Development of Drosophila Melanogaster System for Image Identification and Real-time Temperature Control

• Main Authors: Chang, Sue-Wei, 張書瑋
• Other Authors: Fu, Chien-Chung
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/51290296430345487177

碩士 === 國立清華大學 === 動力機械工程學系 === 99 === Abstract Over the past few decades, scientists were seeking to understand the neural network of a human brain. Due to severe restricted set by the government across the globe, including prohibition on experimenting human subjects. Drosophila Melanogaster has been chosen as a tool by the scientists, due to its similarities in social behavior and hereditary diseases posed by a human. Having only 4-pairs of chromosomes makes it much easier to study as, compared with 23-pairs possessed by a homo sapien. There exists ample of space to manipulate gene regulation by artificial means, for understanding the control mechanisms by linking that to a neural network of Drosophila. In order to understand the fly behavior, several teams have developed customized set of tools to study drosophila’s subtle behaviors. Those tools were able to unveil several mysteries for the knowledge base of brain science. Here is this thesis we present a ”Development of Drosophila Melanogaster System for Image Identification and Real-time Temperature Control”. The system consist of thermal grating aluminum plane, controlled by a PID control module and sensors attached to the system in capable of displaying the temperature gradient. This system is quite flexible in terms of controlling the temperature various from 10℃~40℃ across the aluminum plane, which will enable scientists working on drosophila neural network a handy tool to work on. We design a set experiment in which the lowest temperature is set at 10℃ at one end of the aluminum plane and gradually increasing the temp up to 40℃ towards other end of the aluminum plane and clusters of drosophila flies were let to move freely on the temperature gradient aluminum surface for 30 min in dark. At the end of 30min the system automatically turn on light and capture the image of the surface which is able to determine the distribution of flies on the aluminum plane with respect to temperature gradient with the help of image recognition technique. Using this system we were able to use a proven formula of cold score and warm score calculation for drosophila, for investigating the defects suffered by drosophila flies. This system has a very good temperature control and thermal stability along with image recognition capability and automatic analysis of fly distribution.