AI-Driven Material Optimization for Sustainable and Smart Food Packaging: A Review of Quality Preservation, Safety, and Shelf-Life Enhancement

Talha Riaz¹, Nimra Arshad² , Aliza Batool³, Areeba Batool ,⁴ Rabiya Riaz⁵ , Mumtaz Hussain⁶ , Muhammad Moeid Khan¹, Xianjiang Ye¹, Sadia Ansar⁷, Burhan Khalid⁸

Abstract

AI’s fast development is dramatically changing the field of food packaging since it offers innovative methods for developing high-quality packaging products that can be considered environmentally friendly and sustainable at the same time. Alternative protein products made of yeast require efficient and reliable food packaging solutions since the mentioned type of proteins is quite unstable when it comes to interaction with oxygen, water vapor, temperature, and sunlight. Material optimization in the case of alternative protein products is critically important for ensuring their nutritional and sensory stability, and this paper discusses how AI can contribute to this process. To start with, the application of advanced predictive algorithms and modeling techniques allows for evaluating the effects of different environmental factors on the packaging material and its ability to interact with the food matrix. Predictive analysis of the permeability of various packaging materials, their interaction with external factors, and degradation processes can help to select the most appropriate and efficient types of materials, that can minimize environmental impact while providing optimal protection for the product. This strategy ultimately sees AI as a game-changing tool for the next generation of food packaging, pushing innovation toward protein-based foods that are safer, smarter, and more environmentally friendly.