Biodegradable Packaging Films with Shelf Life in Local Food Markets: Optimization Modeling

Authors

  • Man-Kit Tam Department of Construction and Quality Management, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong, Hong Kong SAR, China Author
  • Joyce Poon Department of Construction and Quality Management, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong, Hong Kong SAR, China Author
  • Richard Lai Department of Construction and Quality Management, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong, Hong Kong SAR, China Author

Keywords:

Biodegradable Packaging, Shelf Life Optimization, Local Food Markets, Sustainable Supply Chain, Food Waste Reduction

Abstract

The transition toward sustainable food supply chains necessitates the replacement of conventional petroleum-based plastics with biodegradable packaging films. However, the adoption of these sustainable alternatives in local food markets is often hindered by uncertainties regarding their impact on shelf life and overall economic viability. This paper presents a comprehensive optimization modeling approach designed to balance the material properties of biodegradable packaging films with the shelf life requirements of fresh produce in local market settings. By conceptualizing a multi-objective framework, the study evaluates the oxygen transmission rates, water vapor permeability, and mechanical strength of various biopolymers against the respiration rates and spoilage kinetics of highly perishable goods. The proposed model seeks to minimize packaging costs and food waste while maximizing the effective shelf life under variable ambient conditions typical of local agricultural markets. Through extensive simulated case studies focusing on specific produce categories, the analysis demonstrates that optimized biodegradable packaging configurations can achieve shelf life extensions comparable to conventional plastics, resulting in significant reductions in aggregate supply chain waste. The findings provide a theoretical foundation and practical guidelines for local producers and distributors to select appropriate biodegradable materials that align with both environmental sustainability goals and economic constraints.

References

1. Kok, S.P.; Go, Y.I.; Wang, X.; Wong, M.L.D. Advances in Fiber Bragg Grating (FBG) Sensing: A Review of Conventional and New Approaches and Novel Sensing Materials in Harsh and Emerging Industrial Sensing. IEEE Sens. J. 2024, 24, 29485–29505.

2. Nimmala, S.; Gupta, N.S.; Sena, P.V.; Chari, K.K.; Pasha, M.A.; Rambabu, B. Energy-Efficient Wireless Sensor Networks Optimization using Deep Q-Networks for Smart Energy Applications. In Proceedings of the 5th International Conference on Trends in Material Science and Inventive Materials (ICTMIM), Kanyakumari, India, 7–9 April 2025; pp. 1023–1027.

3. Zhang, R.; Liu, H.; Wang, Y.; Li, Z.; Zhang, Y. Research on Self-Diagnosis and Self-Healing Technologies for Fiber Optic Sensing Networks in Complex Environments. Sensors 2025, 25, 1641.

4. Alghananim, M.S.; Feng, Y.; Ochieng, W.Y. The first calibration model for bluetooth angle of arrival: Enhancing positioning accuracy in indoor environments. arXiv 2025, arXiv:2501.08805v1.

5. Chowdhury, M.Z.; Shahjalal, M.; Ahmed, S.; Jang, Y.M. 6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions. IEEE Open J. Commun. Soc. 2020, 1, 957–975.

6. Spachos, P.; Hatzinakos, D. Real-Time Indoor Carbon Dioxide Monitoring Through Cognitive Wireless Sensor Networks. IEEE Sens. J. 2015, 16, 506–514.

7. Bagwari, A.; Logeshwaran, J.; Usha, K.; Raju, K.; Alsharif, M.H.; Uthansakul, P.; Uthansakul, M. An Enhanced Energy Optimization Model for Industrial Wireless Sensor Networks Using Machine Learning. IEEE Access 2023, 11, 96343–96362.

8. Zhao, L.; Ding, L. Wireless sensor network based on IoT automation technology application in green supply chain management of automobile manufacturing industry. Internet J. Adv. Manuf. Technol. 2024, 1–12.

9. El Ouadghiri, M.; Aghoutane, B.; El Farissi, N. Communication model in the Internet Of Things. Procedia Comput. Sci. 2020, 177, 72–77.

10. Tariq, M.; Ahmed, T. Compressed Edge Models for AI-Driven IoT Fire prediction Systems. Electronics 2025, 14, 1011.

11. Pech, G.; Delgado, C. Assessing the publication impact using citation data from both Scopus and WoS databases: An approach validated in 15 research fields. Scientometrics 2020, 125, 909–924.

12. Koo, Y.C.; Mahyuddin, M.N.; Ab Wahab, M.N.A. Novel Control Theoretic Consensus-Based Time Synchronization Algorithm for WSN in Industrial Applications: Convergence Analysis and Performance Characterization. IEEE Sens. J. 2023, 23, 4159–4175.

13. Wu, T.-H.; Liao, C.-Y.; Yeh, C.-H.; Chen, Y.-W.; Kao, Y.-H.; Lin, S.-Y.; Lin, Y.-H.; Liaw, S.-K. A Self-Healing WDM Access Network with Protected Fiber and FSO Link Paths Effective Against Fiber Breaks. Photonics 2025, 12, 323.

14. Arun Mozhi Devan, P.; Ibrahim, R.; Omar, M.B.; Bingi, K.; Abdulrab, H.; Hussin, F.A. Improved Whale Optimization Algorithm for Optimal Network Coverage in Industrial Wireless Sensor Networks. In Proceedings of the 2022 International Conference on Future Trends in Smart Communities (ICFTSC), Kuala Lumpur, Malaysia, 7–8 December 2022; pp. 124–129.

Downloads

Published

2026-03-17

Issue

Section

Articles