Printed Colorimetric Indicators with Enhanced Humidity Resistance for Real-Time Fish Freshness Monitoring

Conventional expiration dates often fail to accurately reflect the real-time freshness of highly perishable foods such as fish, as spoilage rates are strongly influenced by storage and handling conditions. Colorimetric indicators based on natural pigments, particularly anthocyanins, have emerged as promising alternatives due to their sensitivity to volatile amines generated during spoilage. However, their practical implementation is hindered by limited stability under the high-humidity environments typically found in food packaging.

In this work, bio-based colorimetric indicators were fabricated using a scalable printing approach on flexible substrates and subsequently modified through surface hydrophobization to improve resistance to moisture. The resulting indicators exhibited enhanced water repellency and maintained structural integrity under conditions representative of packaged fish storage. Importantly, the applied surface modification did not hinder the diffusion of volatile amines, enabling the indicators to retain their sensing capability.

The performance of the indicators was evaluated under refrigerated storage conditions in packaged fish, where high humidity levels are prevalent. The indicators demonstrated a clear and distinguishable color response associated with spoilage, while remaining stable over extended storage periods. Control experiments under comparable humidity conditions in the absence of fish confirmed that the observed color changes were primarily driven by volatile amines rather than environmental moisture.

These results highlight the potential of combining printed sensing platforms with surface engineering strategies to enable practical, low-cost freshness monitoring systems for food packaging applications, particularly under challenging high-humidity conditions.

Acknowlegment: This work was developed within the scope of the projects: CICECO-Aveiro Institute of Materials, UID/50011/2025 (DOI 10.54499/UID/50011/2025) & LA/P/0006/2020 (DOI 10.54499/LA/P/0006/2020) & UID/PRR/50011/2025 (DOI 10.54499/UID/PRR/50011/2025), financed by national funds through the FCT/MCTES (PIDDAC) and SMARTPACK (POCI/Portugal 2020 – Project 182881). FCT is acknowledged by the PhD fellowship 2022.11211.BD (https://doi.org/10.54499/2022.11211.BD).