Intelligent packaging: Sensors to monitor product quality

Abstract                      
For fresh products the quality of the product can vary considerably during shelf life. Monitoring the quality during transport and storage in the production chain gives additional information for better predicting the product quality and can give important information for logistic control of the chain.

Monitoring can be done by with sensors that measure environmental conditions, like Time-Temperature loggers integrated with the package. The signal of this logger has to be translated into product quality by a suitable predictive model with the data on time and temperature as input together with quantitative information on the mechanism and kinetics of quality decay in the specific product.

More sophisticated direct quality sensors can monitor compounds in the product/package that are directly related with product quality. In this project the concept for a sensor for fresh fish quality has been developed. This sensor design needs further optimization. Also for this type of sensor a translation from the sensor signal into real product quality has to be made. Predictive models have to be developed and validated for this purpose.

Thesis objectives
Study the quality of fresh fish as a function of initial quality, time, temperature and packaging conditions. Measure sensor signals during storage and measure specific quality indicator compounds. This will be done by chemical, microbial and electrochemical analyses.  Develop predictive models for product quality related to the sensor signal. Validate the sensor system and model in a dynamic real-world simulation.

This topic is a collaboration between PDQ and A&F.

PhD-Project

Introduction
Innovative packaging with enhanced functions is constantly sought in response to consumer, producer, and government demands. Intelligent Packaging can be defined as: “Packaging systems that are capable of carrying out intelligent functions (such as detecting, sensing, recording, tracing, communicating, and applying scientific logic) to facilitate decision making to extend shelf life, enhance safety, improve quality, provide information, and warn about possible problems”.

Intelligent packaging systems contain internal or external sensors for monitoring external conditions (like temperature) or indicator compounds (like volatiles) from the food that can indicate the quality status of a food. The sensors can be linked to RFID-tags to communicate the sensor information during the whole supply chain.

Fresh packed fish is taken as an example within this project. The quality of fish is receiving a lot of attention, both by retailers and consumers. Freshness makes a major contribution to the quality of fish. An intelligent packaging sensor should monitor freshness indicator compounds and/or measure the storage environment and predict the freshness state of the fish.

Aim
The aim of this project is the development of intelligent packaging concepts that can monitor and predict food quality and/or safety within the supply chain. The intelligent packaging systems, based on internal or external sensors that are combined with mathematical models for food quality and safety, will be evaluated on their abilities to predict the quality and/or safety of perishable foods during the whole supply chain.

Research
To develop sensors for intelligent packages, quality or safety indicators from shelf life limiting reactions in perishable foods have to be identified. An overview of these sensors for different perishable food groups will be made. Kinetic modeling of these indication reactions need to be combined with the kinetics of sensors from intelligent packaging systems to be able to make predictions about the quality status.

Indicator compounds for the freshness of chilled (modified atmosphere) packed cod are being identified. The volatile amine TMA is formed by micro-organisms and causes the bad smell of spoiled fish. TMA is often used as indicator for the shelf life of chilled fish, but is mostly formed in the later stages of storage, prior to spoilage and is difficult to use as freshness indicator of very fresh fish. A conductivity sensor is being developed to measure the volatile amines within the headspace of the package. Other compounds, like DMA, NH3, ATP degradation products, aldehydes and ketones are also formed during the early stages of storage and are studied on their ability to be used as freshness indicator in intelligent packaging systems. Sensitive detection systems, which might be used in a packaging system, have to be found to measure the low concentrations of these compounds.

Future research
The rate of formation of indicator compounds depends largely on the storage temperature and the packaging atmosphere. We will measure indicator compounds, the sensor output and do microbial analyses in fresh cod packed in different gas compositions during storage at different temperatures. Mathematical models will be developed and validated for the formation of indicator compounds (the amines) and for the sensor data (the conductivity). Other influences on the signal of the sensor have to be studied and excluded to the prediction of the formation of the indicator compound.

Sensorial experiments need to be done to link the indicator value with the perceived quality of the fish.