Chicken freshness detection method based on integrated intelligent indicator film and improved CNN

Traditional food expiration labels cannot reflect the real-time freshness status of meat products, leading to food safety risks and economic losses. This study proposes a chicken freshness detection method that integrates intelligent indicator films with an improved convolutional neural network (ESD-YOLOv8). The indicator film design employs UiO-66 and UiO-66-Br metal–organic frameworks (MOFs) as carriers, combined with natural anthocyanins and chitosan-PVA (CS-PVA) biodegradable matrix. The network architecture introduces three key modules: (1) Deformable Attention Enhanced Bottleneck (DAEB) module with deformable attention mechanisms to adaptively adjust receptive fields for precise color gradient detection; (2) Spatial Grouped Attention Fusion Pyramid Module (SGAFPM); (3) Optimized detection head for improved recognition accuracy. This method provides a non-invasive, rapid, and low-cost technical solution for food safety monitoring.