Overview of aquaculture Artificial Intelligence (AAI) applications: enhance sustainability and productivity, reduce labor costs, and increase the quality of aquatic products-Reference-Cited by-同舟云学术

Overview of aquaculture Artificial Intelligence (AAI) applications: enhance sustainability and productivity, reduce labor costs, and increase the quality of aquatic products

Published:2024-08-29 Issue: Volume: Page:
ISSN:2300-8733
Container-title:Annals of Animal Science
language:en
Short-container-title:

Author:

Ragab Sherine¹,Hoseinifar Seyed Hossein²,Doan Hien Van³⁴,Rossi Waldemar⁵,Davies Simon⁶,Ashour Mohamed⁷,El-Haroun Ehab¹

Affiliation:

1. Fish Nutrition Research Laboratory , Animal Production Department , Faculty of Agriculture, Cairo University , Cairo , Egypt

2. Department of Fisheries , Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources , Gorgan , Iran

3. Department of Animal and Aquatic Sciences , Faculty of Agriculture, Chiang Mai University , Chiang Mai , Thailand

4. Functional Feed Innovation Center (FuncFeed) , Faculty of Agriculture, Chiang Mai University , Chiang Mai , Thailand

5. School of Aquaculture and Aquatic Sciences, College of Agriculture, Community, and the Sciences , Kentucky State University , Frankfort , KY, United States

6. Aquaculture Nutrition Research Unit ANRU, Carna Research Station, Ryan Institute , College of Science and Engineering, University of Galway , Galway , Ireland

7. National Institute of Oceanography and Fisheries (NIOF) , Cairo , Egypt

Abstract

Abstract The current work investigates the prospective applications of Artificial Intelligence (AI) in the aquaculture industry. AI depends on collecting, validating, and analyzing data from several aspects using sensor readings, and feeding data sheets. AI is an essential tool that can monitor fish behavior and increase the resilience and quality of seafood products. Furthermore, AI algorithms can early detect potential pathogen infections and disease outbreaks, allowing aquaculture stakeholders to take timely preventive measures and subsequently make the proper decision in an appropriate time. AI algorithms can predict ecological conditions that should help aquaculture farmers adopt strategies and plans to avoid negative impacts on the fish farms and create an easy and safe environment for fish production. In addition, using AI aids to analyze and collect data regarding nutritional requirements, nutrient availability, and price could help the farmers to adjust and modify their diets to optimize feed formulations. Thus, using AI could help farmers to reduce labor costs, monitor aquatic animal’s growth, health, optimize feed formulation and reduce waste output and early detection of disease outbreaks. Overall, this review highlights the importance of using AI to achieve aquaculture sustainability and boost the net profits of farmers

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/aoas-2024-0075

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