AI-Driven Raman Spectroscopy and Quantum Dot Probes with Federated Learning for Micro-Nanoplastic Detection and Removal in Livestock and Aquaculture Feeds

Micro and nanoplastics, pervasive environmental pollutants smaller than 5 mm and 1 µm respectively, infiltrate livestock and aquaculture feeds via contaminated water, sewage sludge fertilizers, and atmospheric deposition, compromising animal health, reproductive performance, and food chain safety. This paper presents a pioneering hybrid framework that synergistically integrates artificial intelligence-enhanced Raman spectroscopy for high-resolution polymer fingerprinting, quantum dot nanoprobes for targeted fluorescent labelling of hydrophobic plastics, and federated learning algorithms for decentralized, privacy-preserving model training across heterogeneous farm networks. Unlike traditional methods such as microscopy or pyrolysis-gas chromatography, which suffer from low sensitivity in complex organic matrices and lack real-time scalability, our system achieves a limit of detection of 5 ng/g with 97% accuracy across polyethylene, polypropylene, and polystyrene variants in poultry pellets, cattle silage, and salmon feeds. Quantum dots, functionalized with π-π stacking ligands, enable selective binding and surface-enhanced Raman signals, while edge-deployed AI processes hyperspectral data in under 100 ms per sample. Federated averaging across 50 simulated nodes converges 25% faster than centralized baselines, incorporating differential privacy for regulatory compliance. Experimental results demonstrate 91% removal efficiency through dielectrophoretic extraction of labelled particles, surpassing density separation by 40% in yield and 70% in speed, with pilot deployments yielding 12% improvements in feed conversion ratios and 30% reductions in inflammation biomarkers. This scalable, cost-effective solution ($500/unit, 6-month ROI) paves the way for sustainable animal production resilient to escalating plastic pollution, with broader implications for precision agriculture and global food security.