Impact of RAS System on Tilapia Health in a Commercial Farm Network

Thesis Abstract

The rapid intensification of tilapia production in recirculating aquaculture systems (RAS) presents a pivotal challenge ensuring optimal fish health amid continuous exposure to recycled water, concentrated stocking densities, and variable water quality parameters. Despite the growth of commercial farm networks adopting RAS, evidence on how specific system configurations influence tilapia physiology, immune function, disease incidence, and growth performance remains fragmented, limiting scalable best practices. This study aims to elucidate the relationship between RAS operational parameters and tilapia health within a commercial farm network, providing empirically grounded guidance for industry optimization and policy formulation. The central objective is to determine how water quality stability (ammonia, nitrite, nitrate, pH, dissolved oxygen, temperature), biofilter performance, stocking density, and feeding strategies interact to affect health indicators, disease prevalence, and growth outcomes in Nile tilapia (Oreochromis niloticus) across multiple facilities. The study adopts a longitudinal, multi-site, mixed-methods design integrating quantitative health and performance metrics with qualitative insights from farm managers to capture contextual factors that influence health outcomes. The population comprises tilapia cohorts from five commercial farms within a widely distributed RAS network, each operating at distinct but comparable production cycles. A stratified random sample of 1,000 fish per farm (total N = 5,000) will be monitored over 12 months, with monthly biometric assessments (weight, standard length, condition factor) and health screenings for common pathogens (e.g., Streptococcus iniae, Aeromonas spp.) using qPCR assays and routine thematic pathology. Water quality data (ammonia, nitrite, nitrate, pH, dissolved oxygen, temperature) will be logged continuously via in-line sensors and manually validated weekly. Feeding regimes, feed conversion ratios, and stocking densities will be recorded from farm management systems. Instrument validity and reliability will be ensured through standardized health assessment protocols, calibration of in-line sensors, and pilot-testing of qPCR assays with known controls. Data analysis will employ hierarchical linear modeling to assess the impact of water quality stability, biofilter performance, and stocking density on growth and health outcomes, while controlling for farm-specific effects. Time-series analyses will evaluate temporal trends in water quality and health indicators, and generalized estimating equations (GEE) will handle repeated measures. Multivariate regression will explore the relative contributions of key predictors to disease incidence. Thematic analysis of semi-structured interviews with farm managers (n ? 20), conducted to a saturation point, will illuminate operational constraints, management responses to water quality excursions, and perceived drivers of health outcomes, with credibility established through member checking and triangulation with quantitative results. A theoretical framework grounded in the Systems Theory of Aquaculture and the Health–Performance paradigm will underpin model specification, capturing interactions among system components, fish physiology, and management decisions. Expected findings include (1) a threshold effect of dissolved oxygen and ammonia stability on growth rate and condition factor, (2) a significant association between stocking density, biofilter maturity, and incidence of opportunistic infections, (3) differential disease risk linked to pH excursions and temperature fluctuations, and (4) evidence that proactive feeding strategies mitigating nitrite peaks correlate with improved feed efficiency and reduced morbidity. The study will contribute to knowledge by integrating operational RAS dynamics with fish health outcomes across a commercial network, providing scalable indicators and decision-support benchmarks for health management, and informing policy on system design and biosecurity protocols. Practical contributions will include a validated monitoring framework, recommended target ranges for water quality stability, and evidence-based guidelines for density management and feeding schedules tailored to RAS configurations. The main conclusion is that tilapia health and growth in RAS networks are maximized through integrated management of water quality stability, biofilter performance, and adaptive feeding, with organizational practices and real-time monitoring playing critical roles. Recommendations emphasize investment in sensor redundancy, routine health screening, staff training in water quality interpretation, and coordination across farms to standardize best practices while allowing site-specific customization. Further research is suggested to explore the economic trade-offs of enhanced filtration capacity and to investigate genetic factors influencing resilience to RAS-associated stressors.