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Natural convection heating of liquid food packed in glass jars of different sizes and volumes during sterilization is simulated by solving the governing equations for continuity, momentum and energy conservation, using the finite element method. The effect of the aspect ratio of the container on temperature distribution, flow pattern, position of the slowest heating zone (SHZ) and cooking value were analyzed. The position of the SHZ varied – depending of container volume and aspect ratio – in the range of 49.39–76.83% and 5.81–19.09% of jar radius and height, respectively. Sterilization times were estimated and differences between 135 and 105 s for containers of a same size of 360 or 660 cm3, respectively, were predicted depending on jar shape. A prediction model was developed that allows to calculate – with a simple procedure – sterilization times as a function of container dimensions. PRACTICAL APPLICATIONS It is frequent in low‐volume processing plants that work with foods packed in glass jars to change container size and/or shape between successive batches of production, but maintaining the same process schedule. This leads to products with lack of microbial innocuousness (underprocessing) or with low nutritional or sensory quality (overprocessing). In that sense, in this work velocity and temperature profiles, and the location of the “slowest heating zone” were modeled and simulated using the finite element method for liquid foods in glass jars of different volumes and shapes during their thermal treatment. This information allowed estimate sterilization times as well as quality losses during thermal treatment. Finally, a simplified method for the calculation of sterilization times as a function of container size and shape was developed. This method could be very practical for the design of thermal processes in low‐volume productions, whose operators usually lack simulation software and personnel trained in process calculations.

The aim of this work was to determine natural convective heat transfer rates in bottled liquid food pasteurized using different container orientations; conventional vertical, inverted vertical, and horizontal bottle positions. For this purpose, a computational fluid dynamic (CFD) model was applied to predict the temperature distribution, flow pattern, and quality changes in non‐Newtonian fluid foods for three orientations. The numerically predicted temperatures were successfully validated against experimental data and the model allowed to identify the critical point during the thermal process. Results showed that the fluid flow developed in a horizontal orientation provided a better mixing of liquid food and, hence, a more rapid heating of the slowest heating zone compared to a vertical position. Moreover, the horizontal orientation achieved a 47.2% reduction of processing time and quality losses decreased (45.5–46.4%) with respect to a vertical position. These results suggest that a horizontal position could be considered as an interesting alternative for food processors since processing times can be reduced improving the final quality of the product. Practical Applications Pasteurization is a heat treatment process applied to a food product with the purpose of destroying disease‐producing microorganisms, inactivating spoilage‐causing enzymes, and reducing spoilage microorganisms. Overcooking causes detrimental effects in terms of the final product quality. Therefore, providing an adequate process with a desired sterility is one of the challenges to canning industry. In this work, we investigate how to improve, through container orientation modification, the natural convective heat transfer rates during pasteurization of fluid food. These results were obtained by the numerical simulation of the thermal process using CFD analysis which allowed to determine the temperature history and velocity field in the bottled liquid food. From the numerical results, the set of operating conditions that enhance the quality and the safety of the final product was determined, thus minimizing expensive and time‐consuming pilot test‐runs.

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The influence of particle size (PZ) and processing temperature (PT) on quality attributes and processing time of pumpkin cubes packaged in glass jars were evaluated during their pasteurization. Secondorder polynomial models were developed for the following responses: texture retention (TR), total colour change (TCC) and heating time (HT), using multiple linear regression for a range of operating conditions (20-30 mm and 85-100°C for PZ and PT, respectively). A combination of the polynomial models with the methodology of desirability function was used for optimization of the pumpkin pasteurization process. The obtained optimal conditions were 20 mm and 100°C for PZ and PT, respectively; in order to obtain TR of 82.21%, TCC of 7.54 and HT of 44.97 min. However, these optimal conditions change to 100°C and 21 mm and the responses obtained are TR of 73.60%, TCC of 7.52 and HT of 39.66 min, when the processing time is prioritized.