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.