Microplastic Accumulation and Risk Assessment in Closed Biofloc Aquaculture: Integrating Biofloc Engineering with Artificial Neural Networks (ANN) Modeling

Document Type : Original Research Paper

Authors

1 Department of Chemistry, Faculty of Mathematics and Natural Sciences, Andalas University, Padang, P.O.Box 25163, Indonesia

2 Department of Aquaculture, Faculty of Fisheries and Marine Sciences, Universitas Bung Hatta, Padang, P.O.Box 25133, Indonesia

3 Department of Medical Laboratory Technology, Syedza Saintika University, Padang, P.O.Box 25132, Indonesia

10.22059/poll.2026.407025.3209

Abstract

Microplastics (MPs) are pervasive contaminants in closed aquaculture systems, where limited water exchange restricts removal. This study assessed biofloc as a mitigation strategy for polyethylene (PE) MPs and characterized MPs in terms of morphology, size, color, and polymer type across four treatments. Biofloc reduced background MPs by 26.3%, but PE addition significantly increased concentrations, indicating low removal efficiency for buoyant polymers. Fragmented and fibrous MPs dominated, while FTIR spectroscopy confirmed PE, polyamide (PA), and polyethylene terephthalate (PET) as major polymers. Health risk assessment using Estimated Daily Intake (EDI), Target Hazard Quotient (THQ), and Hazard Index (HI) indicated all indices remained below 1, though cumulative risk increased with higher MP loads. An Artificial Neural Network (ANN) model accurately predicted exposure indices (R² = 0.95; RMSE = 0.021), and SHapley Additive exPlanations (SHAP) identified MP concentration as the primary driver of health risk. These findings highlight that while biofloc can partially sequester environmental MPs, it is ineffective against buoyant PE, emphasizing the need for integrated mitigation strategies. Combining biofloc management with ANN-based predictive modeling provides a robust framework to reduce MP exposure and support sustainable aquaculture practices in closed systems. Future research should focus on optimizing biofloc compositions, evaluating PE fragmentation, and assessing long-term ecological and food safety impacts.

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Main Subjects

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Pollution
Volume 12, Issue 2
May 2026
Pages 560-573

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