[1] FAO. Fisheries and aquaculture statistics [M]. Rome: FAO fisheries and Aquaculture Department, Food and Agriculture Organization of the United Nations, 2021.
[2]Barraza-Guardado R H, Martínez-Córdova L R, Enríquez-Ocaa L F, et al. Effect of shrimp farm effluent on water and sediment quality parameters off the coast of Sonora, Mexico [J]. Ciencias Marinas, 2014, 40(4): 221-235.
[3]Li D L, Wang Z H, Wu S Y, et al. Automatic recognition methods of fish feeding behavior in aquaculture: A review [J]. Aquaculture, 2020, 528: 735508.
[4]徐丽英, 于承先, 邢斌, 等. 基于PDA的集约化水产饲料投喂决策系统[J]. 农业工程学报, 2008, 24(S2): 250-254.
Xu Liying, Yu Chengxian, Xing Bin, et al. PDAbased aquaculture feeding support system [J]. Transactions of the CSAE, 2008, 24(S2): 250-254.
[5]王华, 李勇, 陈康, 等. 水产养殖动物摄食节律与投喂模式的研究进展[J]. 饲料工业, 2008, 29(24): 17-21.
Wang Hua, Li Yong, Chen Kang, et al. Research progress of feeding rhythm and feeding regime for aquatic animal [J]. Feed Industry, 2008, 29(24): 17-21.
[6]Sun M, Hassan S G, Li D L. Models for estimating feed intake in aquaculture: A review [J]. Computers and Electronics in Agriculture, 2016, 127: 425-438.
[7]Kiris G A, Kumlu M, Dikel S. Stimulatory effects of neuropeptide Y on food intake and growth of Oreochromis niloticus [J]. Aquaculture, 2007, 264(1-4): 383-389.
[8]曹晓慧, 刘晃. 养殖鱼类摄食行为的特征提取研究与应用进展[J]. 渔业现代化, 2021, 48(2): 1-8.
Cao Xiaohui, Liu Huang. Advances in the study and application of feature extraction in feeding behavior of cultured fish [J]. Fishery Modernization, 2021, 48(2): 1-8.
[9] Lee J V, Loo J L, Chuah Y D, et al. The use of vision in a sustainable aquaculture feeding system [J]. Research Journal of Applied Sciences, Engineering and Technology, 2013, 6(19): 3658-3669.
[10]Papadakis V M, Glaropoulos A, Kentouri M, et al. Sub-second analysis of fish behavior using a novel computervision system [J]. Aquacultural Engineering, 2014, 62: 36-41.
[11]果佳良. 基于计算机视觉的鱼类三维行为监测研究及应用[D]. 秦皇岛: 燕山大学, 2015.
Guo Jialiang. Fish behavior of three-dimensional monitoring research and application based on computer vision [D]. Qinhuangdao: Yanshan University, 2015.
[12]Liu Z Y, Li X, Fan L Z, et al. Measuring feeding activity of fish in RAS using computer vision [J]. Aquacultural Engineering, 2014, 60: 20-27.
[13]Zhou C, Zhang B H, Lin K, et al. Near-infrared imaging to quantify the feeding behavior of fish in aquaculture [J]. Computers and Electronics in Agriculture, 2017, 135: 233-241.
[14]Rillahan C, Chambers M, Howell W H, et al. A self-contained system for observing and quantifying the behavior of Atlantic cod, Gadus morhua, in an offshore aquaculture cage [J]. Aquaculture, 2009, 293(1-2): 49-56.
[15]Kolarevic J, Aas Hansen , Espmark A, et al. The use of acoustic acceleration transmitter tags for monitoring of Atlantic salmon swimming activity in recirculating aquaculture systems (RAS) [J]. Aquacultural Engineering, 2016, 72-73: 30-39.
[16]黄月群, 蔡德所, 宋晓红, 等. 基于声学标签系统的鱼类运动轨迹监测技术[J]. 南方水产科学, 2020, 16(4): 114-120.
Huang Yuequn, Cai Desuo, Song Xiaohong, et al. Study on monitoring technology of fish motion trajectories based on acoustic tag system [J]. South China Fisheries Science, 2020, 16(4): 114-120.
[17]Conrad J L, Weinersmith K L, Brodin T, et al. Behavioural syndromes in fishes: A review with implications for ecology and fisheries management [J]. Journal of Fish Biology, 2011, 78: 395-435.
[18]乔峰, 郑堤, 胡利永, 等. 基于机器视觉实时决策的智能投饵系统研究[J]. 工程设计学报,2015, 22(6): 528-533.
Qiao Feng, Zheng Di, Hu Liyong, et al. Research on smart bait casting machine based on machine vision technology [J]. Chinese Journal of Engineering Design, 2015, 22(6): 528-533.
[19]Zhao J, Bao W J, Zhang F D, et al. Assessing appetite of the swimming fish based on spontaneous collective behaviors in arecirculating aquaculture system [J]. Aquacultural Engineering, 2017, 78: 196-204.
[20]赵建, 朱松明, 叶章颖, 等. 循环水养殖游泳型鱼类摄食活动强度评估方法研究[J]. 农业机械学报, 2016, 47(8): 288-293.
Zhao Jian, Zhu Songming, Ye Zhangying, et al. Assessing method for feeding activity of swimming fishes in RAS [J]. Transactions of the Chinese Society for Agricultural Machinery, 2016, 47(8): 288-293.
[21]胡利永, 魏玉艳, 郑堤, 等. 基于机器视觉技术的智能投饵方法研究[J]. 热带海洋学报, 2015, 34(4): 90-95.
Hu Liyong, Wei Yuyan, Zheng Di, et al. Research on intelligent bait casting method based on machine vision technology [J]. Journal of Tropical Oceanography, 2015, 34(4): 90-95.
[22]陈彩文, 杜永贵, 周超, 等. 基于图像纹理特征的养殖鱼群摄食活动强度评估[J]. 农业工程学报, 2017, 33(5): 232-237.
Chen Caiwen, Du Yonggui, Zhou Chao, et al. Evaluation of feeding activity of fishes based on image texture [J]. Transactions of the CSAE, 2017, 33(5): 232-237.
[23]Zhou C, Xu D M, Chen L, et al. Evaluation of fish feeding intensity in aquaculture using a convolutional neural network and machine vision [J]. Aquaculture, 2019, 507: 457-465.
[24]张佳林, 徐立鸿, 刘世晶. 基于水下机器视觉的大西洋鲑摄食行为分类[J]. 农业工程学报, 2020, 36(13): 158-164.
Zhang Jialin, Xu Lihong, Liu Shijing. Classification of Atlantic salmon feeding behavior based on underwater machine vision [J]. Transactions of the CSAE, 2020, 36(13): 158-164.
[25]Sadoul B, Evouna Mengues P, Friggens N C, et al. A new method for measuring group behaviours of fish shoals from recorded videos taken in near aquaculture conditions [J]. Aquaculture, 2014, 430: 179-187.
[26]陈志鹏. 基于计算机视觉的鱼群摄食行为检测方法研究[D]. 上海: 上海海洋大学, 2019.
Chen Zhipeng. Research on fish feeding behavior detection method based on computer vision [D]. Shanghai: Shanghai Ocean University, 2019.
[27]Duarte S, Reig L, Oca J. Measurement of sole activity by digital image analysis [J]. Aquacultural Engineering, 2009, 41(1): 22-27.
[28]Jing D X, Han J, Wang X D, et al. A method to estimate the abundance of fish based on dual-frequency identification sonar (DIDSON) imaging [J]. Fisheries Science, 2017, 83(5): 685-697.
[29]Bulcock P, Bostock J, Jauncey K, et al. The evolution of aquaculture feed supply systems [J]. Eurofish, 2001, 2: 74-76.
[30]Handegard N O, Tjstheim D. When fish meet a trawling vessel: Examining the behaviour of gadoids using a freefloating buoy and acoustic splitbeam tracking [J]. Canadian Journal of Fisheries & Aquatic Sciences, 2005, 62: 2409-2422.
[31]Tao J P, Gao Y, Qiao Y, et al. Hydroacoustic observation of fish spatial patterns and behavior in the ship lock and adjacent areas of Gezhouba Dam, Yangtze River [J]. Acta Ecologica Sinica, 2010, 30(4): 233-239.
[32]荆丹翔, 韩军, 王杰英, 等. 基于成像声呐的鱼类三维空间分布[J]. 水产学报, 2018, 42(6): 996-1005.
Jing Danxiang, Han Jun, Wang Jieying, et al. Three-dimensional distribution of fish using an imaging sonar [J]. Journal of Fisheries of China, 2018, 42(6): 996-1005.
[33]Baumgartner L J, Reynoldson N, Cameron L, et al. Assessment of a dual-frequency identification sonar (DIDSON) for application in fish migration studies [J]. NSW Department of Primary Industries-Fisheries Final Report Series, 2006, 84: 1-33.
[34]Foster M, Petrell R, Ito M R, et al. Detection and counting of uneaten food pellets in a sea cage using image analysis [J]. Aquaculture Engineering, 1995, 14(3): 251-269.
[35]Ang K P, Petrell R J. Control of feed dispensation in seacages using underwater video monitoring: Effects on growth and food conversion [J]. Aquacultural Engineering, 1997, 16: 45-62.
[36]Parsonage K D, Petrell R J. Accuracy of a machine-vision pellet detection system [J]. Aquacultural Engineering, 2003, 29: 109-123.
[37]Atoum Y, Srivastava S, Liu X. Automatic feeding control for dense aquaculture fish tanks [J]. ISPL, 2015, 22: 1089-1093.
[38]Zhou C, Xu D M, Lin K, et al. Intelligent feeding control methods in aquaculture with an emphasis on fish: A review [J]. Reviews in Aquaculture, 2017, 10(4): 1-19.
[39]Li D W, Xu L H, Liu H Y. Detection of uneaten fish food pellets in underwater images for aquaculture [J]. Aquacultural Engineering, 2017, 78: 85-94.
[40]穆春华, 范良忠, 刘鹰. 基于计算机视觉的循环水养殖系统残饵识别研究[J]. 渔业现代化, 2015, 42(2): 33-37.
Mu Chunhua, Fan Liangzhong, Liu Ying. Research on the residual feeds recognition of recirculating aquaculture systems based on computer vision [J]. Fishery Modernization, 2015, 42(2): 33-37.
[41]刘杨. 基于深度学习的水下残饵检测方法研究与实现[D]. 扬州: 扬州大学, 2021.
Liu Yang. Research and realization on underwater uneaten feed pellets detection method based on deep learning [D]. Yangzhou: Yangzhou University, 2021.
[42]Acker T, Burczynski J, Hedgepeth J, et al. Digital scanning sonar for fish feeding monitoring in aquaculture [C]∥ Proceedings of the 6th European Conference on Underwater Acoustrics, Gdansk University of Technology, 2002: 671-675.
[43]Juell J E, Furevik D M, Bjordal A. Demand feeding in salmon farming by hydroacoustic food detection [J]. Aquacultural Engineering, 1993, 12(3): 155-167.
[44]Llorens S, PérezArjona I, Soliveres E, et al. Detection and target strength measurements of uneaten feed pellets with a single beam echosounder [J]. Aquacultural Engineering, 2017, 78: 216-220.
[45]马长震, 谌志新, 汤涛林, 等. 基于超声探测技术的深水网箱剩余饵料监测系统[J]. 微计算机信息, 2012, 28(4): 39-40, 61.
[46]Colson D J, Patek S N, Brainerd E L, et al. Sound production during feeding in Hippocampus seahorses (Syngnathidae) [J]. Environmental Biology of Fishes, 1998, 51: 221-229.
[47]Lagardere J P, Mallekh R, Mariani A. Acoustic characteristics of two feeding modes used by brown trout (Salmo trutta), rainbow trout (Oncorhynchus mykiss) and turbot (Scophthalmus maximus) [J]. Aquaculture, 2004, 240: 607-616.
[48]Mallekh R, Lagardere J P, Eneau J P, et al. An acoustic detector of turbot feeding activity [J]. Aquaculture, 2003, 221: 481-489.
[49]Silva J F, Hamilton S, Rocha J V, et al. Acoustic characterization of feeding activity of Litopenaeus vannamei in captivity [J]. Aquaculture, 2019, 501: 76-81.
[50]Smith D V, Shahriar M S. A context aware sound classifier applied to prawn feed monitoring and energy disaggregation [J]. KnowledgeBased Systems, 2013, 52: 21-31.
[51]AQ1SYSTEMS fish feeding systems [EB/OL]. http://www.aq1systems.com/farming/13510000.html, 2022-09-11.
[52]Popper A N, Schilt C R. Hearing and acoustic behavior: basic and applied considerations [M]. New York: Springer, 2008.
[53]张沛东, 张国胜, 张秀梅, 等. 音响驯化对鲤鱼和草鱼的诱引作用[J]. 集美大学学报(自然科学版), 2004, 9(2): 110-115.
Zhang Peidong, Zhang Guosheng, Zhang Xiumei, et al. Attraction effect of acoustic taming on Cyprinus carpio and Ctenophyagodon idellus [J]. Journal of Jimei University (Natural Science), 2004, 9(2): 110-115.
[54]陈帅, 黄洪亮, 张国胜, 等. 音响驯化对鱼类有效作用范围的研究[J]. 渔业现代化, 2013, 40(1): 36-39.
Chen Shuai, Huang Hongliang, Zhang Guosheng, et al. Research on the effective range of the acoustic conditioning [J]. Fishery Modernization, 2013, 40(1): 36-39.
[55]Zion B, Rosenfeld L, Karplus I. Social facilitation of acoustic training in the common carp Cyprinus carpio (L.) [J]. Behaviour, 2007, 144: 611-630.
[56]Bjornsson B, Karlsson H, Thorsteinsson V. Effects of anthropogenic feeding on the migratory behaviour of coastalcod (Gadus morhua) in Northwest Iceland [J]. Fisheries Research, 2010, 106: 81-92.
[57]Niklitschek E J, Secor D H. Dissolved oxygen, temperature and salinity effects on the ecophysiology and survival of juvenile Atlantic sturgeon in estuarine waters: I. Laboratory results [J]. Journal of Experimental Marine Biology and Ecology, 2009, 381: 150-160.
[58]Buentello J A, Gatlin Ш D M, Neill W H. Effects of water temperature and dissolved oxygen on daily feed consumption, feed utilization and growth of channel catfish (Ictalurus punctatus) [J]. Aquaculture, 2000, 182: 339-352.
[59]Genaro M Soto-Zarazúa, Enrique Rico-García, Rosalía Ocampo, et al. Fuzzy-logic-based feeder system for intensive tilapia production (Oreochromis niloticus) [J]. Aquaculture International, 2010, 18(3): 379-391.
[60]Bórquez-Lopez R A, Casillas-Hernandez R, Lopez-Elias J A, et al. Improving feeding strategies for shrimp farming using fuzzy logic, based on water quality parameters [J]. Aquacultural Engineering, 2018, 81: 38-45.
[61]吴强泽. 池塘养殖智能投饲系统的研究[D]. 南京: 南京农业大学, 2016.
Wu Qiangze. Research on intelligent feeding system of pond aquaculture [D]. Nanjing: Nanjing Agricultural University, 2016.
[62] 赵思琪, 丁为民, 张建凯. 基于模糊逻辑控制的鱼塘养殖精准投饲系统设计与试验[J]. 农业现代化研究, 2019, 40(3): 527-536.
Zhao Siqi, Ding Weimin, Zhang Jiankai. Design and experiment of precision feeding system of pond culturing based on fuzzylogic control [J]. Research of Agricultural Modernization, 2019, 40(3): 527-536.
[63] Yalcuk A, Postalcioglu S. Evaluation of pool water quality of trout farms by fuzzy logic: Monitoring of pool water quality for trout farms[J]. International Journal of Environmental Science and Technology, 2015, 12: 1503-1514.
[64]Wu T H, Huang Y I, Chen J M. Development of an adaptive neural-based fuzzy inference system for feeding decisionmaking assessment in silver perch (Bidyanus bidyanus) culture [J]. Aquacultural Engineering, 2015, 66: 41-51.
[65]Zhao S Q, Ding W M, Zhao S Q, et al. Adaptive neural fuzzy inference system for feeding decision-making of grass carp (Ctenopharyngodon idellus) in outdoor intensive culturing ponds [J]. Aquaculture, 2019, 498: 28-36.
[66]Cui Y B, Hung S S O. A prototype feeding-growth table for White Sturgeon [J]. Journal of Applied Aquaculture, 1996, 5: 25-34.
[67]朱松明, 崔引安, 吴春江, 等. 鲤鱼摄食生长与呼吸耗氧动态模型的研究[J]. 农业工程学报, 1993, 9(5): 25-31.
Zhu Songming, Cui Yin’an, Wu Chunjiang, et al. A study on kinetic models of feeding-growth and oxygen consumption for Cyprinus Carpio [J]. Transactions of the CSAE, 1993, 9(5): 25-31.
[68]刘洋, 刘红柏, 徐革锋, 等. 水温对不同规格细鳞鲑摄食和生长的影响[J]. 中国水产科学,2018, 25(2): 286-293.
Liu Yang, Liu Hongbai, Xu Gefeng, et al. Effects of water temperature on feeding and growth of the lenok Brachymystax lenok (Pallas) with different sizes [J]. Journal of Fishery Sciences of China, 2018, 25(2): 286-293.
[69]Kochi K, Kobayashi M, Hirotaka S. Feeding habits of Ictalurus punctatus in the downstream section of Nunome Dam reservoir in Japan [J]. Landscape and Ecological Engineering, 2021, 17(4): 563-569.
[70]Palomares M L, Pauly D. A multiple regression model for prediction the food consumption of marine fish populations [J]. Marine and Freshwater Research, 1989, 40(3): 259-273.
[71]Kitchll J F, Stewart D J, Weininger D. Applications of a bioenergetics model to yellow perch (Perca flavescens) and walleye (Stizostedion vitreum) [J]. Canadian Journal of Fisheries and Aquatic Sciences, 1977, 34(10): 1910-1921.
[72]刘晓娟, 罗伟, 王春芳, 等. 运用生物能量学模型预测草鱼生长、饲料需求和污染排放[J]. 水产学报, 2018, 42(6): 950-967.
Liu Xiaojuan, Luo Wei, Wang Chunfang, et al. Establishment of bioenergy models to predict growth, feed requirement and waste output of grass carp (Ctenopharyngodon idella) [J]. Journal of Fisheries of China, 2018, 42(6): 950-967.
[73]Dinh V T, Ngo T D, Nguyen T H, et al. Development of a nutritional model to define the energy and protein requirements of tilapia, Oreochromis niloticus [J]. Aquaculture, 2011, 320(1-2): 69-75.
[74]Zhou Z G, Xie S Q, Lei W, et al. A bioenergetic model to estimate feed requirement of gibel carp Carassius auratus gibelio [J]. Aquaculture, 2005, 248(1-4): 287-297.
[75]Lupatsch I, Kissil G W, Sklan D. Defining energy and protein requirements of gilthead seabream (Sparus aurata L.) to optimize feeds and feeding regimes [J]. Israeli Journal of Aquaculture Bamidgeh, 2003, 55(4): 243-257.
[76]刘晓娟, 沙宗尧, 李大鹏, 等. 基于生物能量学模型的尖吻鲈精准投喂管理辅助决策系统构建[J]. 水生生物学报, 2021, 45(2): 237-249.
Liu Xiaojuan, Sha Zongyao, Li Dapeng, et al. Establishment of precise feeding management assistant system of lates calcarifer based on bioenergy model [J]. Acta Hydrobiologica Sinica, 2021, 45(2): 237-249.
[77]张磊. 黄颡鱼能量收支及生物能量学最适生长模型的研究[D]. 武汉: 华中农业大学, 2010.
Zhang Lei. Energy budget and optimum bioenergetics growth model of Yellow Catfish Pelteobagrus Fulvidraco [D]. Wuhan:Huazhong Agricultural University, 2010.
[78]Zhao S Q, Zhu M, Ding W M, et al. Feed requirement determination of grass carp (Ctenopharyngodon idella) using a hybrid method of bioenergetics factorial model and fuzzy logic control technology under outdoor pond culturing systems [J]. Aquaculture, 2020, 521: 734970.
[79]Rodrigo Fortes Da S, Alexandre K, Francisco Javier S V. Dietary self-selection in fish: A new approach to studying fish nutrition and feeding behavior [J]. Reviews in Fish Biology and Fisheries, 2016, 26(1): 39-51.
[80]Sánchez-Vázquez F J, Zamora S, Madrid J A. Light-dark and food restriction cycles in sea bass: Effect of conflicting zeitgebers on demand feeding rhythms [J]. Physiology & Behavior, 1995, 58(4): 705-714.
[81]Montoya A, Alves Martins D, Yúfera M, et al. Self-selection of diets with different oil oxidation levels in gilthead seabream (Sparus aurata) [J]. Aquaculture, 2011, 314(1-4): 282-284.
[82]Fortes-Silva R, Martínez F J, Villaroel M, et al. Daily feeding patterns and self-selection of dietary oil in Nile tilapia [J]. Aquaculture Research, 2010, 42(1): 157-160.
[83]Sánchez-Vázquez F J, Yamamoto T, Akiyama T, et al. Selection of macronutrients by goldfish operating self-feeders [J]. Physiology & Behavior, 1998, 65(2): 211-218.
[84]Sánchez-Vázquez F J, Yamamoto T, Akiyama T, et al. Macronutrient self-selection through demand feeders in rainbow trout [J]. Physiology & Behavior, 1999, 66(1): 45-51.
[85]Huntingford F, Kadri S, Jobling M. Appetite and Feed Intake[M]. New York: Wiley-Blackwell, 2012: 183-219.
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