Open Innovation Submission Portal

Modelling and prediction of product changes during storage and shelf-life

Request Number 180035 | Author Mondelēz International

Description

We are looking for systems that provide comprehensive and robust modelling and prediction of product changes during storage to determine commercial shelf-life without real-time storage testing. Changes detected could include chemical and/or structural changes that could affect texture or taste. Solutions must also consider multiple storage conditions (temperature, humidity, light, oxygen).

Background

Even small changes to our recipes and processes can have significant impact on shelf-life. This means that we have to perform extensive shelf-life testing for even small changes - this can be time-consuming and costly.

We want a tool that will allow us to better assess shelf-stability risks and accelerate project implementation by avoiding full scale storage tests.

Key Success Criteria

Your solution should be able to demonstrate a correlation between simulation and descriptive sensory for a range of scenarios representing different failure mechanisms (e.g. lipid oxidation, state and phase transition, color degradation, flavor degradation). Prediction model should be validated against real time storage of real product.

Possible Approaches
  • Prediction model
  • Computer Modelling
  • Artificial Intelligence
  • Neural Networks
What We Aren't Interested In

Accelerated shelf-life tests (storage at elevated temperature)

Preferred Collaboration types

At this stage, we're open to various types of mutually-beneficial partnerships.

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