한국수산과학회

ISSN NUMBER

  • pISSN
  • :
  • 0374-8111
  • |
  • eISSN
  • :
  • 2287-8815

Open Access Journal

UTIL MENU



SEARCH FOR ARTICLE

검색

kfas, vol. 54, no. 6, pp.965-973, December, 2021
DOI. https://doi.org/10.5657/KFAS.2021.0965

Analysis and Prediction of Behavioral Changes in Angelfish Pterophyllum
scalare Under Stress Conditions
스트레스 조건에 노출된 Angelfish Pterophyllum scalare의 행동 변화
분석 및 예측

김윤재·노혜민1·김도형*
부경대학교 수산생명의학과, 1부산대학교 전기전자컴퓨터공학부

The behavior of angelfish Pterophyllum scalare exposed to low and high temperatures was monitored by video tracking,
and information such as the initial speed, changes in speed, and locations of the fish in the tank were analyzed.
The water temperature was raised from 26°C to 36°C or lowered from 26°C to 16°C for 4 h. The control group was
maintained at 26°C for 8 h. The experiment was repeated five times for each group. Machine learning analysis comprising
a long short-term memory model was used to train and test the behavioral data (80 s) after pre-processing.
Results showed that when the water temperature changed to 36°C or 16°C, the average speed, changes in speed and
fractal dimension value were significantly lower than those in the control group. Machine learning analysis revealed
that the accuracy of 80-s video footage data was 87.4%. The machine learning used in this study could distinguish between
the optimal temperature group and changing temperature groups with specificity and sensitivity percentages of
86.9% and 87.4%, respectively. Therefore, video tracking technology can be used to effectively analyze fish behavior.
In addition, it can be used as an early warning system for fish health in aquariums and fish farms.

Keyword : Fish behavior, Angelfish, Temperature change, Video tracking

Download :


Copyrightⓒ 2014 The Korean Society of Fisheries and Aquatic Science
All Rights Reserved.

Editorial Office Pukyong National University, 45 Yongso-ro, Nam-gu, Busan 608-737, Korea TEL : 82.51.629.7363 | FAX : 82.51.626.1039 | E-mail : kosfas@kosfas.or.kr