Numerical models of mass transfer during ripening and storage of salami

Published: 8 September 2013
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Ripening, in the dry sausages manufacturing process, has an influence over the main physical, chemical and microbiological transformations that take place inside these products and that define the final organoleptic properties of dry sausages. A number of study about the influence of ripening conditions on the main chemical and microbiological characteristics of dry sausages is available today. All these studies indicate that the final quality and safety standards achieved by the sausage manufacturing process can be considered to be strictly dependent from the specific ripening conditions. The water diffusion inside a seasoned sausage is surely an aspect of primary importance with regard to the quality of final product. As a consequence the aim of this research was to develop two parametric numerical models, concerning the moisture diffusion physics, describing salami ripening and storage. Mass transfer equations inside the sausage volume were numerically solved using a finite element technique. A first model describes diffusion phenomena occurring inside the salami and the exchange phenomena involving the surface of the product and the environment. After the ripening, the salami are stored in waterproof packaging, consequently an additional model able to describe also the evaporation and condensation phenomena occurring between the salami surface and the air in the package, was developed. The moisture equilibrium between salami surface and conservation atmosphere is mainly ruled by the temperature changes during storage. Both models allow to analyze the history of the moisture content inside the salami and are parametrised on product size and maturation/storage conditions. The models were experimentally validated, comparing the numerical outputs of the simulations with experimental data, showing a good agreement.

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How to Cite

Fabbri, A. (2013) “Numerical models of mass transfer during ripening and storage of salami”, Journal of Agricultural Engineering, 44(s2). doi: 10.4081/jae.2013.304.

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