| Summary: | 碩士 === 國立虎尾科技大學 === 光電工程系光電與材料科技碩士班 === 105 === This thesis aims to construct a pesticide residue detection system for Taiwan agricultural products to reduce the cost of pesticide testing and shorten the detection time. Raspberry Pi 3B development board and 8MP Raspberry Pi camera module (V2) camera were used in conjunction with Acetylcholinesterase (Ache) detection method to perform image recognition processing in QT Creator encoder. Firstly, the QT Creator man-machine interface design software and OpenCV image processing library were installed on Raspberry Pi 3B development board to complete the establishment of a development environment, and C ++ program was then written. Ache was used to formulate the detection solution capable of detecting organic phosphorus and carbamate pesticide. When Ache comes in contact with organic phosphorus or carbamate pesticide, it will inhibit the activity of Ache, causing Ache being unable to hydrolyze with acetylcholine (matrix) to become acetic acid and thiocholine. Such long-term acting will cause nerve conduction disorder to result in decreased memory. Alzheimer’s disease is a most apparent symptom caused by a decline in acetylcholine.
When thiocholine reacts with the coloring agent, it will turn yellow from transparent. The higher the concentration of pesticide, the lower it contains thiocholine and the slower it turns yellow. On the contrary, the lower the concentration of pesticide, the higher it contains thiocholine and the faster it turns yellow. The yellowing process of the transparent test solution was video recorded through the camera being fixed on a light source, and the variation amount of RGB value was recorded every second. Finally, the concentration of pesticide in the vegetable was determined through the integral size of blue channel spectrum to achieve the goal of detecting pesticide residue value rapidly and cheaply.
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