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Systematic review identifies challenges in scaling aquaponics, highlighting technological solutions for improvement.
The growing global demand for food, coupled with climate change, underscores the need for sustainable strategies to enhance food security and reduce waste. Aquaponics offers a promising solution by integrating aquaculture and horticulture within a single system, thereby improving productivity, diversification, and environmental sustainability. Despite growing scientific and governmental interest, the commercialization of aquaponics remains challenging. This systematic review identifies 53 key challenges to scaling aquaponics, grouped into five categories: 1) infrastructure and mechanics, 2) system knowledge, 3) market dynamics and consumer preferences, 4) culture and norms, and 5) legal frameworks and policies. The largest number of challenges were identified in system knowledge (16 issues) and market dynamics and consumer preferences (20 critical topics). Technological advancements, including Artificial Intelligence (AI), Internet of Things (IoT), Machine Learning (ML), deep learning, sensor technology, monitoring systems, computer vision, digital detection, and data processing, offer potential solutions that enable automatic management and control of the system, continuous monitoring of fish and plants, analysis of large datasets, decision-making, and optimization of production and inputs. These solutions provide answers and a way forward across these challenging areas. The document critically examines the primary factors influencing the scalability of aquaponics, emphasizing the role of technology in enhancing efficiency and strengthening key production and management processes. While progress has been made, significant opportunities remain to use technology to optimize aquaponic systems, particularly in microbiology, pest control, and monitoring, offering a window for scalable technology and applications. The overarching aim is to address existing barriers to sustainable food production.
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Fimbres‐Acedo et al. (2026) studied this question.
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