Thermal Food Processing

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Thermal Processing of Canned Foods 349 254.6 233.0 214.4 FIGURE 11.9 A typical NumeriCAL modeled product temperature profile (°F) for canned beef chunk in gravy (300 × 405 can size) processed in a hydrostatic sterilizer (jh = 4.70, fh = 22.33, f2 = 43.71, xbh = 33.00, jc = 1.00, fc = 42.57). initial product temperature (15.2°C higher) by using the same input heating and cooling factors as the left curve. The agreement between the predicted and measured product temperatures (Figure 11.10, right curve) suggests that the model predictability is not affected by the initial product temperatures within the range studied. Figure 11.11 shows the chocolate drink packaged in 15.5-fluid oz glass bottles and processed in 119.4 and 125.6°C retort temperatures, respectively. The left curve shows modeling results on developing NumeriCAL heating and cooling factors (jh = 1.56, fh = 10.50, jc = 0.73, fc = 10.86). This set of heating/cooling factors was then used to predict the production temperature for a higher retort sterilization temperature (125.6°C), as shown in the right curve. It is clearly shown that the model-predicted product temperatures are on the conservative side. The result suggests that the commercial sterility value might not have been obtained if the input heating/cooling factors had been developed at a higher temperature in this case. Figure 11.12 shows the effect of the come-up and cooling profiles on the NumeriCAL model-predicted results. The left curve shows a normal sterilization process with 4.5 min come-up time for developing NumeriCAL heating and cooling factors (jh = 1.79, fh = 44.79, jc = 1.56, fc = 50.70). This set of input
350 Thermal Food Processing: New Technologies and Quality Issues FIGURE 11.10 NumeriCAL simulated product temperatures (°F) under different initial product temperatures (IT) with 15.2°C difference (tomato puree, 2:1 v/v in 300 × 405 cans). Left: Modeling the heat penetration data with IT of 29.5°C (85.1°F). Right: Predicting product temperatures with IT of 44.72°C (112.5°F) (jh = 1.68, fh = 48.19, jc = 1.67, fc = 50.30).
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Thermal Food Processing
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87. Polysaccharide Association Stru
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133. Handbook of Frozen Foods, edit
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Published in 2006 by CRC Press Tayl
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Various alternative thermal process
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Professor Sun is a fellow of the In
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Antonio Martínez Instituto de Agro
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Contents Part I: Modeling of Therma
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Chapter 17 Pressure-Assisted Therma
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1 CONTENTS Thermal Physical Propert
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Thermal Physical Properties of Food
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2 CONTENTS Heat and Mass Transfer i
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Heat and Mass Transfer in Thermal F
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5 CONTENTS Modeling Thermal Process
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Modeling Thermal Processing Using C
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6 CONTENTS Thermal Processing of Me
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Thermal Processing of Meat Products
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7 CONTENTS Thermal Processing of Po
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Thermal Processing of Poultry Produ
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9 CONTENTS Thermal Processing of Da
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Thermal Processing of Dairy Product
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14 CONTENTS Ohmic Heating for Food
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Ohmic Heating for Food Processing 4
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15 CONTENTS Radio Frequency Dielect
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Radio Frequency Dielectric Heating
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16 CONTENTS Infrared Heating Noboru
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Infrared Heating 495 0.78 1.4 Far-i
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Infrared Heating 497 A black body a
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Infrared Heating 499 Spectral atten
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Infrared Heating 501 Axial Distance
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Infrared Heating 503 the calculated
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Infrared Heating 505 TABLE 16.1 Com
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Infrared Heating 507 Rotating drum
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Infrared Heating 509 Conc. of acid
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Infrared Heating 513 Degradation ra
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Infrared Heating 517 T l (K) N l /
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Infrared Heating 519 Temperature (
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Infrared Heating 521 and thawing ti
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Infrared Heating 523 15. T Takeo. F
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Infrared Heating 525 55. CM Liu, N
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622 Index Aspergillus niger, 448 At
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624 Index Carrots activation energy
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628 Index dielectric properties of,
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630 Index Joule heating, see Ohmic
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636 Index Reynolds stress models, 5
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638 Index Tea, 451, 510 Temperature
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640 Index Wax beans, 398, 411 Web s
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Thermal Food Processing

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