Shelf-life Estimation1 FST 151 FOOD FREEZING FOOD SCIENCE AND TECHNOLOGY 151 Shelf-life Prediction of Frozen Foods & Case Studies Lecture Notes Prof. Vinod.

Slides:



Advertisements
Similar presentations
OFF DESIGN PERFORMANCE PREDICTION OF STEAM TURBINES
Advertisements

This show will proceed as you click your mouse Exit.
Process Control: Designing Process and Control Systems for Dynamic Performance Chapter 6. Empirical Model Identification Copyright © Thomas Marlin 2013.
Food Storage and Preservation. Storage and Preservation  Principles of Preservation  Methods of Preservation  Drying, curing & smoking  Fermentation.
Cold preservation Refrigeration and cool storage Freezing.
CHAPTER V CONTROL SYSTEMS
Technology of frozen foods
Department of Mechanical Engineering ME 322 – Mechanical Engineering Thermodynamics Lecture 19 Calculation of Entropy Changes.
Meat evaluation There are some important parameters such as temperature, acidity (pH), water activity (aw) and cooking loss. Other physical parameters.
Topic 5: Enzymes Pg
Intelligent packaging
Preservation of Seafoods FSN 261 Spring 2011 Chuck Crapo Seafood Technology Specialist 1.
 Crystal size distribution (CSD) is measured with a series of standard screens.  The size of a crystal is taken to be the average of the screen openings.
HACCP School Development Project Chapter 11 Quality and Food Safety By Andrea Boyes and Julia Wood Srednja šola Zagorje.
L Berkley Davis Copyright 2009 MER301: Engineering Reliability Lecture 14 1 MER301: Engineering Reliability LECTURE 14: Chapter 7: Design of Engineering.
Department of Food Science
Development of Empirical Models From Process Data
CHAPTER 6 Statistical Analysis of Experimental Data
MATH408: Probability & Statistics Summer 1999 WEEKS 8 & 9 Dr. Srinivas R. Chakravarthy Professor of Mathematics and Statistics Kettering University (GMI.
High Pressure Food Freezing Prof. Vinod Jindal 1 FST 151: FOOD FREEZING High Pressure Food Freezing Lecture Notes Prof. Vinod K. Jindal (Formerly Professor,
Food Freezing Basic Concepts (cont'd) - Prof. Vinod Jindal
Differential Equations 7. The Logistic Equation 7.5.
IE-331: Industrial Engineering Statistics II Spring 2000 WEEK 1 Dr. Srinivas R. Chakravarthy Professor of Operations Research and Statistics Kettering.
Freeze Concentration - Vinod Jindal 1 FST 151 FOOD FREEZING FOOD SCIENCE AND TECHNOLOGY 151 Special topics: Freeze Concentration Lecture Notes Prof. Vinod.
© Food – a fact of life 2009 Principles of home food preservation Foundation DRAFT ONLY.
Chemometrics Method comparison
Special topics: Freeze Drying Lecture Notes
Hazard Analysis Critical Control Point (HACCP)
Ch 8.1 Numerical Methods: The Euler or Tangent Line Method
9 DIFFERENTIAL EQUATIONS.
Energy and Chemical Reactions in Cells
COURSE SYNOPSIS Taxonomy, ecology, biochemistry and analytical technology of food microorganisms. Sources of microorganisms in food; distribution, role.
Week: 14 REFRIGERATED STORAGE INTRODUCTION PRINCIPLES OF REFRIGERATED STORAGE CONTROL OF MICROBIAL GROWTH DURING REFRIGERATEED STORAGE ESTABLISHING SHELF-LIFE.
BASELINE software tool for calculation of microbiological criteria and risk management metrics for selected foods and hazards WP6 Model Development Final.
MECN 3500 Inter - Bayamon Lecture 3 Numerical Methods for Engineering MECN 3500 Professor: Dr. Omar E. Meza Castillo
State Key Laboratory for Physical Chemistry of Solid Surfaces 厦门大学固体表面物理化学国家重点实验室 Statistical Thermodynamics and Chemical Kinetics State Key Laboratory.
FRACTURE MECHANICS AND FATIGUE DESIGN HANS MF PANJAITAN Marinteknisk Senter Otto Nielsens Veg Trondheim Norway Mobile:
DENNIS R. HELDMAN DALE A. SEIBERLING FOOD ENGINEERING RESEARCH LABORATORY Using Off-Peak Power Rates to Reduce Refrigeration Costs.
Arnold’s Food Chemistry Lesson 5: Food Preserving/Processing Methods.
Sampling Design and Analysis MTH 494 Lecture-22 Ossam Chohan Assistant Professor CIIT Abbottabad.
Food Freezing Quality Aspects - Prof. Vinod Jindal
Lecture – 3 The Kinetics Of Enzyme-Catalyzed Reactions Dr. AKM Shafiqul Islam
Growth Kinetics of Parent and Green Fluorescent Protein-Producing Strains of Salmonella Thomas P. Oscar, Agricultural Research Service, USDA, 1124 Trigg.
Food Freezing Basic Concepts (cont'd) - Prof. Vinod Jindal 1 FST 151 FOOD FREEZING FOOD SCIENCE AND TECHNOLOGY 151 Food Freezing - Basic concepts (cont’d)
BME 353 – BIOMEDICAL MEASUREMENTS AND INSTRUMENTATION MEASUREMENT PRINCIPLES.
Copyright © Cengage Learning. All rights reserved. 9 Differential Equations.
Unit Food Science. Problem Area Processing Animal Products.
Microbial growth in:- Closed Cultivation Systems Open Cultivation Systems Semi-Open Cultivation Systems.
1 Development of Empirical Models From Process Data In some situations it is not feasible to develop a theoretical (physically-based model) due to: 1.
© 2014 Carl Lund, all rights reserved A First Course on Kinetics and Reaction Engineering Class 9.
1 Engineering Materials Chapter 3. 2 INTRODUCTION Within the last couple of decades, very rapid development of engineering materials has taken place,
Microbial kinetics of growth and substrate utilization. Batch culture and Kinetics of Microbial growth in batch culture After inoculation the growth rate.
BY: M.SC. MOHAMMED SABAH Chapter 8. Irradiation. Ionising radiation takes the form of -rays from isotopes or, commercially to a lesser extent, from X-rays.
Engineering Statistics Design of Engineering Experiments.
© Food – a fact of life 2009 Hazard Analysis Critical Control Point (HACCP) HACCP is a system which looks for and prevents potential problems before they.
Food preservation and processing by use of low temperature
T 1/2 : Half Life Chemical Kinetics-6. Can be derived from integrated rate law.
Control engineering ( ) Time response of first order system PREPARED BY: Patel Ravindra.
Lecture 2   Meat drying in combination with additional treatment i) Pre-salting ii) cured dried meat iii) smoked dried meat iv) dried meat with spices.
Behaviour of agricultural/food materials under stress
Thermal and Non-Thermal Preservation
Principles of home food preservation.
Food components in food sciences (basic food chemistry)
WHO Technical Report Series, No. 953, 2009
Immobilized enzyme system
ITD – MST : Physical preservation of meat
Control of Microorganisms by Physical and Chemical Agents
Bioreactors Engineering
Principles of home food preservation
FDE 101-Basic Concepts in Food Engineering
Presentation transcript:

Shelf-life Estimation1 FST 151 FOOD FREEZING FOOD SCIENCE AND TECHNOLOGY 151 Shelf-life Prediction of Frozen Foods & Case Studies Lecture Notes Prof. Vinod K. Jindal (Formerly Professor, Asian Institute of Technology) Visiting Professor Chemical Engineering Department Mahidol University Salaya, Nakornpathom Thailand

Shelf-life Estimation2 We freeze foods to extend their storage life by making them more inert. A range of physical and biochemical reactions continues however and many of these will be influenced when storage conditions are altered. To a large extent we are unconcerned with the microbiology of frozen foods since no microorganisms grow below - 10 o C. The production of safe frozen foods requires the same attention to good manufacturing practice (GMP) and HACCP principles as in the case of fresh foods.

Shelf-life Estimation3 Shelf-Life Prediction of Frozen Foods Fresh or chilled foods normally have a single dominant deterioration mechanism (e.g., microbial spoilage). It is relatively easy to model the effect of temperature on the microbial growth. These models can be used to calculate when the microbial load will exceed a safe limit and thus to determine the safe shelf-life.

Shelf-life Estimation4 The prediction of the shelf-life of frozen foods is difficult because of many spoilage mechanisms present in them. These include enzymatic deterioration, cell damage and protein and starch interactions, non-enzymatic browning, water migration (both during freezing and storage), water re-crystallization and change in crystalline form, solute crystallization, oxidative deterioration (e.g., lipid oxidation in fatty meats and color changes in fish and meat), protein denaturation (which may alter water-binding capacity), and lastly, microbial changes.

Shelf-life Estimation5 Normal frozen food storage temperatures (-18 to -22 o C) are significantly higher than the glass transition temperature and will consequently contain some unfrozen water. FROZEN FOODS: WHY IT IS DIFFICULT TO PREDICT SHELF-LIFE A. UNFROZEN WATER AND GLASS TRANSITION B. DETERIORATION MECHANISMS

Shelf-life Estimation6

7

8

9 APPROACHES TO SHELF-LIFE DETERMINATION Most food engineers and technologists like to model shelf- life based on the kinetics of deterioration. As most of the deterioration mechanisms in frozen foods follow either zero- order or first-order kinetics, the modeling of shelf-life should be a simple exercise. However, the kinetic data for so many deterioration mechanisms are not easily available for the frozen food storage conditions. Additionally, many foods may undergo more than one deterioration reaction and the combined effects of these would need to be assessed. Therefore, many laboratory- based procedures have been introduced.

Shelf-life Estimation10 A. TIME TEMPERATURE TOLERANCE (TTT) The time–temperature–tolerance (TTT) experiments were introduced by the USDA laboratories in the 1960s. The assumption made for TTT experiments is that for every food there is a relationship between the storage temperature and the time taken to undergo a certain amount of quality deterioration. Such changes during storage at different temperatures are cumulative and irreversible. It is generally agreed that the most detrimental factor influencing frozen food quality is fluctuation in storage temperature and this will significantly reduce the shelf-life of the product.

Shelf-life Estimation11 B. PRACTICAL STORAGE LIFE A more commonly used descriptor was later introduced named the practical storage life (PSL). This is defined as the period of storage during which the frozen food retains its quality characteristics and is suitable for consumption. Though both the effect of temperature and food type are included for a number of food products, fluctuating storage temperatures can cause problems.

Shelf-life Estimation12 C. HIGH-QUALITY LIFE (HQL) This is the most common shelf-life determinant parameter used in the food industry. In reality, this is a time– temperature–tolerance variable but differs from the others in that sensory quality is used in its determination. It is normally defined as the time elapsed between freezing and the time when a statistically significant difference (P< 0.1) can be detected by sensory evaluation. A simpler exercise may be the determination of the elapsed time at which 70% of a trained taste panel can identify a noticeable difference between the frozen food in question and a control when using a triangular test. The control would normally have been stored at -35 o C.

Shelf-life Estimation13 where t θ is the storage time at a temperature θ and HQL θ, the high-quality life at the same temperature. The values of HQL θ can be read from the chart or, alternatively, the experimental curves from which the chart was derived can be expressed in the form When different storage conditions are used during the life of the product, the HQL needs to be integrated over the different temperatures. For acceptable quality, it is essential that

Shelf-life Estimation14 Where D is analogous to the decimal reduction time in bacterial killing. It is found from two points on the semi-log plot of HQL versus θ. In fact D can be calculated as where HQL ref is the high-quality life at a reference temperature θ ref. A typical plot from which D is derived is shown in Figure 28.1.

Shelf-life Estimation15 FIGURE 28.1 Plot of shelf-life versus temperature for a typical food.

Shelf-life Estimation16 D.ACCELERATED MEASUREMENT AND THE Q 10 APPROACH The above type of plot can also be used for the so-called Q 10 approach. This estimates the effect of temperature on the accelerated deterioration of shelf-life. In its simplest form, it can be expressed as the ratio of the rate of deterioration at a temperature of θ+10 o C to that at a temperature of θ. Alternatively, it can be expressed as

Shelf-life Estimation17 An advantage of Q 10 approach is the ability to conduct accelerated experimental shelf-life trials at elevated temperatures and then extrapolate the results to normal storage conditions. Such tests are widely used in the food industry. However, exact values of Q 10 are difficult to find for many foods and approximate values are frequently used. IV. METHODS USED FOR SPECIFIC FOODS Despite the significant research efforts applied to shelf- life determination of frozen foods, there is no single, universally accepted method available for application to the food industry. Th. e available data are scarce. The rate constants for the common deterioration reactions are not available for a wide range of frozen foods.