Sensory evaluation techniques

"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...

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Bibliographic Details
Main Authors Meilgaard, Morten C. (Author), Civille, Gail Vance (Author), Carr, B. Thomas (Author)
Format Electronic eBook
LanguageEnglish
Published Boca Raton : CRC Press, Taylor & Francis Group, CRC Press is an imprint of the Taylor & Francis Group, an Informa business, [2016]
EditionFifth edition.
Subjects
Sensory evaluation.
Senses and sensation.
Food preferences.
elektronické knihy
electronic books
Online AccessFull text
ISBN9781482216912
1482216914
9781523107506
1523107502
9781482216905
1482216906
Physical Description1 online resource (xxix, 600 pages)

Cover

Table of Contents:
  • Machine generated contents note: 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
  • 2.1. Introduction
  • 2.2. Sensory Attributes
  • 2.2.1. Appearance
  • 2.2.2. 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
  • 2.3.3.1. General
  • 2.3.3.2. Retronasal Odor
  • 2.3.3.3. 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
  • 3.1. 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
  • Note continued: 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
  • 4.1. 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
  • Note continued: 4.3.8. Lack of Motivation
  • 4.3.9. Capriciousness versus Timidity
  • 4.4. Poor Physical Condition
  • References
  • 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
  • 6.1. 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
  • 7.1. 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
  • Note continued: 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
  • Note continued: 7.9.2. Principle of the Test
  • 7.9.3. Analysis and Interpretation of Results: Parameters of the Test
  • References
  • 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
  • Note continued: 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
  • Note continued: 9.1. Introduction
  • 9.2. Definitions
  • 9.3. Applications of Threshold Determinations
  • References
  • 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
  • Note continued: 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
  • 11.1. Definition
  • 11.2. Field of Application
  • 11.3.Components of Descriptive Analysis
  • 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
  • Note continued: 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
  • 12.1. Designing a Descriptive Method
  • 12.2. Myths about the Spectrum Descriptive Analysis Method
  • 12.2.1. Myth 1: All Descriptive Methods Are the Same
  • 12.2.2. Myth 2: Concept Development Is Unnecessary in Training a Spectrum Panel
  • 12.2.3. Myth 3: All Spectrum Training and Panel Leaders Are the Same; Anyone Can Do It
  • 12.2.4. Myth 4: Consumer Terms Are Better than Technical Terms
  • 12.2.5. Myth 5: Spectrum Panelists Are Forced to Use Canned Lexicons
  • Note continued: 12.2.6. Myth 6: Spectrum Panelists Are Coerced into Intensity Calibration
  • 12.2.7. Myth 7: The Universal Scale Cannot Show Small Differences
  • 12.2.8. Myth 8: 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
  • 12.2.14. 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
  • Note continued: 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 12.2 Spectrum Intensity Scales for Descriptive Analysis
  • Appendix 12.3 Streamlined Approach to Spectrum References
  • Appendix 12.4 Spectrum Descriptive Analysis: Product Lexicons
  • Appendix 12.5 Spectrum Descriptive Analysis: Examples of Full Product Descriptions
  • Appendix 12.6 Spectrum Descriptive Analysis Training Exercises
  • 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
  • Note continued: 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
  • Note continued: 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 33I
  • 13.6.3. Design of Internet Research
  • 13.6.4. Internet 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
  • Note continued: 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
  • 15.1. Introduction
  • 15.2. Data Relationships
  • 15.2.1. All Independent Variables
  • 15.2.1.1. Correlation Analysis
  • 15.2.1.2. Principal Components Analysis
  • Note continued: 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
  • 15.3.2.4. Reverse Engineering the Profile of the Target Product
  • 15.3.2.5. External Preference Mapping of Individual Respondents
  • 15.3.3. Partial Least-Squares Mapping
  • 15.4. Treatment Structure of an Experimental Design
  • 15.4.1. Factorial Treatment Structures
  • 15.4.2. Fractional Factorials and Screening Studies
  • 15.4.2.1. Constructing Fractional Factorials
  • 15.4.2.2. Plackett-Burman Experiments
  • Note continued: 15.4.2.3.Computer-Aided Optimal Fractional Designs
  • 15.4.2.4. Analysis of Screening Studies
  • 15.4.3. Conjoint Analysis
  • 15.4.4. Response Surface Methodology
  • References
  • 16.1. Introduction
  • 16.1.1. Rationale
  • 16.1.2. Qualities of a Good Report
  • 16.2. Anatomy of the Report
  • 16.2.1. Part 1: Summary or Abstract
  • 16.2.2. Part 2: Objectives and Introduction
  • 16.2.3. Part 3: Materials and Methods
  • 16.2.4. Part 4: Results and Discussion
  • 16.3. Graphical Presentation of Data
  • 16.3.1. Introduction
  • 16.3.2. General Guidelines for Graphing Data
  • 16.3.3. Appropriateness of Graphs
  • 16.3.4.Common Graphs and Examples
  • 16.4. Example Reports
  • References
  • 17.1. Introduction
  • 17.2. Attribute Descriptive Methods
  • 17.2.1. Establishing Sensory Specifications
  • 17.2.1.1. Initial Sample Screening
  • 17.2.1.2. Sensory Descriptive Evaluations and Sample Selection for Consumer Testing
  • 17.2.1.3. Consumer Testing Production Samples
  • Note continued: 17.2.1.4. Establishing the Sensory Specifications
  • 17.2.2. Implementing the In-Plant QC/Sensory Function
  • 17.2.3. Product Sampling, Data Analysis, and Reporting
  • 17.3. Difference-from-Control Methods
  • 17.3.1. Establishing Sensory Specifications
  • 17.3.2. Implementing the In-Plant QC/Sensory Function
  • 17.3.3. Product Sampling, Data Analysis, and Reporting
  • 17.4. In-Out Method
  • 17.4.1. Establishing Sensory Specifications
  • 17.4.2. Implementing the In-Plant QC/Sensory Function
  • 17.4.3. Product Sampling, Data Analysis, and Reporting
  • References
  • 18.1. Introduction
  • 18.2. Front End of Innovation
  • 18.2.1. Definition, Purpose, Outcome
  • 18.2.2. Applications
  • 18.2.3. Tools and Techniques
  • 18.2.4. Design of Front-End Innovation Research
  • 18.2.5. Data Analysis and Mining
  • 18.2.5.1. Case Study: Understanding Consumer Perception of Crispy and Crunchy
  • 18.3. Sequence Mapping
  • 18.4. Capturing the Iconic Experience
  • Note continued: 18.4.1. Definition and Purpose or Scope
  • 18.4.2. Applications
  • 18.4.2. Design of Research
  • 18.4.3. Tools and Techniques
  • 18.4.4. Data Analysis and Mining/Conclusions
  • 18.5. Consumer Cocreation
  • 18.6. Qualitative Use of Kano Methodology
  • 18.7. Benefit Perception beyond Liking: Functional, Emotional, and Health and Wellness Benefits
  • 18.7.1. Definition and Purpose or Scope
  • 18.7.2. Tools and Techniques
  • 18.7.3. Applications
  • 18.7.4. Design of Research
  • 18.7.5. Conclusions
  • 18.8. Behavioral Economics
  • 18.9. Category Appraisals, Key Drivers Studies and Sensory Segmentation
  • 18.9.1. Definition and Purpose or Scope
  • 18.9.2. Design and Benefits of the Research
  • 18.9.2.1. Phase I: Defining the Limits of the Category
  • 18.9.2.2. Phase II: Documentation of Product Characteristics, Competitive Intelligence and Selection of Products for Consumer Testing
  • Note continued: 18.9.2.3. Phase III: Determining Consumer Acceptance and Perception of the Products in the Category
  • 18.9.2.4. Phase IV: Identifying Key Drivers, Drivers of Benefit Perception, and Strategic Product Guidance
  • 18.9.3. Conclusion
  • 18.10. Ad Claims
  • 18.10.1. Introduction
  • 18.10.2. Types of Claims
  • 18.10.3. Types of Claims Testing
  • 18.10.4. Building the Case
  • 18.10.5. Cautions and Things to Consider
  • Additional Resources
  • References
  • Scenario 1
  • Scenario 2
  • Scenario 3
  • Scenario 4
  • Scenario 5
  • References
  • Additional Qualitative References.

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