Title : From biotechnology to intelligent aquaculture: Integrating microbiome engineering, artificial intelligence, and knowledge transfer for sustainable production
Abstract:
Aquaculture is entering a new technological era in which increasing production efficiency can no longer depend on conventional management practices. Disease emergence, antimicrobial resistance, environmental variability, resource limitations, and the complexity of host–microbiome interactions require a transition toward more predictive, preventive, and knowledge-driven production systems. Biotechnology has already provided important tools for addressing these challenges, including probiotics, plant-derived bioactive compounds, molecular diagnostics, bioremediation, and microbiome-based approaches. However, the next challenge is to integrate these biological tools with advanced data analysis and artificial intelligence (AI) to transform information into actionable decisions.
This presentation proposes a conceptual framework for the transition from biotechnology to intelligent aquaculture, integrating microbiome engineering, multi-omics, artificial intelligence, and knowledge transfer. Probiotics and regional plant-derived bioactive compounds are considered not simply as alternatives to antibiotics, but as potential tools for modulating microbial communities, improving host performance, and increasing resilience to pathogenic pressure. In particular, agricultural residues and underutilized plant resources may represent valuable sources of phytochemicals while contributing to circular bioeconomy strategies. These approaches generate increasingly complex datasets describing microbial communities, host responses, environmental conditions, production performance, and pathogen dynamics.
Artificial intelligence provides an opportunity to integrate these heterogeneous datasets and identify patterns that may be difficult to recognize through conventional analytical approaches. Machine learning and generative AI can potentially support literature mining, candidate identification, experimental design, microbiome analysis, disease-risk prediction, environmental monitoring, feed management, and decision-support systems. Importantly, AI should not replace biological experimentation or expert judgment; rather, it can serve as an enabling technology that accelerates hypothesis generation, knowledge integration, and evidence-based decision-making.
A critical component of intelligent aquaculture is the human dimension. Scientific innovation has limited impact when technologies cannot be effectively transferred, understood, or adopted by producers, technicians, students, and decision-makers. Therefore, capacity building, digital literacy, knowledge management, and technology transfer must be incorporated into the innovation process. The integration of AI with biotechnology and organizational learning can facilitate continuous professional development and improve access to scientific knowledge, particularly in regions where technical resources and specialized expertise are limited.
The proposed framework moves aquaculture management from a predominantly reactive model, in which interventions occur after disease or production problems emerge, toward a predictive and preventive model, in which biological, environmental, and production data are continuously integrated to anticipate risks and guide interventions. This transition has the potential to improve animal health and productivity while reducing unnecessary antimicrobial use, optimizing resource utilization, and strengthening environmental sustainability.
Ultimately, intelligent aquaculture should not be understood as the replacement of biology by technology. It represents the integration of biological knowledge, biotechnology, data, artificial intelligence, and human expertise to create more resilient, adaptive, and sustainable production systems. This convergence may provide a pathway for accelerating innovation and translating scientific advances into practical solutions capable of supporting the next generation of global aquaculture.
