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It is known that the cooling of food prevents the reproduction of microflora, thus contributing to the preservation of the beneficial properties of products. Despite this, the cooling process is still the least studied stage of cold processing, which necessitates further in-depth study of the problem discussed in the article. Given the diversity and volume of processing facilities and the energy resources they consume, it is important to justify the analytical and numerical apparatus to address many engineering and plant-based cooling products of technological challenges. Below, in the article, computer-based tools are used to be different from the method used conveniently enough for practical purposes to quantify and calculate the common in production process of food freezing.

The main process that ensures the production of bread as a marketable product is the external thermal energy supply during baking. This process is accompanied by a complex physical phenomenon - moisture exchange between the dough-bread with the external environment and the steam-air environment of the baking chamber, as well as internal heat and mass transfer in the heated dough piece. At the same time, biochemical processes associated with the transformation of starch and proteins. Taking into account that the main factor realizing the efficiency and quality indicators of baked bread is heat exchange in the dough piece, in this article, taking into account the peculiarities of the dynamics of the heat transfer phenomenon, a quantitative analysis of the course of this process is carried out. In this work, in contrast to the results obtained by other researchers in the field of calculating the processes of heat treatment of food products, a quantitative analysis of the process is proposed based on a new methodological approach to the problem of physical and mathematical substantiation of the heat transfer process in a dough piece. That can be effectively used in the simulation of innovative samples of baking equipment.

BACKGROUND As an option for higher-tier leaching assessment of pesticides in Europe according to FOCUS, pesticide properties can be estimated from lysimeter studies by inversely fitting parameter values (substance half-life DT50 and sorption coefficient to organic matter kom). The aim of the study was to identify adequate methods for inverse modelling. RESULTS Model parameters for the PEARL (Pesticide Emission Assessment at Regional and Local scales) model were estimated with different inverse optimisation algorithms - the Levenberg-Marquardt ( LM), PD_MS2 ( PEST Driver Multiple Starting Points 2) and SCEM (Shuffled Complex Evolution Metropolis) algorithms. Optimisation of crop factors and hydraulic properties was found to be an ill-posed problem, and all algorithms failed to identify reliable global minima for the hydrological parameters. All algorithms performed equally well in estimating pesticide sorption and degradation parameters. SCEM was in most cases the only algorithm that reliably calculated uncertainties. CONCLUSION The most reliable approach for finding the best parameter set in the stepwise approach of optimising evapotranspiration, soil hydrology and pesticide parameters was to run only SCEM or a combined approach with more than one algorithm using the best fit of each step for further processing. PD_MS2 was well suited to a quick parameter search. The linear parameter uncertainty intervals estimated by LM and PD_MS2 were usually larger than by the non-linear method used by SCEM. With the suggested methods, parameter optimisation, together with reliable estimation of uncertainties, is possible also for relatively complex systems. © 2014 Society of Chemical Industry [ABSTRACT FROM AUTHOR]