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Published on: October 26, 2016
Gellan gum/ artemisia sphaerocephala Krasch gum composite films integrated with machine learning for real-time
Xu Zhang1, Chunwei Li1, Mingjian Sun1
1College of Home and Art Design, Northeast Forestry University, Harbin, 150040, PR China.
Abstract:
The widespread use of non-degradable plastic food packaging poses serious environmental and food safety concerns, motivating the development of biodegradable intelligent packaging systems capable of real-time freshness monitoring. In this study, a bilayer antibacterial indicator film was fabricated, consisting of an inner gellan gum/Artemisia sphaerocephala Krasch gum (GG/ASKG) layer and an outer cellulose acetate (CA) layer, incorporating optimized nano‑zinc oxide (2%) and nano‑silicon dioxide (1.5%). Films were prepared via solution casting and characterized by UV-blocking, water vapor permeability (WVP), water contact angle, antibacterial activity, and colorimetric response during fish storage. Nano-SiO2 significantly enhanced barrier properties, increasing UV-blocking efficiency to >90%, raising water contact angle above 90°, and reducing WVP by 46.3%, whereas nano-ZnO mainly improved antimicrobial performance, producing inhibition zones of 14.04 mm (E. coli) and 11.18 mm (S. aureus), ~30% larger than the control. The absence of new chemical bonds confirmed that nanoparticles interacted physically with the polymer matrix. All films exhibited distinct color changes in stored fish, transitioning from rosy pink (fresh) to yellowish pink (slightly spoiled), and ultimately to a greyish-purple hue (spoiled), enabling visual freshness monitoring and extending fish shelf life by ~1 day at room temperature. Furthermore, L, a, b color parameters were incorporated into a backpropagation artificial neural network (BP-ANN) with Batch Normalization and Dropout, achieving high predictive performance for TVB-N values (R2 = 0.954, classification accuracy = 100%), demonstrating that visual color changes could be quantitatively translated into reliable freshness indicators. This work highlights a novel strategy that integrates multifunctional nanomaterials and data-driven algorithms for intelligent, biodegradable food packaging.
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