Cost-effective approaches for microplastic pellets characterization using a machine learning tool

Vincenzo Mariano Scarrica

doi:10.1016/j.ecoinf.2025.103230

Cost-effective approaches for microplastic pellets characterization using a machine learning tool

2025-05-28

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Vincenzo Mariano Scarrica

DOI：10.1016/j.ecoinf.2025.103230

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Abstract

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• Cost-effective AI-based approach for microplastic pellet classification. • Random Forest model classifies polymer types using degradation state, color, weight and size. • The method does not require spectroscopic data, reducing analysis costs and complexity. • Scalable machine learning approach for rapid microplastic identification. • Application to different sites: Galicia, Asturias (Spain), and Volcano Island (Italy).

Keywords:

Microplastic

Pellet

Polymer classification

Machine learning

Random Forest

Cost-effective approaches for microplastic pellets characterization using a machine learning tool

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