AQUA: A Large Language Model for Aquaculture & Fisheries

TL;DR

AQUA is the first large language model specifically designed for aquaculture, aiming to enhance industry practices and research through synthetic data generation and AI-driven decision support.

Contribution

Introduction of AQUA, a domain-specific large language model for aquaculture, and AQUADAPT, a framework for synthetic data creation and refinement.

Findings

AQUA supports industry practitioners with AI-driven insights.

AQUADAPT improves data quality for aquaculture applications.

Foundation laid for LLM-based innovations in aquaculture research.

Abstract

Aquaculture plays a vital role in global food security and coastal economies by providing sustainable protein sources. As the industry expands to meet rising demand, it faces growing challenges such as disease outbreaks, inefficient feeding practices, rising labor costs, logistical inefficiencies, and critical hatchery issues, including high mortality rates and poor water quality control. Although artificial intelligence has made significant progress, existing machine learning methods fall short of addressing the domain-specific complexities of aquaculture. To bridge this gap, we introduce AQUA, the first large language model (LLM) tailored for aquaculture, designed to support farmers, researchers, and industry practitioners. Central to this effort is AQUADAPT (Data Acquisition, Processing and Tuning), an Agentic Framework for generating and refining high-quality synthetic data using a combination of expert knowledge, largescale language models, and automated evaluation techniques. Our work lays the foundation for LLM-driven innovations in aquaculture research, advisory systems, and decision-making tools.