Preparatory selection of sterilization regime for "canned natural Atlantic mackerel with oil" based on developed mathematical models of the process

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Definition of preparatory parameters for sterilization regime of canned "Natural Atlantic Mackerel with Oil" is the aim of current study. PRSC software developed at the department of automation and computer engineering is used for preparatory selection. To determine the parameters of process model, in laboratory autoclave AVK-30M the pre-trial process of sterilization and cooling in water with backpressure of canned "Natural Atlantic Mackerel with Oil" in can N 3 has been performed. Gathering information about the temperature in the autoclave sterilization chamber and the can with product has been carried out using Ellab TrackSense PRO loggers. Due to the obtained information three transfer functions for the product model have been identified: in the least heated area of autoclave, the average heated and the most heated. In PRSC programme temporary temperature dependences in the sterilization chamber have been built using this information. The model of sterilization process of canned "Natural Atlantic Mackerel with Oil" has been received after the pre-trial process. Then in the automatic mode the sterilization regime of canned "Natural Atlantic Mackerel with Oil" has been selected using the value of actual effect close to normative sterilizing effect (5.9 conditional minutes). Furthermore, in this study step-mode sterilization of canned "Natural Atlantic Mackerel with Oil" has been selected. Utilization of step-mode sterilization with the maximum temperature equal to 125 °C in the sterilization chamber allows reduce process duration by 10 %. However, the application of this regime in practice requires additional research. Using the described approach based on the developed mathematical models of the process allows receive optimal step and variable canned food sterilization regimes with high energy efficiency and product quality.

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Sterilization regime, model, energy consumption, software

Короткий адрес: https://sciup.org/14294963

IDR: 14294963   |   DOI: 10.21443/1560-9278-2016-4-861-868

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