A semi-empirical model for de-watering and cooling of leafy vegetables

• Published in: Applied thermal engineering Vol. 208; p. 118227
• Main Authors: Bianco, Nicola, Mauro, Alfonso William, Mauro, Gerardo Maria, Pantaleo, Antonio Marco, Viscito, Luca
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 25.05.2022; Elsevier BV
• Subjects: Agri-food; Cooling; De-watering; Digital models; Digitization; Empirical analysis; Food processing industry; Food science; Fresh leafy vegetables; Heat transfer; Heat transfer coefficients; Microbalances; Modules; Moisture content; Moisture effects; Optimization; Parametric analysis; Performance assessment; Porous media; Temperature effects; Vegetables; Water masses; De-watering; Agri-food; Food science; Food processing industry; Fresh leafy vegetables; Digital models
• ISSN: 1359-4311; 1873-5606
• DOI: 10.1016/j.applthermaleng.2022.118227

[Display omitted] •Integrated and energy efficient leafy vegetables processing is proposed.•A semi-empirical approach is presented to model the fresh vegetables de-watering and cooling processes.•Mass and heat transfer processes are calibrated with experimental data.•Model validation vs real experimental data is satisfactory given the uncertainty of input data.•Operational maps are provided to define optimal process conditions. This paper presents a semi-empirical model for mass and heat transfer applied to de-watering and cooling of fresh leafy vegetables. This process aims at optimizing vegetables’ moisture content and temperature through the interaction with conditioned airflows to ensure proper storage and preservation. It is implemented in different modules – i.e., a first set of hot modules with hot air, a second set of cold modules with cold air – allowing to remove water from the vegetables and to achieve the desired temperature. A dedicated transfer model is developed to follow the evolution of the liquid droplets on the leaves during the process. It is based on water mass and energy balances on product and air sides, where the bed of leaves is treated as a porous medium. The mass and heat transfer coefficients are calibrated by comparison with experimental data. The model is validated with real data from the field, and a parametric analysis is implemented to show its potential application to optimize the process. The calibrated model presents satisfactory reliability – less than ±1.0 °C as average error for output temperature – according to the uncertainty of the approaches available in literature, thereby ensuring a robust performance assessment. This can support the process application in several fields of the agri-food industry with significant quality and productivity improvements. Finally, the model can be used to develop digital twins to foster the ongoing digitalization of the agri-food sector with a view to sustainability.