Assessing appetite of the swimming fish based on spontaneous collective behaviors in a recirculating aquaculture system

Abstract In order to realize the real-time appetite-based feeding in aquaculture, a novel and practical method, based on the quantification of the spontaneous collective behaviors, was proposed in this study to assess the real-time appetite of the swimming fish in a recirculating aquaculture system. First, foreground feature points of fish school were extracted using an improved complex network. Then, covariance, a modified social force model and a kinetic energy model were used to analyze the collective behaviors of the school from perspectives of dispersion degree, interaction force and the changing magnitude of the water flow field, respectively. Finally, the quantified behavioral characteristics were integrated and used to assess the appetite of fish school. The presented method shows its good performance in the expression of the collective behaviors representing five typical appetites (0.01, 0.52, 1.28, 2.26 and 2.92), and the assessing accuracy of the appetite of the school is also maintained at a low non-match rate ((2.19 ± 0.81)% best) in the context of ten different sampling durations.

[1]  Ying Liu,et al.  Behavioral responses of tilapia (Oreochromis niloticus) to acute fluctuations in dissolved oxygen levels as monitored by computer vision , 2006 .

[2]  Rongrong Ji,et al.  Social Attribute-Aware Force Model: Exploiting Richness of Interaction for Abnormal Crowd Detection , 2015, IEEE Transactions on Circuits and Systems for Video Technology.

[3]  J. Sethna.  Statistical Mechanics: Entropy, Order Parameters, and Complexity , 2021 .

[4]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[5]  Improved Minimax Estimators of Normal Convariance and Precision Matrices , 1995 .

[6]  Jon-Erik Juell,et al.  An ultrasonic telemetric system for automatic positioning of individual fish used to track Atlantic salmon (Salmo salar L.) in a sea cage , 1993 .

[7]  R. G. Evans,et al.  Pulse jet orchard heater system development: Part II. System scaling and application. , 2009 .

[8]  A. Luchiari,et al.  Effects of ambient colour on colour preference and growth of juvenile rainbow trout Oncorhynchus mykiss (Walbaum) , 2008 .

[9]  Sabine Van Huffel,et al.  Overview of total least-squares methods , 2007, Signal Process..

[10]  I. Couzin,et al.  Shared decision-making drives collective movement in wild baboons , 2015, Science.

[11]  Zhangying Ye,et al.  Behavioral Characteristics and Statistics-Based Imaging Techniques in the Assessment and Optimization of Tilapia Feeding in a Recirculating Aquaculture System , 2016 .

[12]  Alessio Del Bue,et al.  Abnormal Crowd Behavior Detection by Social Force Optimization , 2011, HBU.

[13]  C. Noble,et al.  Growing amago and rainbow trout in duoculture with self-feeding systems: Implications for production and welfare , 2010 .

[14]  Colin R. Twomey,et al.  Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion , 2015, Proceedings of the National Academy of Sciences.

[15]  J. López-Olmeda,et al.  Does feeding time affect fish welfare? , 2011, Fish Physiology and Biochemistry.

[16]  Rabab K. Ward,et al.  Detection and counting of uneaten food pellets in a sea cage using image analysis , 1995 .

[17]  Jianhua Li,et al.  A complex network-based approach for interest point detection in images , 2012, IEEE international Symposium on Broadband Multimedia Systems and Broadcasting.

[18]  Tom G. Pottinger,et al.  Current issues in fish welfare , 2006 .

[19]  Peilin Jia,et al.  Association Study of 167 Candidate Genes for Schizophrenia Selected by a Multi-Domain Evidence-Based Prioritization Algorithm and Neurodevelopmental Hypothesis , 2013, PloS one.

[20]  Qi Zhu,et al.  Abnormal crowd behavior detection by using the particle entropy , 2014 .

[21]  P. Giaquinto,et al.  Red Light Stimulates Feeding Motivation in Fish but Does Not Improve Growth , 2013, PloS one.

[22]  Jon-Erik Juell,et al.  Hydroacoustic detection of food waste — A method to estimate maximum food intake of fish populations in sea cages , 1991 .

[23]  Åsmund Bjordal,et al.  Demand feeding in salmon farming by hydroacoustic food detection , 1993 .

[24]  Pietro Perona,et al.  Automated image-based tracking and its application in ecology. , 2014, Trends in ecology & evolution.

[25]  Alfonso Pérez-Escudero,et al.  Collective Animal Behavior from Bayesian Estimation and Probability Matching , 2011, PLoS Comput. Biol..

[26]  Shane P. Windsor,et al.  The flow fields involved in hydrodynamic imaging by blind Mexican cave fish (Astyanax fasciatus). Part I: open water and heading towards a wall , 2010, Journal of Experimental Biology.

[27]  Raymond J. Dolan,et al.  Disentangling the Roles of Approach, Activation and Valence in Instrumental and Pavlovian Responding , 2011, PLoS Comput. Biol..

[28]  Yangsheng Xu,et al.  An energy model approach to people counting for abnormal crowd behavior detection , 2012, Neurocomputing.

[29]  V. Braithwaite,et al.  Stressed mothers - troubled offspring: a study of behavioural maternal effects in farmed Salmo salar. , 2011, Journal of fish biology.

[30]  J. Dalsgaard,et al.  Farming different species in RAS in Nordic countries: Current status and future perspectives , 2013 .

[31]  Wei Fang,et al.  Development of an intelligent feeding controller for indoor intensive culturing of eel , 2005 .

[32]  G. Parisi,et al.  Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study , 2007, Proceedings of the National Academy of Sciences.

[33]  Simon Mackenzie,et al.  Welfare of farmed fish in present and future production systems , 2011, Fish Physiology and Biochemistry.

[34]  H. Chaté,et al.  Relevance of metric-free interactions in flocking phenomena. , 2010, Physical review letters.

[35]  Ramin Mehran,et al.  Abnormal crowd behavior detection using social force model , 2009, CVPR.

[36]  P. Amundsen,et al.  Diet, gastric evacuation rates and food consumption in a stunted population of Arctic charr, Salvelinus alpinus L., in Takvatn, northern Norway , 1988 .

[37]  G. Mylonakis,et al.  Effects of background color on growth performances and physiological responses of scaled carp (Cyprinus carpio L.) reared in a closed circulated system , 2000 .

[38]  Royann J. Petrell,et al.  Accuracy of a machine-vision pellet detection system , 2003 .

[39]  Jianping Li,et al.  Spatial behavioral characteristics and statistics-based kinetic energy modeling in special behaviors detection of a shoal of fish in a recirculating aquaculture system , 2016, Comput. Electron. Agric..

[40]  Colin R. Twomey,et al.  Visual sensory networks and effective information transfer in animal groups , 2013, Current Biology.

[41]  D. Bellwood,et al.  Development of swimming abilities in reef fish larvae , 2000 .

[42]  I. Couzin,et al.  Collective memory and spatial sorting in animal groups. , 2002, Journal of theoretical biology.

[43]  Fan Liangzhong,et al.  Measuring feeding activity of fish in RAS using computer vision , 2014 .

[44]  M. H. Kamran Siddiqui,et al.  Velocity measurements around a freely swimming fish using PIV , 2007 .