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EbookNice Team
Status:
Available4.7
21 reviewsISBN 10: 1482216905
ISBN 13: 978-1482216905
Author: Morten C Meilgaard
This new edition of a bestseller covers all phases of performing sensory evaluation studies, from listing the steps involved in a sensory evaluation project to presenting advanced statistical methods. Like its predecessors, Sensory Evaluation Techniques, Fifth Edition gives a clear and concise presentation of practical solutions, accepted methods, standard practices, and some advanced techniques. The fifth edition is comprehensively reorganized, revised, and updated. Key highlights of this book include: A more intuitive organization Statistical methods adapted to suit a more basic consumer methodology Rearranged material to reflect advances in Internet testing New time-intensity testing methods New chapters on advanced sensory processes, quality control testing, advertising claims, and business challenges New material on mapping and sorting, graph theory, multidimensional scaling, and flash profiling techniques Explanations of theories of integrity, amplitude, and balance and blend Updated appendices for spectrum method scales Updated references Sensory Evaluation Techniques remains a relevant and flexible resource, providing how-to information for a wide variety of users in industry, government, and academia who need the most current information to conduct effective sensory evaluation and interpretations of results. It also supplies students with the necessary theoretical background in sensory evaluation methods, applications, and implementations.
I Introduction to Sensory Techniques
1.1 Introduction
1.2 Development of Sensory Testing
1.3 Human Subjects as Instruments
1.3.1 Chain of Sensory Perception
1.4 Conducting a Sensory Study
References
2 Sensory Attributes and the Way We Perceive Them
2.1 Introduction
2.2 Sensory Attributes
2.2.1 Appearance
Odor/Aroma/Fragrance
2.2.3 Consistency and Texture
2.2.4 Flavor
2.2.5 Noise
2.3 Human Senses
2.3.1 Sense of Vision
2.3.2 Sense of Touch
2.3.3 Olfactory Sense
23.3.1 General
2.3.3.2 Retronasal Odor
23.3.3 Odor Memory
2.3.4 Chemical/Trigeminal Sense
2.3.5 Sense of Gustation/Taste
2.3.6 Sense of Hearing
2.4 Perception at Threshold and Above
References
3 Controls for Test Room, Products, and Panel
3.1 Introduction
3.2 Test Controls
3.2.1 Development of Test-Room Design
3.2.2 Location
3.2.3 Test-Room Design
3.2.3.1 Booth
3.2.3.2 Descriptive Evaluation and Training Area
3.2.3.3 Preparation Area
3.2.3.4 Office Facilities
3.2.3.5 Entrance and Exit Areas
3.2.3.6 Storage
3.2.4
General Design Factors
3.2.4.1 Color and Lighting
3.2.4.2 Air Circulation, Temperature, and Humidity
3.2.4.3 Construction Materials
3.3 Product Controls
3.3.1
General Equipment
3.3.2 Sample Preparation
3.3.2.1 Supplies and Equipment
3.3.2.2 Materials
3.3.2.3 Preparation Procedures
3.3.3 Sample Presentation
3.3.3.1 Container, Sample Size, and Other Particulars
3.3.3.2 Order, Coding, and Number of Samples
3.3.4 Product Sampling
3.4 Panelist Controls
3.4.1 Panel Training or Orientation
3.4.2 Product/Time of Day
3.4.3 Panelists/Environment
References
4 Factors Influencing Sensory Verdicts
4.1 Introduction
4.2 Physiological Factors
4.2.1 Adaptation
4.2.2 Enhancement or Suppression
4.3 Psychological Factors
4.3.1 Expectation Error
4.3.2 Error of Habituation
4.3.3 Stimulus Error
4.3.4
Logical Error
4.3.5 Halo Effect
4.3.6 Order of Presentation of Samples
4.3.7 Mutual Suggestion
4.3.8 Lack of Motivation
4.3.9 Capriciousness versus Timidity
4.4 Poor Physical Condition
References
5 Measuring Responses
5.1 Introduction
5.2 Psychophysical Theory
5.2.1 Fechner's Law
5.2.2 Stevens' Law
5.2.3 Beidler Model
5.3 Classification
5.4 Grading
5.5 Ranking
5.6 Scaling
5.6.1 Category Scaling
5.6.2 Line Scales
5.6.3 Magnitude Estimation Scaling
5.6.3.1 Magnitude Estimation versus Category Scaling
5.6.3.2 Magnitude Matching (Cross-Modality Matching)
5.6.4 Labelled Magnitude Scales (LMS)
References
6 Guidelines for Choice of Technique
6.1 Introduction
6.2 Define the Project Objective
6.3 Define the Test Objective
6.4 Review Project Objective and Test Objectives: Revise Test Design
Reference
7 Overall Difference Tests: Does a Sensory Difference Exist between Samples?
7.1 Introduction
7.2 Unified Approach to Difference and Similarity Testing
7.3 Triangle Test
7.3.1 Scope and Application
7.3.2 Principle of the Test
7.3.3 Test Subjects
7.3.4 Test Procedure
7.3.5 Analysis and Interpretation of Results
7.4 Duo-Trio Test
7.4.1 Scope and Application
7.4.2 Principle of the Test
7.4.3 Test Subjects
7.4.4 Test Procedure
7.5 Two-out-of-Five Test
7.5.1 Scope and Application
7.5.2 Principle of the Test
7.5.3 Test Subjects
7.5.4 Test Procedure
7.6 Same/Different Test (or Simple Difference Test)
7.6.1 Scope and Application
7.6.2 Principle of the Test
7.6.3 Test Subjects
7.6.4 Test Procedure
7.6.5 Analysis and Interpretation of Results
7.7 "A"-"Not A" Test
7.7.1 Scope and Application
7.7.2 Principle of the Test
7.7.3 Test Subjects
7.7.4 Test Procedure
7.7.5 Analysis and Interpretation of Results
7.8 Difference-from-Control Test
7.8.1 Scope and Application
7.8.2 Principle of the Test
7.8.3 Test Subjects
7.8.4 Test Procedure
7.8.5 Analysis and Interpretation of Results
7.9 Sequential Tests
7.9.1 Scope and Application
7.9.2 Principle of the Test
7.9.3 Analysis and Interpretation of Results: Parameters of the Test
References
8 Attribute Difference Tests: How Does Attribute X Differ between Samples?
8.1 Introduction: Paired Comparison Designs
8.2 Directional Difference Test Comparing Two Samples
8.2.1 Scope and Application
8.2.2 Principle
8.2.3 Test Subjects
8.2.4 Test Procedure
8.3 Specified Method of Tetrads: Comparing Two Samples on a Specified Attribute Using the Method of Tetrads
8.3.1 Scope and Application
8.3.2 Principle of the Test
8.3.3 Test Assessors
8.3.4 Test Procedure
8.4 Pairwise Ranking Test: Friedman Analysis-Comparing Several Samples in All Possible Pairs
8.4.1 Scope and Application
8.4.2 Principle of the Test
8.4.3 Test Subjects
8.4.4 Test Procedure
8.5 Introduction: Multisample Difference Tests-Block Designs
8.5.1 Complete Block Designs
8.5.2 Balanced Incomplete Block (BIB) Designs
8.6 Simple Ranking Test: Friedman Analysis: Randomized (Complete) Block Design
8.6.1 Scope and Application
8.6.2 Principle of the Test
8.6.3 Test Subjects
8.6.4 Test Procedure
8.6.5 Analysis and Interpretation of Results
8.7 Multisample Difference Test: Rating Approach-Evaluation by Analysis of Variance (ANOVA)
8.7.1 Scope and Application
8.7.2 Principle of the Test
8.7.3 Test Subjects
8.7.4 Test Procedure
8.7.5 Analysis and Interpretation of Results
8.8 Multisample Difference Test BIB Ranking Test (Balanced Incomplete Block Design)-
Friedman Analysis
8.8.1 Scope and Application
8.8.2 Principle of the Test
8.8.3 Test Subjects
8.8.4 Test Procedure
8.9 Multisample Difference Test BIB Rating Test-Evaluation by Analysis of Variance
8.9.1 Scope and Application
8.9.2 Principle of the Test
8.9.3 Test Subjects
8.9.4 Test Procedure
8.9.5 Analysis and Interpretation of Results
References
9 Determining Threshold
9.1 Introduction
9.2 Definitions
9.3 Applications of Threshold Determinations
References
10 Selection and Training of Panel Members
10.1 Introduction
10.2 Panel Development
10.2.1 Personnel
10.2.1.1 Special Considerations for a Quality Control Quality Assurance (QC/QA) Panel
10.2.2 Facilities
10.2.3 Data Collection and Handling
10.2.4 Projected Costs
10.3 Selection and Training for Difference Tests
10.3.1 Selection
10.3.1.1 Matching Tests
10.3.1.2 Detection/Discrimination Tests
10.3.1.3 Ranking Rating Tests for Intensity
10.3.1.4 Interpretation of Results of Screening Tests
10.3.2 Training
10.4 Selection and Training of Panelists for Descriptive Testing
10.4.1 Recruiting Descriptive Panelists
10.4.2 Selection for Descriptive Testing
10.4.2.1 Prescreening Questionnaires
10.4.2.2 Acuity Tests
10.4.2.3 Ranking/Rating Screening Tests for Descriptive Analysis
10.4.2.4 Personal Interview
10.4.2.5 Mock Panel
10.4.3 Training for Descriptive Testing
10.4.3.1 Terminology Development
10.4.3.2 Introduction to Descriptive Scaling
10.4.3.3 Initial Practice
10.4.3.4 Small Product Differences
10.4.3.5 Final Practice
10.5 Panel Performance and Motivation
10.5.1 Performance
10.5.2 Panelist Maintenance, Feedback, Rewards, and Motivation
Appendix 10.1 Prescreening Questionnaires
Appendix 10.2 Panel Leadership Advice
References
II Descriptive Analysis Techniques
II. Definition
Components of Descriptive Analysis
11.2 Field of Application 11.3
11.3.1 Characteristics: The Qualitative Aspect
11.3.2 Intensity: The Quantitative Aspect
11.3.3 Order of Appearance: The Time Aspect
11.3.4 Overall Impression: The Integrated Aspect
11.4 Commonly Used Descriptive Test Methods with Trained Panels
11.4.1 Flavor Profile Method
11.4.2 Texture Profile Method
11.4.3 Quantitative Descriptive Analysis (QDA) Method
11.4.4 Spectrum™ Descriptive Analysis Method
11.4.5 Time-Intensity Descriptive Analysis
11.4.5.1 Fixed-Time-Point Methods
11.4.5.2 Continuous Measurement Methods
11.5 Commonly Used Descriptive Test Methods with Untrained Panels
11.5.1 Free-Choice Profiling
11.5.2 Flash Profiling
11.5.3 Projective Mapping (Napping)
11.5.4 Sorting
11.6 Application of Descriptive Analysis Panel Data
References
12 Spectrum™ Descriptive Analysis Method
12.1 Designing a Descriptive Method
12.2 Myths about the Spectrum Descriptive Analysis Method
122.1 Myth 1: All Descriptive Methods Are the Same
12.2.2 Myth 2: Concept Development Is Unnecessary in Training a Spectrum Panel
1223 Myth 3: All Spectrum Training and Panel Leaders Are the Same Anyone Can Do It
122.4 Myth 4: Consumer Terms Are Better than Technical Terms
12.2.5 Myth 5: Spectrum Panelists Are Forced to Use Canned Lexicons
12.2.6 Myth 6: Spectrum Panelists Are Coerced into Intensity Calibration
12.2.7 Myth 7: The Universal Scale Cannot Show Small Differences
1228 Myth & Published References and Terms Are the Equivalent of a Training Manual
12.2.9 Myth 9. Product Users Make the Best Panelists and Hedonics Influence Panel Ratings
12.2.10 Myth 10: Panelists Cannot Be Trained for an Array of Products
12.2.11 Myth 11: Training for the Spectrum Method Is Too Time-Intensive
12.2.12 Myth 12: The Spectrum Method Is Consensus Only
12.2.13 Myth 13: Consensus Profiling Prevents Statistical Analysis of Panel Data
122.14 Myth 14: Difficult-to-Find References Prevent Universality of the Spectrum Scale
12.3 Terminology and Lexicon Development
12.4 Intensity
12.5 Combining the Spectrum Descriptive Analysis Method with Other Measures
12.5.1 Using the Spectrum Method Simultaneously with Other Methods
12.5.2 Combining the Spectrum Method with Other Sources of Sensory Data
12.6 Spectrum Descriptive Procedures for Quality Assurance, Shelf-Life Studies, and So On
References
Appendix 12.1 Spectrum Terminology for Descriptive Analysis
Appendix 12.6 Spectrum Descriptive Analysis Training Exercises
13 Affective Tests: Consumer Tests and In-House Panel Acceptance Tests
13.1 Purpose and Applications
13.1.1 Product Maintenance
13.1.2 Product Improvement/ Optimization
13.1.3 Development of New Products
13.1.4 Assessment of Market Potential
13.1.5 Category Review/Benchmarking
13.1.6 Support for Advertising Claims
13.1.7 Uncovering Consumer Needs
13.2 Subjects/Consumers in Affective Tests
13.2.1 Sampling and Demographics
13.2.1.1 User Group
13.2.1.2 Age
13.2.1.3 Gender
13.2.1.4 Income
13.2.1.5 Geographic Location
13.2.2 Source of Test Subjects
13.2.2.1 Employees
13.2.2.2 Local Area Residents
13.2.2.3 General Population
13.3 Choice of Test Location
13.3.1 Laboratory Tests
13.3.2 Central Location Tests
13.3.3 Home Use Tests
13.4 Affective Methods: Qualitative
13.4.1 Applications
13.4.2 Qualitative Screener Development
13.4.3 Types of Qualitative Affective Tests
13.4.3.1 Focus Groups
13.4.3.2 Focus Panels
13.4.3.3 Mini Groups, Diads, Triads
13.4.3.4 One-on-One Interviews
13.5 Affective Methods: Quantitative
13.5.1 Applications
13.5.2 Design of Quantitative Affective Tests
13.5.2.1 Quantitative Screener Development
13.5.2.2 Questionnaire Design
13.5.2.3 Protocol Design
13.5.3 Types of Quantitative Affective Tests
13.5.3.1 Preference Tests
13.5.3.2 Acceptance Tests
13.5.4 Assessment of Individual Attributes (Attribute Diagnostics)
13.5.5 Other Information
13.6 Internet Research
13.6.1 Introduction
13.6.2 Applications
13.6.3 Design of Internet Research
13.6.4 Intermet Research Considerations
13.6.4.1 Benefits and Pitfalls of Using the Internet for Research
13.6.4.2 Platform
13.6.4.3 Recommendations and Checks & Balances
Case Study: Internet Research
13.7 Using Other Sensory Methods to Uncover Insights
13.7.1 Relating Affective and Descriptive Data
Case Study: Relating Consumer Qualitative Information with Descriptive Analysis Data
13.7.2 Using Affective Data to Define Shelf-Life or Quality Limits
13.7.3 Rapid Prototype Development
Appendix 13.1 Screeners for Consumer Studies-Focus Group, CLT, and Home Use Test (HUT)
Appendix 13.2 Discussion Guide Group or One-on-One Interviews
Appendix 13.3 Questionnaires for Consumer Studies
Appendix 13.4 Protocol Design for Consumer Studies
References
14 Basic Statistical Methods
14.1 Introduction
14.2 Summarizing Sensory Data
14.2.1 Summary Analysis of Data in the Form of Ratings
14.2.2 Estimating the Proportion of a Population That Possesses a Particular Characteristic
14.2.3 Confidence Intervals on u and p
14.2.4 Other Interval Estimates
14.2.5 Data Transformations
14.3 Statistical Hypothesis Testing
14.3.1 Statistical Hypotheses
14.3.2 One-Sided and Two-Sided Hypotheses
14.3.3 Type I and Type II Errors
14.3.4 Examples: Tests on Means, Standard Deviations, and Proportions
14.3.5 Calculating Sample Sizes in Discrimination Tests
14.4 Thurstonian Scaling
14.4.1 A Fundamental Measure of Sensory Differences
14.4.2 Decision Rules in Sensory Discrimination Tests
14.4.3 Estimating the Value of &
14.4.3.1 Forced Choice Methods
14.4.3.2 Methods Using Scales
14.4.4 Transitioning from Percent Distinguisher Model to the Thurstonian Model for Planning Discrimination Tests
14.5 Statistical Design of Sensory Panel Studies
14.5.1 Sampling: Replication versus Multiple Observations
14.5.2 Blocking an Experimental Design
14.5.2.1 Completely Randomized Designs
14.5.3 Randomized (Complete) Block Designs
14.5.3.1 Randomized Block Analysis of Ratings
14.5.3.2 Randomized Block Analysis of Rank Data
14.5.4 Balanced Incomplete Block Designs
14.5.4.1 BIB Analysis of Ratings
14.5.4.2 BIB Analysis of Rank Data
14.5.5 Latin Square Designs
14.5.6 Split-Plot Designs
14.5.6.1 Split-Plot Analysis of Ratings
14.5.7 A Simultaneous Multiple Comparison Procedure
Appendix 14.1 Probability
References
15 Advanced Statistical Methods
15.1 Introduction
15.2 Data Relationships
15.2.1 All Independent Variables
15.2.1.1 Correlation Analysis
15.2.1.2 Principal Components Analysis
15.2.1.3 Multidimensional Scaling
15.2.1.4 Cluster Analysis
15.2.2 Dependent and Independent Variables
15.2.2.1 Regression Analysis
15.2.2.2 Principal Component Regression
15.2.2.3 Partial Least Squares Regression
15.2.2.4 Discriminant Analysis
15.3 Preference Mapping
15.3.1 Internal Preference Mapping
15.3.2 External Preference Mapping
15.3.2.1 Constructing the Perceptual Map of the Product Space
15.3.2.2 Identifying Preference Segments
15.3.2.3 From Perceptual Map to Preference Map
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