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• Cover
• Title Page
• Copyright Page
• Dedication
• Preface
• Acknowledgments
• The Authors
• Contents
• Chapter 8: Descriptive Analysis Techniques
• I. Definition
• II. Field of Application
• III. Components of Descriptive Analysis
• A. Characteristics — The Qualitative Aspect
• B. Intensity — The Quantitative Aspect
• C. Order of Appearance — The Time Aspect
• D. Overall Impression — The Integrated Aspect
• IV. Commonly Used Descriptive Test Methods
• A. The Flavor Profile Method
• B. The Texture Profile Method
• C. The Quantitative Descriptive Analysis (QDA) Method
• D. Time-Intensity Descriptive Analysis
• V. Designing a Descriptive Procedure. The Spectrum™ Method
• A. Terminology
• B. Intensity
• C. Other Options
• VI. Modified Short-Version Descriptive Spectrum™ Procedures for Quality Assurance, Shelf-Life Studies, etc.
• Appendix 1 — Spectrum™ Reference Lists of Terminology for Descriptive Analysis
• A. Terms Used to Describe Appearance
• B. General Flavor Terms
• C. Terms Used to Describe Oral Texture (With Procedures and Definitions)
• D. Example of Texture Terminology: Oral Texture of Cookies
• Appendix 2 — Reference Samples Useful for the Establishment of Spectrum™ Intensity Scales for Descriptive Analysis
• A. Intensity Scale Values (0 to 15) for Some Common Aromatics
• B. Intensity Scale Values (1 to 15) for the Four Basic Tastes in Various Products
• C. Intensity Scale Values (0 to 15) for Some Common Texture Attributes
• 1. Standard Roughness: Scale
• 2. Standard Wetness Scale
• 3. Standard Stickiness to Lips Scale
• 4. Standard Springiness Scale
• 5. Standard Hardness Scale
• 6. Standard Cohesiveness Scale
• 7. Standard Fracturability Scale
• 8. Standard Viscosity Scale
• 9. Standard Denseness Scale
• 10. Standard Moisture Absorption Scale
• 11. Standard Cohesiveness of Mass Scale
• 11. Standard Tooth Packing Scale
• References
• Chapter 9: Affective Tests: Consumer Tests and In-House Panel Acceptance Tests
• I. Purpose and Applications
• A. Product Maintenance
• B. Product Improvement/Optimization
• C. Development of New Products
• D. Assessment of Market Potential
• II. The Subjects/Consumers In Affective Tests
• A. Sampling and Demographics
• B. Source of Test Subjects: Employees, Local Residents, the General Population
• III. Choice Of Test Location
• A. Laboratory Tests
• B. Central Location Tests
• C. Home-Use Tests
• IV. Methods Used In Affective Tests/Consumer Tests
• A. Primary Response: Preference or Acceptance?
• 1. Preference Tests
• a. Example 1. Paired Preference. Improved Peanut Butter
• 2. Acceptance Tests
• a. Example 2: Acceptance of Two Prototypes Relative to a Competitive Product. High Fiber Breakfast Cereal
• B. Assessment of Individual Attributes
• V. Design of Questionnaires
• VI. Using Other Sensory Methods to Supplement Affective Testing
• A. Relating Affective and Descriptive Data
• B. Using Affective Data to Define Shelf-Life or Quality Limits
• 1. Example 5: Shelf-Life of Sesame Cracker
• References
• Chapter 10: Selection And Training Of Panel Members
• I. Introduction
• II. Panel Development
• III. Selection and Training For Difference Tests
• A. Selection
• 1. Matching Tests
• 2. Detection/Discrimination Tests
• 3. Ranking/Rating Tests for Intensity
• 4. Interpretation of Results of Screening Tests
• B. Training
• IV. Selection and Training of Panelists for Descriptive Testing
• A. Selection for Descriptive Testing
• 1. Prescreening Questionnaires
• 2. Acuity Tests
• 3. Ranking/Rating Screening Tests for Descriptive Analysis
• 4. Personal Interview
• B. Training for Descriptive Testing
• 1. Terminology Development and Introduction to Scaling
• 2. Initial Practice
• 3. Small Product Differences
• 4. Final Practice
• V. Panel Performance and Motivation
• A. Performance
• B. Feedback and Motivation
• C. Rewards and Motivation
• References
• Chapter 11: Basic Probability and Statistical Methods
• I. Introduction
• II. Probability
• A. The Normal Distribution
• 1. Example 1.’ Normal Probabilities on an Interval
• 2. Example 2: Normal Tail Probabilities
• B. The Binomial Distribution
• 1. Example 3.’ Calculating Exact Binomial Probabilities
• 2. Example 4: The Normal Approximation to the Binomial
• III. Estimation Techniques
• A. Estimating the Parameters of a Normal Distribution
• 1. Example 5.’ Estimating the Average Perceived Sweetness Intensity in a Cola and Its Standard Deviation
• B. Estimating the Population Proportion p of a Binomial Distribution
• 1. Example 6: A Preference Test
• C. Confidence Intervals on μ and p
• 1. Example 7 ‘ Confidence Intervals on the Mean μ
• 2. Example 8: Confidence Interval on the Proportion p
• IV. Statistical Inference
• A. Statistical Hypotheses
• B. One-Sided and Two-Sided Hypotheses
• C. Type I and Type II Errors
• D. Examples: Tests on Means, Standard Deviations, and Proportions
• 1. Example 9: Testing that the Mean of a Normal Distribution is Equal to a Specified Value
• 2. Example 10: Comparing the Means of Two Normal Populations — Paired-Sample Case
• 3. Example 11: Comparing the Means of Two Normal Populations — Independent (or Two-Sample) Case
• 4. Example 12: Comparing Standard Deviations from Two Normal Populations
• 5. Example 13 : Testing that the Population Proportion is Equal to a Specified Value
• 6. Example 14: Comparing Two Population Proportions
• V. Concluding Remarks
• References
• Chapter 12: Advanced Statistical Techniques
• I. Introduction
• II. Replication vs. Multiple Observations
• III. The Blocking Structure of an Experimental Design
• A. Randomized (Complete) Block Designs
• 1. Randomized Block Analysis of Ratings
• 2. Randomized Block Analysis of Rank Data
• B. Balanced Incomplete-Block Designs
• 1. BIB Analysis of Ratings
• 2. BIB Analysis of Rank Data
• C. Split-Plot Designs
• 1. Split-Plot Analysis of Ratings
• D. Multiple Comparison Procedures
• 1. One-at-a-Time Multiple Comparison Procedures
• 2. Simultaneous Multiple Comparison Procedures
• IV. The Treatment Structure of an Experimental Design
• A. Factorial Treatment Structures
• B. Response Surface Methodology
• V. Multivariate Statistical Methods
• References
• Chapter 13: Guidelines For Choice Of Technique
• I. Introduction
• A. Define the Project Objective
• B. Define the Test Objective
• C. Reissue Project Objective and Test Objectives. Revise Test Design
• Table 1: Types of Problems in Sensory Analysis
• Table 2: Difference Tests
• Table 3: Attribute Difference Tests
• Table 4: Affective Tests
• Table 5: Descriptive Tests
• Reference
• Chapter 14: Guidelines For Reporting Results
• I. Introduction
• II. Summary
• III. Objective
• IV. Experimental
• V. Results and Discussion
• References
• Statistical Tables
• Table TI: Random Orders of the Digits I to 9. Arranged in Groups of Three Columns
• Table T2: Binomial Probabilities
• Table T3: The Standard Normal Distribution
• Table T4: Upper α Probability Points of Student’s t Distribution
• Table T5: Upper α Probability Points of x2 Distribution
• Table T6: Upper α Probability Points of F Distribution
• Table T7: Triangle Test for Difference — Critical Number (Minimum) of Correct Answers
• Table T8: Duo-Trio Test for Difference or One-Sided Paired Comparison Test for Difference — Critical Number (Minimum) of Correct Answers
• Table T9: Two-Sided Paired Comparison Test for Difference — Critical Number (Minimun) of Correct Answers
• Table T10: Two-Out-of-Five Test for Difference — Critical Number (Minimum) of Correct Answers
• Table T11: Triangle Test for Similarity — Critical Number (Maximum) of Correct Answers
• Table T12: Duo-Trio Test for Similarity or Two-Sided Paired-Comparison Test for Similarity — Critical Number (Maximum) of Correct Answers
• Table T13: Two-Out-of-Five Test for Similarity — Critical Number of Correct Responses
• Table Tl4: Percentage Points of the Studentized Range — Upper α Critical Values for Tukey’s HSD Multiple Comparison Procedure
• Index