Composition‐Based Prediction of Temperature‐Dependent Thermophysical Food Properties: Reevaluating Component Groups and Prediction Models

Abstract

Prediction of temperature-dependent thermophysical properties (thermal conductivity, density, specific heat, and thermal diffusivity) is an important component of process design for food manufacturing. Current models for prediction of thermophysical properties of foods are based on the composition, specifically, fat, carbohydrate, protein, fiber, water, and ash contents, all of which change with temperature. The objectives of this investigation were to reevaluate and improve the prediction expressions for thermophysical properties. Previously published data were analyzed over the temperature range from 10 to 150°C. These data were analyzed to create a series of relationships between the thermophysical properties and temperature for each food component, as well as to identify the dependence of the thermophysical properties on more specific structural properties of the fats, carbohydrates, and proteins. Results from this investigation revealed that the relationships between the thermophysical properties of the major constituents of foods and temperature can be statistically described by linear expressions, in contrast to the current polynomial models. Links between variability in thermophysical properties and structural properties were observed. Relationships for several thermophysical properties based on more specific constituents have been identified. Distinctions between simple sugars (fructose, glucose, and lactose) and complex carbohydrates (starch, pectin, and cellulose) have been proposed. The relationships between the thermophysical properties and proteins revealed a potential correlation with the molecular weight of the protein. The significance of relating variability in constituent thermophysical properties with structural properties--such as molecular mass--could significantly improve composition-based prediction models and, consequently, the effectiveness of process design.

The Complex Effect of Food Matrix Fat Content on Thermal Inactivation of Listeria monocytogenes: Case Study in Emulsion and Gelled Emulsion Model Systems

“…In general, results of the current study are more complex than the trend of linearly decreasing thermal conductivity with increasing food matrix fat content which has been commonly reported for both viscous (Pereira et al, 2013) and gelled emulsion (Baghe-Khandan et al, 1982;Tavman and Tavman, 1999) food products. Solely based on model system composition and following the modeling approach of Phinney et al (2017), thermal conductivity would decrease from approximately 0.63 W/(mK) at 1% fat to approximately 0.52 W/(mK) at 20% fat, almost independently of temperature (results not shown). Consequently, thermal conductivity values cannot be directly linked to the differences in thermal conductivity between sunflower oil and water (i.e., 0.168-0.162 and 0.598-0.660 W/(mK), respectively) over the relevant temperature range (Turgut et al, 2009;Sharqawy, 2013), implying that the thermal conductivity of the model systems was affected by phenomena occurring during the (gelled) emulsion preparation process, e.g., the homogenization step at 22 000 rpm.…”

“…Apart from the influence of bacterial species and strains, differences in inactivation kinetics could be caused, at least in part, by variations in compositional and physicochemical factors due to the use of real food products in the aforementioned studies. In addition, these microbiological studies did not take into account that food matrix fat content also influences heat transfer dynamics inside the food product during thermal processing, both when considering conductive and convective heat transfer (Cordioli et al, 2016;Phinney et al, 2017).…”

Densidade aparente dos resíduos da polpa de maracujá

“…De maneira intermediária, as sementes suspensas de Padrão 2, caracterizadas pela coloração amarronzada ou mais escura, estavam em estádio de maturação mais avançado que as sementes claras, porém com desenvolvimento parcial do endosperma, tornando-as menos densas que as sementes do Padrão 1 que eram claras, mas com maior conteúdo de endosperma. Destaca-se também que a presença de poros internos nas sementes exerce influência na densidade aparente, conforme relatado por Phinney et al (2017).…”

“…O volume do corpo submerso pode ser determinado a partir da densidade e massa do líquido de referência (PHINNEY et al, 2017).…”

The Impact of Cooling Rate on the Safety of Food Products as Affected by Food Containers

“…In general, the k ‐value outcomes of these studies were found to be inconsistent and this may be due to the different food materials studied with varying moisture contents. Only a few studies have investigated the k value in liquid foods that are mainly heated or cooled by convective heat transfer (Madoumier, Azzaro‐Pantel, Tanguy, & Gésan‐Guiziou, ; Muramatsu, Tagawa, & Kasai, ; Phinney, Frelka, & Heldman, ).…”