QEEAT is a tool for assessing cold chains with respect to quality of products, energy use and environmental impact of refrigeration technologies involved in the food product cold chain. It contains predictions on how the quality and safety evolve along the cold chain as a function of user-defined temperatures and durations, and, likewise, how the energy use and TEWI (Total Equivalent Warming Impact) are linked to that same cold chain settings. Six main product categories have been considered: fruits, ready to eat meal, meat, fish, vegetable and milk products.
Mid July 2013, QEEAT release 3 has been made available to all partners of the FRISBEE consortium. This release is a so-called beta release: it is open for testing and bug reporting and will surely be improved in the coming months based on remarks and suggestions of the whole consortium.
The detailed technical functionalities of QEEAT Release 3 are the following:
• The user can select between a number of representative food products
• The user has the choice between two options: selecting a reference cold chain for each product and/or building a tailor-made cold chain using representative cold chain blocks
• The user can change properties of a selected product, and also settings of cold chain block technologies for up to six cold chains in parallel (Figure 1)
Figure 1: Freezing room description. Default values are provided for all relevant settings, while the user can also change some of these settings or can choose from a drop-down menu, like when considering the type of insulation in use in the storage room enclosures.
• Simulation of quantified CO2 emissions, static energy use (in kWh/kg) and all quality indicators relevant for the specific food product, is possible for one and up to six selected cold chains (Figure 2)
Figure 2: QEEAT Release 3 illustration of the evolution of one important quality indicator related with the potential spoilage of raw, smoked and salted ham. The reference cold chain where the chilled storage is at 2°C (Cold chain 1) is compared with a chain in which chilled storage is done at 5°C (Cold chain 2). For the other steps in these two cold chains, equal settings were chosen, resulting in the different lines running in parallel outside the chilled storage cold chain block.
• The cooling time (when entering the cold chain) can be predicted.
The next releases of the tool will be structured as follows:
• Release 4 will include extensions towards superchilling, supercooling, VIP and nanoparticles in the wall
• Release 5 will include the possibility of stochastic simulation
• Release 6 will be an extension towards multi-objective optimization
• Release 7 will be the final release and will contain the QEEAT calculations for other improving and new technologies not included in release 4