基于机器视觉的鱼类模式生物在线监测技术方法研究
文献类型：期刊论文
| 作者 | 周振宇; 邵振洲; 施智平; 渠瀛; 张融; 饶凯锋; 关永 |
| 刊名 | 生态毒理学报
 |
| 出版日期 | 2016 |
| 卷号 | 11期号:1页码:217-224 |
| 关键词 | 生物式水质监测 实时性 观测指标 |
| 其他题名 | Study on the Method of Fish Model Organism On-line Monitoring Technology Based on Machine Vision |
| 中文摘要 | 水污染的防治问题是我国关注的重中之重,现有理化监测方法的实时性和综合性较差,特别是对于一些极端可变化的环境,更需要新的方法以辅助和解决。生物式水质监测方法被提出,通过利用生物对环境污染或变化所产生的反应来直接或间接体现水质的污染情况。然而,观测指标与量化标准是面临的一大难题。文章利用机器视觉的方法,以青鳉鱼为模式生物,并以青鳉鱼的生理特征以及运动特征(呼吸频率、胸鳍摆动频率、摆尾频率)为观测指标,两方面综合评定青鳉鱼应激状态,实时监测与分析。实验结果表明该方法能为生物式水质监测和预警的发展提供一定支持与参考。测得青鳉鱼呼吸频率为3.06 Hz,胸鳍摆动频率为4.83 Hz,尾鳍摆动频率为5.08 Hz,结果与实际指标一致。 |
| 英文摘要 | The prevention and control of water pollution is a top - priority issue in China. The real - time and comprehensive performance of existing physical and chemical monitoring methods are insufficient. Some new approaches are required for assistance in the extremely variable environment,especially. A biological method of water quality monitoring provides a novel solution in this field. The water quality is detected by the biological response to reflect the direct or indirect pollution. However,the observation indexes and quantitative criteria are major problems to estimate in the complex water environment. In this paper,the medaka fish is chosen as the model organism,and the corresponding physiological characteristics and movement characteristics are observation indexes,such as breathing frequency,pectoral oscillation frequency,tail beat frequency,etc. By adopting machine vision based method,the real - time monitoring and analysis are achieved. Experimental results show that the proposed method can provide the support and reference for the development of biological water quality monitoring and early warning. The measured breathing frequency of medaka fish was 3.06 Hz,the pectoral oscillation frequency was 4.83 Hz and the tail beat frequency was 5.08 Hz. The results are consistent with the actual indexes. |
| 收录类别 | CSCD |
| CSCD记录号 | CSCD:5712587 |
| 源URL | [http://ir.rcees.ac.cn/handle/311016/36650]  |
| 专题 | 生态环境研究中心_环境水质学国家重点实验室 |
| 推荐引用方式 GB/T 7714 | 周振宇,邵振洲,施智平,等. 基于机器视觉的鱼类模式生物在线监测技术方法研究[J]. 生态毒理学报,2016,11(1):217-224. |
| APA | 周振宇.,邵振洲.,施智平.,渠瀛.,张融.,...&关永.(2016).基于机器视觉的鱼类模式生物在线监测技术方法研究.生态毒理学报,11(1),217-224. |
| MLA | 周振宇,et al."基于机器视觉的鱼类模式生物在线监测技术方法研究".生态毒理学报 11.1(2016):217-224. |
入库方式： OAI收割
来源：生态环境研究中心
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