Water quality classification and monitoring using e-nose and e-tongue in aquaculture farming

Aquaculture is an important to national food security. Productivity of aquaculture farms hinges on water quality. Lack of appropriate instrumentation for measurement of water quality is a hindrance to the industry. This experiment proposed and verify the application of e-nose and e-tongue for water quality parameters for shrimp farming. Results indicated it has the potential but required additional analytical techniques. Thus, by using sensor array technologies, e-nose and e-tongue has been employed in classification of different type of water that has been used in aquaculture farming. E-nose consists of 10 metal oxide sensors meanwhile e-tongue consists of 13 working electrodes and one reference electrode. Linear Discriminant Analysis (LDA) was used as data classifier. The e-nose and e-tongue was able to classify different type of water with the accuracy up to 95%. These results show the potential use of e-nose and e-tongue to classify the different type of water used in aquaculture industry.