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

K. Adnan, N. Yusuf, H. Maamor, F. A. Rashid, S. Ismail, R. Thriumani, A. Zakaria, L. Kamarudin, A. Shakaff, M. N. Jaafar, M. Ahmad
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引用次数: 10

Abstract

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.
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电子鼻和电子舌在水产养殖水质分类与监测中的应用
水产养殖是国家粮食安全的重要组成部分。水产养殖场的生产力取决于水质。缺乏测量水质的适当仪器是该行业的一个障碍。本实验提出并验证了电子鼻和电子舌在对虾养殖水质参数研究中的应用。结果表明它有潜力,但需要额外的分析技术。因此,利用传感器阵列技术,利用电子鼻和电子舌对水产养殖中使用的不同类型的水进行分类。电子鼻由10个金属氧化物传感器组成,电子舌由13个工作电极和1个参比电极组成。采用线性判别分析(LDA)作为数据分类器。电子鼻和电子舌能够对不同类型的水进行分类,准确率高达95%。这些结果显示了电子鼻和电子舌对水产养殖业中不同类型的水进行分类的潜力。
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