Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A Review
Crustacean farming is a fast-growing sector and has contributed to improving incomes. Many studies have focused on how to improve crustacean production. Information about crustacean behavior is important in this respect. Manual methods of detecting crustacean behavior are usually infectible, time-co...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/11/9/2709 |
| _version_ | 1797520473877118976 |
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| author | Daoliang Li Chang Liu Zhaoyang Song Guangxu Wang |
| author_facet | Daoliang Li Chang Liu Zhaoyang Song Guangxu Wang |
| author_sort | Daoliang Li |
| collection | DOAJ |
| description | Crustacean farming is a fast-growing sector and has contributed to improving incomes. Many studies have focused on how to improve crustacean production. Information about crustacean behavior is important in this respect. Manual methods of detecting crustacean behavior are usually infectible, time-consuming, and imprecise. Therefore, automatic growth situation monitoring according to changes in behavior has gained more attention, including acoustic technology, machine vision, and sensors. This article reviews the development of these automatic behavior monitoring methods over the past three decades and summarizes their domains of application, as well as their advantages and disadvantages. Furthermore, the challenges of individual sensitivity and aquaculture environment for future research on the behavior of crustaceans are also highlighted. Studies show that feeding behavior, movement rhythms, and reproduction behavior are the three most important behaviors of crustaceans, and the applications of information technology such as advanced machine vision technology have great significance to accelerate the development of new means and techniques for more effective automatic monitoring. However, the accuracy and intelligence still need to be improved to meet intensive aquaculture requirements. Our purpose is to provide researchers and practitioners with a better understanding of the state of the art of automatic monitoring of crustacean behaviors, pursuant of supporting the implementation of smart crustacean farming applications. |
| first_indexed | 2024-03-10T07:57:17Z |
| format | Article |
| id | doaj.art-98ea90baf3134d8ebc9ad0a2b37ee166 |
| institution | Directory Open Access Journal |
| issn | 2076-2615 |
| language | English |
| last_indexed | 2024-03-10T07:57:17Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Animals |
| spelling | doaj.art-98ea90baf3134d8ebc9ad0a2b37ee1662023-11-22T11:44:21ZengMDPI AGAnimals2076-26152021-09-01119270910.3390/ani11092709Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A ReviewDaoliang Li0Chang Liu1Zhaoyang Song2Guangxu Wang3College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, ChinaCollege of Information and Electrical Engineering, China Agricultural University, Beijing 100083, ChinaBeijing Engineering and Technology Research Centre for Internet of Things in Agriculture, China Agricultural University, Beijing 100083, ChinaChina-EU Center for Information and Communication Technologies in Agriculture, China Agricultural University, Beijing 100083, ChinaCrustacean farming is a fast-growing sector and has contributed to improving incomes. Many studies have focused on how to improve crustacean production. Information about crustacean behavior is important in this respect. Manual methods of detecting crustacean behavior are usually infectible, time-consuming, and imprecise. Therefore, automatic growth situation monitoring according to changes in behavior has gained more attention, including acoustic technology, machine vision, and sensors. This article reviews the development of these automatic behavior monitoring methods over the past three decades and summarizes their domains of application, as well as their advantages and disadvantages. Furthermore, the challenges of individual sensitivity and aquaculture environment for future research on the behavior of crustaceans are also highlighted. Studies show that feeding behavior, movement rhythms, and reproduction behavior are the three most important behaviors of crustaceans, and the applications of information technology such as advanced machine vision technology have great significance to accelerate the development of new means and techniques for more effective automatic monitoring. However, the accuracy and intelligence still need to be improved to meet intensive aquaculture requirements. Our purpose is to provide researchers and practitioners with a better understanding of the state of the art of automatic monitoring of crustacean behaviors, pursuant of supporting the implementation of smart crustacean farming applications.https://www.mdpi.com/2076-2615/11/9/2709aquaculturecrustacean behavioracoustic technologymachine visionmovement sensor |
| spellingShingle | Daoliang Li Chang Liu Zhaoyang Song Guangxu Wang Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A Review Animals aquaculture crustacean behavior acoustic technology machine vision movement sensor |
| title | Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A Review |
| title_full | Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A Review |
| title_fullStr | Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A Review |
| title_full_unstemmed | Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A Review |
| title_short | Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A Review |
| title_sort | automatic monitoring of relevant behaviors for crustacean production in aquaculture a review |
| topic | aquaculture crustacean behavior acoustic technology machine vision movement sensor |
| url | https://www.mdpi.com/2076-2615/11/9/2709 |
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