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Multivariate Water Quality Patterns as a Proxy for Environmental Performance in Tropical Pond-Based Aquaculture Systems

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  • Carlos Ricardo Delgado-Villafuerte

    (Doctoral Program in Natural Resources and Sustainable Management, University of Cordoba, 14071 Cordoba, Spain
    Environmental Engineering Career, Higher Polytechnic School of Agriculture of Manabí Manuel Félix López, Calceta 130250, Ecuador)

  • Ana Gonzalez-Martinez

    (Department of Animal Production, Faculty of Veterinary Sciences, University of Cordoba, 14071 Cordoba, Spain)

  • Fabian Peñarrieta-Macias

    (Environmental Engineering Career, Higher Polytechnic School of Agriculture of Manabí Manuel Félix López, Calceta 130250, Ecuador)

  • Cecilio Barba

    (Department of Animal Production, Faculty of Veterinary Sciences, University of Cordoba, 14071 Cordoba, Spain)

  • Antón García

    (Department of Animal Production, Faculty of Veterinary Sciences, University of Cordoba, 14071 Cordoba, Spain)

Abstract

Water quality plays a central role in determining the environmental performance of pond-based tropical aquaculture systems. This study aimed to evaluate the relative environmental performance of different tropical pond-based aquaculture systems by identifying multivariate water quality patterns that allow their discrimination and comparison under commercial production conditions. Four pond-based production systems were evaluated: an aquaponic system (APS), a recirculating aquaculture system (RAS), a conventional earthen pond system (CEP), and an integrated rice–chame system (RCS). Fourteen physicochemical water quality variables were monitored throughout the production cycle under real commercial conditions using a comparative observational design. Multivariate discriminant analysis was applied to identify the variables with the highest discriminatory power and evaluate the ability of water quality patterns to correctly classify observations among production systems. The results revealed a clear multivariate separation between technologically intensive systems (APS and RAS) and less intensive and integrated systems (CEP and RCS), reflecting distinct water quality structures and environmental functioning. Variables associated with mineralization and nutrient dynamics, including electrical conductivity, dissolved solids, turbidity, phosphates, chlorides, dissolved oxygen, nitrites, and temperature, contributed most strongly to system discrimination. The discriminant functions achieved a high overall correct classification rate, demonstrating the robustness of the multivariate approach. These findings support the use of water quality variables as consistent environmental signatures for distinguishing tropical pond-based aquaculture systems, providing an operational framework for assessing their relative environmental performance. Discriminant analysis emerges as a valuable tool for system characterization and comparative evaluation, supporting environmentally informed management and optimization of chame aquaculture under tropical conditions. Although water quality represents a robust integrative indicator, it captures only one dimension of environmental performance, and additional factors such as production efficiency, energy use, and effluent characterization should be incorporated in future studies to achieve a comprehensive sustainability assessment.

Suggested Citation

  • Carlos Ricardo Delgado-Villafuerte & Ana Gonzalez-Martinez & Fabian Peñarrieta-Macias & Cecilio Barba & Antón García, 2026. "Multivariate Water Quality Patterns as a Proxy for Environmental Performance in Tropical Pond-Based Aquaculture Systems," Sustainability, MDPI, vol. 18(7), pages 1-18, March.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:7:p:3309-:d:1908653
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