Performance-Safety-Feasibility Evidence Chains for Next-Generation Food-Preservation Packaging: Engineering and...

Area of Science:

• Food Science and Technology
• Materials Science
• Toxicology

Background:

• Next-generation food packaging innovations struggle with industrial adoption due to a disconnect between preservation claims, migration exposure, and regulatory requirements.
• Current translation limitations stem from inadequate evidence chains linking engineering design to safety and regulatory approval.

Purpose of the Study:

• To reframe packaging innovation as an evidence-chain problem, connecting engineering design to preservation performance, exposure control, and regulatory feasibility.
• To critically examine bio-based polymers, nano-enabled composites, and intelligent packaging systems.
• To propose a prioritization logic for advanced food packaging based on readiness and evidence requirements.

Main Methods:

• Review and synthesis of literature on three dominant food packaging technology pathways: bio-based polymers, nano-enabled composites, and intelligent packaging.
• Analysis of structural design impacts on barrier performance, controlled release, and antimicrobial activity.
• Integration of migration, toxicology, non-intentionally added substances, degradation products, and physicochemical characterization data.

Main Results:

• Bio-based platforms (multilayer, compatibilized) show the most direct path to scale.
• Nano-enabled functions require immobilization and proven low migration for feasibility.
• Intelligent packaging is most feasible in noncontact label formats with validated stability and food quality-linked decision thresholds.

Conclusions:

• A performance-safety-feasibility framework guides the design and evaluation of advanced food packaging.
• The framework aids in optimizing biodegradable and active materials, enhancing freshness monitoring, and supporting material selection and safety assessment.
• Multilayer bio-based systems offer near-term scalability, while nano- and intelligent systems require further validation for widespread adoption.