The Effect of Consumer Cooking Methods on the Quality of Atlantic Salmon and Shrimp

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A variety of cooking methods are practiced by consumers in order to prepare cooked foods. Pan frying, oven baking, and boiling are all common methods used to cook a raw product to a point of doneness. This level of “doneness” is a consumer’s perception as to when the food item is ready to be consumed. However, this quality measurement may not satisfy the appropriate confirmation of microbial inactivation in the product. This false perception is a current issue for the cooking process of seafood products. It is important to understand how the cooking process affects both the quality aspects and microbial survival trends for the product in order to optimize the quality and safety of the product. This review provides information on the basics of thermal food processing, the properties affected, safety concerns with seafood products, and the current research on optimizing food quality and safety

Introduction to Thermal Food Processing

Thermal processing can be defined as the controlled use of heat to alter the rate of reactions in foods (Earle, 1983). Several methods are used in applying heat to a food product. Methods from simply applying steam to using an advanced ohmic heater can be used to successfully thermally process a food, depending on the desired effect. In large scale production,a food material may go through thermal processing at various stages during preparation towards a final product. Heat application is frequently used in secondary processing stages such as radiation, pasteurization, drying, and packaging. Packaging processes such as bottling and canning use heat to stabilize the food and to provide sterilization (Holdsworth and Simpson, 2007).Along with the uses of thermal processing during the commercial production of a food product, heat application is also used by the actual consumer. A variety of cooking methods are used by consumers to create the final product they desire. While it is not possible to enforce specific cooking methods on consumers, suggested guidelines are provided by various organizations. The National Sanitation Foundation provides various tips, like how to properly cook using a microwave and how to monitor the temperature of a cooked product (NSF International, 2004). Together, the Food and Drug Administration (FDA), the Centers for Disease Control and Prevention (CDC), and the Food Safety and Inspection Service (FSIS) provide updated editions of the Food Code. The Food Code is a reference document for foodservice operations, retail food stores, and interested consumers. It establishes science-based guidelines and enforceable provisions for risk processes related to foodborne illness (FDA,2009). Information is provided on a variety of practices, from maintaining hygiene to reaching specific internal temperatures for specific food products


Food Properties Affected During the Cooking Process

When studying the processing of a material, it is necessary to understand its natural properties. Several engineering properties distinguish a food product and make it unique. They are generally any attribute affecting the handling or processing of a food and the majority can be classified as thermal, electrical, optical, and mechanical. These parameters can significantly change when the food is structurally altered. There are intrinsic properties as well, which are primarily controlled by the material itself (Barbosa-Canovas et al., 2004). Mathematical modeling can be used to investigate factors affected during the cooking of foods. Prediction models for quality change can be created by applying kinetic models to experimental data. Connecting quality parameters to cooking methods allows for the optimization of the cooking process as a whole. For example, Haiqing et al. (1999) created a model that successfully predicted transient temperature and moisture distributions during convection cooking of chicken patties. From these prediction models, conclusions can be made on the optimal time-temperature combination for this specific food product. To effectively model the cooking of a food, it is necessary to first understand the basic properties of the food material being studied. Mechanical Properties In order to appropriately characterize a food material, the structural properties and strength properties must be evaluated. Density, porosity, and shrinkage are common structural properties that are studied. Texture is an important strength attribute on a food material and affects consumer perception of quality. Instrumental measuring devices have been developed that correlate to the quality of sensory measurements. One current test of food texture is Texture Profile Analysis (TPA), which was created by General Foods in the 1960’s (Rosenthal, 1999). Through the use of a texture analyzer, parameters ranging from hardness to elasticity to chewiness can be equated. Modeling an accurate relationship between sensory and instrumental measurements can aid in predicting which sensory attributes affect a food material’s quality,such as moisture, deformability modulus, and slope in puncture (Benedito, 2000).Electrical Properties Electrical conductivity and electrical permittivity are useful properties to understand in the electrical electromagnetic processing and resulting quality of foods. By correlating these properties with other characteristics of the food, the effects of electroprocessing can be better understood. Measuring conductivity is particularly useful during ohmic and conventional heating methods (Barbosa-Canovas, 2004). The bulk dielectric properties (dielectric constant, dielectric loss factor) are principally studied to aid in predicting heating rates of materials subjected to microwave electric fields or high frequency. Models for a wide range of frequencies have been created comparing dielectric properties and their effects in food processing (Vankatesh, 2005). Dielectric properties of food products assist in optimizing packaging materials and the design of radio frequency and microwave heating equipment. Dielectric properties data have also been investigated to optimize uniform microwave heating (Chatterjee, 2007)

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