Predictive tool of energy performance of cold storage in agrifood industries: The Portuguese case study

• A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed.
• The correlations used by the predictive tool result from the greatest number of data sets collected to date in Portugal.
• Strong relationships between raw material, energy consumption and volume of cold stores were established.
• Case studies were analyzed that demonstrate the applicability of the tool.
• The tool results are useful in the decision-making process of practice measures for the improvement of energy efficiency.

Food processing and conservation represent decisive factors for the sustainability of the planet given the significant growth of the world population in the last decades. Therefore, the cooling process during the manufacture and/or storage of food products has been subject of study and improvement in order to ensure the food supply with good quality and safety. A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed in order to contribute to the improvement of the energy efficiency of this industry. The predictive tool is based on a set of characteristic correlated parameters: amount of raw material annually processed, annual energy consumption and volume of cold rooms. Case studies of application of the predictive tool consider industries in the meat sector, specifically slaughterhouses. The results obtained help on the decision-making of practice measures for improvement of the energy efficiency in this industry.