chemical route method has chosen for the synthesis of ZnO solution. The modified chemical wet and dry technique (MCWD) is adopted due to uniform coating, inbuilt heat treatment, low cost and overall quick time to make a thin film on aluminium (Al) wire. To set an electrochemical setup, ZnO coated Al and silver (Ag) has taken as working and reference electrode respectively. To respond to different tastes like sour (citric acid), salty (sodium chloride) and sweet (glucose) the electrical data outputs from electrochemical reactions are analysed by varying respective concentrations in the aqueous media. For a sensory bud data validation, extreme learning machine (ELM) based single layered feed-forward neural networks (SLFNs) has been implemented to check the accuracy and pattern recognition.