# Food‐Activated Microneedle Sensor for Real‐Time, Colorimetric Spoilage Monitoring of Pre‐Packaged Food

## TL;DR

A low-cost, color-changing sensor made from food ingredients can detect spoilage in packaged food in real-time, with results readable by smartphone.

## Contribution

A novel food-derived microneedle sensor with real-time spoilage monitoring and AI-powered smartphone readout is introduced.

## Key findings

- The sensor uses anthocyanins to detect spoilage through pH changes, showing strong correlation with spoilage markers.
- Microneedles nondestructively penetrate packaging and rehydrate in food, enabling real-time spoilage detection.
- Machine learning analysis of smartphone images improves accuracy and removes ambiguity in sensor readouts.

## Abstract

At a time of growing food insecurity, developing technologies to reduce food waste is critical. An inexpensive, colorimetric spoilage sensor for real‐time food product assessment is reported. The sensor is composed of dehydrated gelatin microneedles that exhibit high mechanical integrity in their base state. However, once exposed to fluid‐rich food environments, they rapidly transition to a hydrogel sensing state. Food‐derived anthocyanins embedded within these microneedles enable pH‐based spoilage monitoring. When applied to sealed fish products, these microneedles nondestructively penetrate through the packaging and are rehydrated by the underlying fish matrix. As the product ages, a defined color shift occurs, demonstrating strong correlation with quantitative spoilage markers. When applied to unsealed fish products for rapid testing, the large microneedle sensing interface enables accelerated colorimetric sensing. Finally, successful fresh vs spoiled categorization of smartphone‐acquired images of the sensor using machine learning removes readout ambiguity, empowering consumers with independent real‐time product monitoring.

A microneedle spoilage sensor for packaged food products is presented. The sensor is composed entirely of food‐derived agents, integrated together using a novel material processing approach. This resultant platform nondestructively reports spoilage state in real‐time through a colorimetric output. Artificial intelligence‐powered sensor analysis allows for automated readout from smartphone images, improving accessibility and eliminating readout ambiguity.