No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Food Engineering Series
Abstract
Thermal processing is primarily concerned with the application of heat to destroy (inactivate) microorganisms (m.o.) and enzymes, which can cause spoilage of foods and health hazards to the consumers. Thermal processing involves heating of foods at various time—temperature combinations, which define the three main thermal processes, namely, blanching, pasteurization, and sterilization. The objective of thermal processing is the long-term and safe preservation of sensitive foods, preferably at ambient (room) temperatures. Traditionally thermal processing has been applied to the canning of foods, packaged in metallic containers, and preserved for long times (longer than 6 months).
... This method is also used to produce special foods and food ingredients and to process food industry by-products. There is a wide variety of industrial food drying equipment, mainly empirically developed, but continuously improved by recent advances in food drying and engineering technology [26]. The first activity of this teaching experiment offered students information about a radial airflow food drying equipment and also presented them with a mathematical model describing the percentage of moisture removed. ...
International research has revealed different roles of mathematics in the practices of engineers and some implications of mathematics teaching for engineering students. Modeling and mathematical models have proven to be valuable tools for their professional work and for their teaching process. This study identifies opportunities offered by a process of analysis of a mathematical model in the training of engineers. For this analysis, an interpretation of mathematical models as an object–user–representation triad was used; mathematical models were also considered a pedagogical approach to mathematics teaching. Based on this approach, a qualitative study was developed. A teaching experiment was designed, in which, through a set of tasks, the analysis of a model describing the percentage of moisture removed in a radial airflow food dryer is considered. Results show that students evidenced a comprehension of the model function as a covariation relationship and implemented strategies for understanding it through the graphs in the model. The situated character of students’ reasoning and their experience with professional practices of engineers are also highlighted.
Composite breads were made by supplementing wheat flour with chemically modified African yam bean and cassava starches after the flour – starch blends were produced from the cleaned seeds and roots using hammer milling system. Three mixture components were obtained from the D-optimal mixture design of Response Surface Methodology (RSM). The physical and sensory properties of the bread was determined and subjected to statistical analysis of variance (ANOVA) using cubic models to generate the regression equations from the experimental values. The linear, binary and ternary effects of the dependent responses and their interactions was generated and graphically represented using 3D response surface plots. The developed models were tested for adequacy and validated using criterion at p<0.05, non significant (p>0.05) lack-of-fit (LoF), >0.7 adjusted R2 and >4 adequate precision to confirm adequate model signals. The numerical optimization outcomes had the desirability value of 0.86 depicting the ideal value. The optimized values for the optimum blends selected were 80.15 g wheat flour, 11.23 g African yam bean starch and 8.53 g cassava starch which will give the best composite flour -starch blends for enhanced bread products. The optimization was confirmed by performing confirmatory runs determining the 95 % confidence levels of the blends. The D – optimal mixture design of response surface methodology with three experimental components was adequate (propagated the design space) in evaluating and optimizing of the dependent responses tested; bread height, oven spring, loaf weight, loaf volume, specific volume and bulk density, appearance, crumb and crust, taste, aroma and acceptability.
Composite breads were made by supplementing wheat flour with chemically modified African yam bean and cassava starches after the flour-starch blends were produced from the cleaned seeds and roots using hammer milling system. Three mixture components were obtained from the D-optimal mixture design of Response Surface Methodology (RSM). The physical and sensory properties of the bread was determined and subjected to statistical analysis of variance (ANOVA) using cubic models to generate the regression equations from the experimental values. The linear, binary and ternary effects of the dependent responses and their interactions was generated and graphically represented using 3D response surface plots. The developed models were tested for adequacy and validated using criterion at p<0.05, non significant (p>0.05) lack-of-fit (LoF), >0.7 adjusted R 2 and >4 adequate precision to confirm adequate model signals. The numerical optimization outcomes had the desirability value of 0.86 depicting the ideal value. The optimized values for the optimum blends selected were 80.15 g wheat flour, 11.23 g African yam bean starch and 8.53 g cassava starch which will give the best composite flour-starch blends for enhanced bread products. The optimization was confirmed by performing confirmatory runs determining the 95 % confidence levels of the blends. The D-optimal mixture design of response surface methodology with three experimental components was adequate (propagated the design space) in evaluating and optimizing of the dependent responses tested; bread height, oven spring, loaf weight, loaf volume, specific volume and bulk density, appearance, crumb and crust, taste, aroma and acceptability.
Composite breads were made by supplementing wheat flour with chemically modified African yam bean and cassava starches after the flour-starch blends were produced from the cleaned seeds and roots using hammer milling system. Three mixture components were obtained from the D-optimal mixture design of Response Surface Methodology (RSM). The physical and sensory properties of the bread was determined and subjected to statistical analysis of variance (ANOVA) using cubic models to generate the regression equations from the experimental values. The linear, binary and ternary effects of the dependent responses and their interactions was generated and graphically represented using 3D response surface plots. The developed models were tested for adequacy and validated using criterion at p<0.05, non significant (p>0.05) lack-of-fit (LoF), >0.7 adjusted R 2 and >4 adequate precision to confirm adequate model signals. The numerical optimization outcomes had the desirability value of 0.86 depicting the ideal value. The optimized values for the optimum blends selected were 80.15 g wheat flour, 11.23 g African yam bean starch and 8.53 g cassava starch which will give the best composite flour-starch blends for enhanced bread products. The optimization was confirmed by performing confirmatory runs determining the 95 % confidence levels of the blends. The D-optimal mixture design of response surface methodology with three experimental components was adequate (propagated the design space) in evaluating and optimizing of the dependent responses tested; bread height, oven spring, loaf weight, loaf volume, specific volume and bulk density, appearance, crumb and crust, taste, aroma and acceptability.
En este artículo se presenta un modelo dinámico para un recuperador de gases - sales fundidas incluido en una planta de demostración de una tecnología de hibridación de plantas termosolares con otras fuentes de energías renovables. Tanto el demostrador como el modelo se han desarrollado en el ámbito del proyecto HYSOL. Este trabajo describe brevemente dicho proyecto, su tecnología, demostrador y principalmente el modelo dinámico del recuperador, cuyo estado estacionario ha sido comparado con los cálculos de diseño. El artículo se completa con simulaciones dinámicas donde se estudia la convergencia del modelo, la contribución de los distintos procesos físicos a la transferencia de calor y el impacto de las condiciones ambientales a las pérdidas térmicas.
Recently developed procedures in designing aseptic processes for foods containing discrete particles are presented. The use of liquid crystals as temperature sensors for particle surface temperature measurements is discussed. Liquid-particle heat transfer coefficients during tubular flow heating in a holding tube simulating system are presented. An experimental methodology for particle residence time distribution measurements is outlined. A mathematical model for microbial destruction and quality factors retention calculations is presented. The effects of various product and processing parameters on process optimization, based on maximum thiamine retention, are briefly discussed.
Pasteurization and sterilization are well established methods for preserving foods. The dominating technique is in-container thermal processing where retorts with steam or hot water are used. Modern retorts are microprocessor-controlled, with possibilities to store processing cycles for a range of products. “Real time” process controllers are gradually coming. Modern retorting systems have automated equipment for pre- and post-retort handling of the containers. On-line integrity control for container leakage is under development.
Pasteurization and sterilization can also be done in-flow in indirect heat exchangers and direct heating equipment, using steam or electricity. Much development is taking place in using direct electric resistance (Ohmic) heating or dielectric microwave and high frequency heating of pumpable foods. There is a fair number of industries where microwaves are used for rapidly heating prepared foods to pasteurization temperatures and a few for microwave sterilization. Finally, a number of new non-thermal pasteurization and sterilization methods are being tried out at present; e.g. high pressure technique, high voltage pulses, light discharges.
Research at this laboratory for the past several years has involved determination of electrical conductivities of foods, microbial death kinetics, process modeling and experimental verification. Finite element models developed for heating of solid-liquid mixtures in a continuous flow ohmic heater indicate that if all particles and liquid are of equal electrical conductivities, the particle cold spots heat slightly faster than the liquid. For high concentration mixtures, if all particles are of low electrical conductivity, the mixture heats slowly due to high effective resistance, but the particles still heat faster than the fluid. However, if a single particle of unusually low electrical conductivity enters the heater, it will thermally lag the fluid since the current has alternate low-resistance pathways around it. Under these conditions, the potential for underprocessing exists. Particle concentration has been found to be important in determining whether or not particles heat faster than fluids. Under low concentrations, particles will typically lag fluids, while high concentrations favor faster particle heating. These findings have been verified experimentally in a static ohmic heater. Conditions involving a radial velocity profile are discussed.
Working groups discuss concerns that needed to be resolved to develop aseptic processes for foods containing particulates.
This chapter summarizes some basic principles associated with processing and preservation of food. Most food processes utilize six different unit operations such as heat transfer, fluid flow, mass transfer, mixing, size adjustment and separation. The scope of food processing describes unit operations occurring after harvest of raw materials until they are processed into food products, packaged, and shipped for retailing. The chapter explains food preservation methods that eliminate harmful pathogens present in the food and minimizing or eliminating spoilage microorganisms and enzymes for shelf life extension. The thermal properties of food are useful in identifying the extent of process uniformity during thermal processes such as pasteurization and sterilization. The food scientists and process engineers need to adequately characterize or gather information about relevant thermophysical properties of food materials being processed. Finally, the chapter highlights that the food processing operations chosen can influence the extent of changes in product quality attributes.
This chapter discusses on the mathematical methods for estimating proper thermal processes and their computer implementation. The basic principles for determining proper heat processes are described in the first section. It explains the published procedures for determining proper heat processes. The computerized estimation of heat processes is discussed at length. The chapter looks into the programs for estimating parametric values and programs for estimating heat processes without manual calculations. Mathematical procedures for heat process evaluation have been modified and improved by many research workers. Although most of the major problems were solved by these workers, further research which needs to be done in the future is discussed in this chapter.
In this review, current methods used to evaluate the integrated impact of time and temperature upon preserving a food product by a heat treatment are considered. After identifying the basic premise any preservation scheme shall meet, the central role of a feasible description for the heat activation kinetics of microorganisms, their spores, and other quality attributes are stressed. Common concepts to quantify a thermal process are presented. Shortcomings of the prevalent evaluation methods are highlighted and attention is given to the development, restrictions, and possibilities of time-temperature-integrators as "new" evaluation tools to measure the impact of a "classical" in-pack heat treatment and more modern heating techniques such as continuous processing of solid/liquid mixtures on foods.
A complete course in canning
- D L Downing
- Ii Ii
Unit operations for the food industries
- W A Gould
Heat transfer and temperature distribution in pasteurizing processes for packaged foods
- I J Britt
- M A Tung
- Z Yao
- A T Paulson
Tomato production processing and technology. Timonium, MD: CTI Publ. Gould, W.A. 1994.CGMP’s/food plant sanitation
- W A Gould
Heat transfer and food products
- B Hallstrom
- C Skjoldebrand
- C Tragardh
Progress in pasteurization and sterilization. InDevelopments in food engineeringPart 1
- T Ohlsson
InFrontiers in food engineering Proceedings of CoFE5
- Hydrostatic Batch
- Sterilizers
Continuous thermal processing of foods
- M Lewis
- N Heppell
Estimation of thermal death rate constants from inoculated pea puree undergoing thermal processing
- A A Teixeira
- M O Balaban
Lethality-based control of thermal processes for shelf stable foods in
- Z Weng
- D Park
A time-temperature integrator to quantify the effect of thermal processes on food quality
- A Williams
Aseptic processing of foodsTransport properties of foods
- H G D Reuter
Continuous sterilization of particulate foods by ohmic heating InDevelopments in food engineeringPart 2
- S K Sastry
Criteria for optimum design and operation of canned food plants: Batch processing
- R Simpson
- J Reveco
The time is now for the U.S. to capitalize on aseptic processing and packaging of particulate foods
- K R Swartzel
Flow of solid-liquid food suspensions
- S Liu
- J.-R Pain
- P I Fryer