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Bio-Hybrid Films from Chirich Tuber Starch: A Sustainable Approach with Machine Learning-Driven Optimization

Author

Listed:
  • Eyyup Karaogul

    (Department of Food Engineering, Harran University Faculty of Engineering, Sanliurfa 63300, Turkey)

  • Gencay Sarıışık

    (Department of Industrial Engineering, Harran University Faculty of Engineering, Sanliurfa 63300, Turkey)

  • Ahmet Sabri Öğütlü

    (Department of Industrial Engineering, Harran University Faculty of Engineering, Sanliurfa 63300, Turkey)

Abstract

This study investigates the potential of Chirich ( Asphodelus aestivus ) tuber, one of Turkey’s natural resources, for sustainable bio-hybrid film production. Bio-hybrid films developed from Chirich tuber starch in composite form with polyvinyl alcohol (PVOH) were thoroughly examined for their physical, mechanical, and barrier properties. During the production process, twin-screw extrusion and hydraulic hot pressing methods were employed; the films’ optical, chemical, and barrier performances were analyzed through FT-IR spectroscopy, water vapor permeability, solubility, and mechanical tests. To evaluate the films’ durability against environmental factors and model their properties, advanced computational model algorithms such as Gradient Boosting Regression (GBR), Random Forest Regression (RFR), and AdaBoost Regression (ABR) were utilized. The results showed that the GBR algorithm achieved the highest accuracy with 99.92% R 2 and presented the most robust model in terms of sensitivity to environmental factors. The results indicate that Chirich tuber-based bio-hybrid films exhibit significantly enhanced mechanical strength and barrier performance compared to conventional corn starch-based biodegradable polymers. These superior properties make them particularly suitable for industrial applications such as food packaging and medical materials, where durability, moisture resistance, and gas barrier characteristics are critical. Moreover, their biodegradability and potential for integration into circular economy frameworks underscore their environmental sustainability, offering a viable alternative to petroleum-derived plastics. The incorporation of ML-driven optimization not only facilitates precise property prediction but also enhances the scalability of bio-hybrid film production. By introducing an innovative, data-driven approach to sustainable material design, this study contributes to the advancement of bio-based polymers in industrial applications, supporting global efforts to mitigate plastic waste and promote environmentally responsible manufacturing practices.

Suggested Citation

  • Eyyup Karaogul & Gencay Sarıışık & Ahmet Sabri Öğütlü, 2025. "Bio-Hybrid Films from Chirich Tuber Starch: A Sustainable Approach with Machine Learning-Driven Optimization," Sustainability, MDPI, vol. 17(5), pages 1-21, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:1935-:d:1598757
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    References listed on IDEAS

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    1. Daud, Abdel-Karim & Ismail, Mahmoud S., 2012. "Design of isolated hybrid systems minimizing costs and pollutant emissions," Renewable Energy, Elsevier, vol. 44(C), pages 215-224.
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