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Environmental forecasting temperature models have high application value for building design, environmental impact assessment, and human wellness, as they apply to the development of human comfort devices. The current models used in this field are complex and involve many parameters, resulting in a considerable amount of data and a complicated modeling process. This research proposes two models: First, a type-Gaussian model with four parameters calculated to fit the environmental temperature. The proposed model employs the maximum and minimum temperatures ( T M a x , T M i n ) registered in a year for previously selected city or town and the relative time (day number of the year, 1–365). Second: A cosenoidal model to predict the continuous temperature in the day-night cycle of the selected day. This model requires T M a x and T M i n previously estimated via the Gaussian model and the hour in the day-night cycle at which the lowest temperature occurs. The Gaussian model is validated with data from different cities, achieving a high degree of confidence with a CV(RMSE) less than 2.0% in the cases analyzed. This model was compared to Artificial Neural Networks and other mathematical models previously published to confirm its functionality. The proposed models can be used in agriculture, civil engineering, food industry, power plants, biology, heat transfer, transportation, etc.

A numerical study on 2D natural convection in cylindrical cavities during the sterilization of liquid foods was performed. The mathematical model was established on momentum and energy balances and predicts both the heating dynamics of the slowest heating zone (SHZ) and the lethal rate achieved in homogeneous liquid canned foods. Two sophistication levels were proposed in viscosity modelling: 1) considering average viscosity and 2) using an Arrhenius-type model to include the effect of temperature on viscosity. The remaining thermodynamic properties were kept constant. The governing equations were spatially discretized via orthogonal collocation (OC) with mesh size of 25 × 25. Computational simulations were performed using proximate and thermodynamic data for carrot-orange soup, broccoli-cheddar soup, tomato puree, and cream-style corn. Flow patterns, isothermals, heating dynamics of the SHZ, and the sterilization rate achieved for the cases studied were compared for both viscosity models. The dynamics of coldest point and the lethal rate F0 in all food fluids studied were approximately equal in both cases, although the second sophistication level is closer to physical behavior. The model accuracy was compared favorably with reported sterilization time for cream-style corn packed at 303 × 406 can size, predicting 66 min versus an experimental time of 68 min at retort temperature of 121.1 ℃.

For any fermentation process, the production cost depends on several factors, such as the genetics of the microorganism, the process condition, and the culture medium composition. In this work, a guideline for the design of cost-efficient culture media using a sequential approach based on response surface methodology is described. The procedure was applied to analyze and optimize a culture medium of registered trademark and a base culture medium obtained as a result of the screening analysis from different culture media used to grow the same strain according to the literature. During the experiments, the procedure quantitatively identified an appropriate array of micronutrients to obtain a significant yield and find a minimum number of culture medium ingredients without limiting the process efficiency. The resultant culture medium showed an efficiency that compares favorably with the registered trademark medium at a 95% lower cost as well as reduced the number of ingredients in the base culture medium by 60% without limiting the process efficiency. These results demonstrated that, aside from satisfying the qualitative requirements, an optimum quantity of each constituent is needed to obtain a cost-effective culture medium. Study process variables for optimized culture medium and scaling-up production for the optimal values are desirable.

The kinetics of the thermal hydrolysis of the fructans of Agave salmiana were determined during the cooking step of mezcal production in a pilot autoclave. Thermal hydrolysis was achieved at different temperatures and cooking times, ranging from 96 to 116 °C and from 20 to 80 h. A simple kinetic model of the depolymerization of fructans to monomers and other reducing sugars and of the degradation of reducing sugars to furans [principally 5-(hydroxymethyl)furfural, HMF] was developed. From this model, the rate constants of the reactions were calculated, as well as the pre-exponential factors and activation energies of the Arrhenius equation. The model was found to fit the experimental data well. The tradeoff between a maximum fructan hydrolysis and a critical furan concentration in allowing for the best ethanol yield during fermentation was investigated. The results indicated that the thermal hydrolysis of agave was optimal, from the point of view of ethanol yield in the ensuing fermentation, in the temperature range of 106-116 °C and the cooking range time of 6-14 h. The optimal conditions corresponded to a fructan hydrolysis of 80%, producing syrups with furan and reducing sugar concentrations of 1 ± 0.1 and 110 ± 10 g/L, respectively.