| Summary: | 碩士 === 國立宜蘭大學 === 生物機電工程學系碩士班 === 105 === This study extends the previously developed automatic online bivalve-based behavioral response monitoring system, and applies the principle of electromagnetic mutual inductance to measure the valve closing/opening magnitudes of Corbicula fluminea to model the change of daily valve rhythm of clams as a bioindicator in bivalve’s living aquatic environments for identifying the statuses of water qualities. In the experiment, Corbicula fluminea is exposed to five types of water environments, respectively: the running water of Shengou Water Eco-museum in Yuanshan Township, the Lake in Yilan City, the water downstream of Yilan River, the groundwater of Alancheng Community in Yuanshan Township, and the irrigation water of Annong River. Valve movements measured by the automatic online bivalve-based behavioral response monitoring system and the according quality of exposed waters are recorded. Meanwhile, the change of daily valve rhythm of Corbicula fluminea is described using a nonlinear four-parameter lognormal model, and a correlation model for the according quality of exposed waters and valve movement patterns is created based on the above experimental database. According to the above process, a real-time measuring mechanism is set up to obtain the characteristic parameters of valve movements exposed to various water qualities in different aquatic environments.
This study preliminarily develops a real-time low-cost visual interface that can interpret the overall status regarding exposed waters based on the valve movements of Corbicula fluminea. In this study, the LabVIEW software is adopted to compile the core program of system numerical calculation that combines with the online bivalve-based behavioral response monitoring system, and imports the correlation model deduced from the qualities of exposed waters and valve movement patterns. By this developed visual interface and system program, users can simultaneously monitor the overall valve movements and obtain the estimation of exposed water qualities (pH, EC, turbidity, hardness) based on the built-in database, and furthermore operators know the quality information of exposed waters. In the future this system can be applied to the biological early warning system for monitoring water qualities in different aquatic environments.
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