Surface Modification of Paper-Based Colorimetric Sensors via Filler Etching for Meat Freshness Monitoring

Abstract

Real-time and non-destructive monitoring of meat freshness is crucial for ensuring food safety and minimizing economic losses. In this study, a cost-effective colorimetric sensor was successfully developed using a facile hydrochloric acid etching strategy on printing paper substrate. The chemical etching partially removed CaCO₃ fillers from the cellulose matrix, successfully optimizing the substrate microstructure. Importantly, acidic environment on the surface spontaneously regulated the electronic state of the pH-sensitive dye to be demonstrated as the protonated form. Upon exposure to volatile amines, the pre-protonated sensor underwent a sharp color transition from light yellow to deep purple via a rapid deprotonation process, resulting in a highest sensitivity of 15.09 ppm⁻¹ and ΔE_max value of 115.37. When applied to real-time monitoring of pork and fish freshness, the sensor exhibited an excellent performance. Combined with machine learning algorithms, the sensor achieved a high classification accuracy (> 98%) in predicting meat freshness stages. This research effectively extends the protonation enhancement theory in sensing performance improvement, providing a practical, efficient, and commercially viable technology for intelligent packaging and non-destructive food quality control.