Interactions between refrigeration temperatures, energy consumption in a food plant and microbiological quality of the food product: Application to refrigerated stuffed pasta

• Published in: Food control 2021-08, Vol.126, p.108076, Article 108076
• Main Authors: Duret, Steven, Hoang, Hong-Minh, Guillier, Laurent, Derens-Bertheau, Evelyne, Dargaignaratz, Claire, Oriol, Stéphanie, Delahaye, Anthony, Laguerre, Onrawee, Nguyen-the, Christophe
• Format: Article
• Language: English
• Subjects: Bacillus cereus; Bacteriology; Cold chain; Food engineering; Food safety; Life Sciences; Microbiology and Parasitology; Multi-criteria modelling; Refrigeration; Spoilage
• ISSN: 0956-7135; 1873-7129
• DOI: 10.1016/j.foodcont.2021.108076

Food refrigeration is essential to maintain microbiological quality but it accounts for high energy impact. An integrative modelling approach was developed to estimate the impact of increasing refrigeration temperature in the processing plant, on energy consumption, products temperatures, and the food product microbiology. The food product was a pasteurized refrigerated fresh pasta. The microbial indicators considered were Bacillus cereus for safety and total aerobic microflora for spoilage, with limits at consumption of respectively 105 CFU g−1 and 106 CFU g−1. Through six scenarios, the impacts of temperatures ranging from −2 °C to 8 °C in the cooling tunnel, and from 4 °C to 6 °C in the end products cold room storage in the processing plant, were simulated. The same refrigeration conditions throughout the entire cold chain up to the consumer, based on temperature and residence time data of a field study, were applied to all these processing plant refrigeration scenarios. Fixing 8 °C to the cooling tunnel and 6 °C to the cold room reduced the absorbed electrical power by ~20% with ~10% increase of microbiologically defective products at time of consumption. Increasing cooling tunnel temperature saved more energy than increasing cold room temperature for the same impact on microbiology. The modelling approach presented could help food companies to design the best strategy to reduce refrigeration energy consumption in their processing plant. •Decision support models of food plant operation can be developed from sparse data.•In the processing plant, forced air cooling was the best step to save energy.•Food processing plant, professional and domestic cold chains were modeled.•Defective products were caused by improper cold chain conditions at consumer level.•Multi-criteria models could help food plant operators in production strategy.