IJA_2024v14n4

International Journal of Aquaculture, 2024, Vol.14, No.4, 195-210 http://www.aquapublisher.com/index.php/ija 210 Xiao Y., and Watson M., 2019, Guidance on Conducting a Systematic Literature Review, Journal of Planning Education and Research, 39(1): 93-112. https://doi.org/10.1177/0739456X17723971 Yang L., Liu Y., Yu H., Fang X., Song L., Li D. and Chen Y., 2020, Computer vision models in intelligent aquaculture with emphasis on fish detection and behavior analysis: a review, Archives of Computational Methods in Engineering, 28(4): 2785-2816. https://doi.org/10.1007/s11831-020-09486-2 Yue K., and Shen Y., 2021, An overview of disruptive technologies for aquaculture, Aquaculture and Fisheries, 7(2): 111-120. https://doi.org/10.1016/j.aaf.2021.04.009 Yazdi S., Khoshnevis and Shakouri B., 2010, The effects of climate change on aquaculture., International Journal of Environmental Science and Development, 1: 5. https://doi.org/10.1109/ICEEA.2010.5596156 Zainudin A., Habibullah A., Arfiani Y. and Mumpuni S.D., 2023, Digital transformation on aquaculture in Indonesia through efishery, IOP Conference Series: Earth and Environmental Science, 1147(1): 012024. https://doi.org/10.1088/1755-1315/1147/1/012024 Zhang H., and Gui F., 2023, The Application and research of new digital technology in marine aquaculture, Journal of Marine Science And Engineering, 11(2): 401. https://doi.org/10.3390/jmse11020401 Zhao S., Zhang S., Liu J., Wang H., Zhu J., Li D., and Zhao R., 2021, Application of machine learning in intelligent fish aquaculture: A review. Aquaculture, 540(0044-8486): 724-736. https://doi.org/10.1016/j.aquaculture.2021.736724 Zhou C., Lin K., Xu D., Chen L., Guo Q., Sun C., and Yang X., 2018, Near-infrared computer vision and neuro-fuzzy model-based feeding decision system for fish in aquaculture, Computers and Electronics in Agriculture, 146(0168-1699): 114-124. https://doi.org/10.1016/j.compag.2018.02.006 Zhou C., Xu D., Lin K., Sun C., and Yang X., 2017a, Intelligent feeding control methods in aquaculture with an emphasis on fish: a review, Reviews in Aquaculture, 10(4): 975-993. https://doi.org/10.1111/raq.12218 Zhou C., Zhang B., Lin K., Xu D., Chen C., Yang X., and Sun C., 2017b, Near-infrared imaging to quantify the feeding behaviour of fish in aquaculture, Computers and Electronics in Agriculture, 135(0168-1699): 233-241. https://doi.org/10.1016/j.compag.2017.02.013

RkJQdWJsaXNoZXIy MjQ4ODYzNA==