Table of Contents
Preface ix
Acknowledgements xi
1 Introduction 1
1.1 The Distinction between Trained Sensory Panels and Consumer Panels 1
1.2 The Need fox Statistics in Experimental Planning and Analysis 2
1.3 Scales and Data Types 3
1.4 Organisation of the Book 3
2 Important Data Collection Techniques for Sensory and Consumer Studies 5
2.1 Sensory Panel Methodologies 5
2.2 Consumer Tests 7
Part 1 Problem Driven
3 Quality Control of Sensory Profile Data 11
3.1 General Introduction 11
3.2 Visual Inspection of Raw Data 15
3.3 Mixed Model ANOVA for Assessing the Importance of the Sensory Attributes 18
3.4 Overall Assessment of Assessor Differences Using All Variables Simultaneously 19
3.5 Methods for Detecting Differences in Use of the Scale 24
3.6 Comparing the Assessors' Ability to Detect Differences between the Products 27
3.7 Relations between Individual Assessor Ratings and the Panel Average 29
3.8 Individual Line Plots for Detailed Inspection of Assessors 33
3.9 Miscellaneous Methods 34
4 Correction Methods and Other Remedies for Improving Sensory Profile Data 39
4.1 Introduction 39
4.2 Correcting for Different Use of the Scale 40
4.3 Computing Improved Panel Averages 43
4.4 Pre-processing of Data for Three-Way Analysis 45
5 Detecting and Studying Sensory Differences and Similarities between Products 47
5.1 Introduction 47
5.2 Analysing Sensory Profile Data: Univariate Case 48
5.3 Analysing Sensory Profile Data; Multivariate Case 59
6 Relating Sensory Data to Other Measurements 67
6.1 Introduction 67
6.2 Estimating Relations between Consensus Profiles and External Data 68
6.3 Estimating Relations between Individual Sensory Profiles and External Data 74
7 Discrimination and Similarity Testing 79
7.1 Introduction 79
7.2 Analysis of Data from Basic Sensory Discrimination Tests 80
7.3 Examples of Basic Discrimination Testing 81
7.4 Power Calculations in Discrimination Tests 85
7.5 Thurstonian Modelling: What Is It Really? 86
7.6 Similarity versus Difference Testing 87
7.7 Replications: What to Do? 89
7.8 Designed Experiments, Extended Analysis and Other Test Protocols 93
8 Investigating Important Factors Influencing Food Acceptance and Choice 95
8.1 Introduction 95
8.2 Preliminary Analysis of Consumer Data Sets (Raw Data Overview) 99
8.3 Experimental Designs for Rating Based Consumer Studies 102
8.4 Analysis of Categorical Effect Variables 106
8.5 Incorporating Additional Information about Consumers 113
8.6 Modelling of Factors as Continuous Variables 117
8.7 Reliability/Validity Testing for Rating Based Methods 118
8.8 Rank Based Methodology 119
8.9 Choice Based Conjoint Analysis 120
8.10 Market Share Simulation 123
9 Preference Mapping for Understanding Relations between Sensory Product Attributes and Consumer Acceptance 127
9.1 Introduction 128
9.2 External and Internal Preference Mapping 129
9.3 Examples of Linear Preference Mapping 136
9.4 Ideal Point Preference Mapping 141
9.5 Selecting Samples for Preference Mapping 146
9.6 Incorporating Additional Consumer Attributes 147
9.7 Combining Preference Mapping with Additional Information-about the Samples 149
10 Segmentation of Consumer Data 155
10.1 Introduction 155
10.2 Segmentation of Rating Data 156
10.3 Relating Segments to Consumer Attributes 163
Part II Method Oriented
11 Basic Statistics 165
11.1 Basic Concepts and Principles 165
11.2 Histogram, Frequency and Probability 166
11.3 Some Basic Properties of a Distribution (Mean, Variance and Standard Deviation) 168
11.4 Hypothesis Testing and Confidence Intervals for the Mean μ 169
11.5 Statistical Process Control 172
11.6 Relationships between Two or More Variables 173
11.7 Simple Linear Regression 175
11.8 Binomial Distribution and Tests 177
11.9 Contingency Tables and Homogeneity Testing 178
12 Design of Experiments for Sensory and Consumer Data 181
12.1 Introduction 181
12.2 Important Concepts and Distinctions 182
12.3 Full Factorial Designs 185
12.4 Fractional Factorial Designs: Screening Designs 187
12.5 Randomised Blocks and Incomplete Block Designs 188
12.6 Split-Plot and Nested Designs 190
12.7 Power of Experiments 191
13 ANOVA for Sensory and Consumer Data 193
13.1 Introduction 193
13.2 One-Way ANOVA 194
13.3 Single Replicate Two-Way ANOVA 196
13.4 Two-Way ANOVA with Randomised Replications 198
13.5 Multi-Way ANOVA 200
13.6 ANOVA for Fractional Factorial Designs 201
13.7 Fixed and Random Effects in ANOVA: Mixed Models 203
13.8 Nested and Split-Plot Models 205
13.9 Post Hoc Testing 206
14 Principal Component Analysis 209
14.1 Interpretation of Complex Data Sets by PCA 209
14.2 Data Structures for the PCA 210
14.3 PCA: Description of the Method 211
14.4 Projections and Linear Combinations 213
14.5 The Scores and Loadings Plots 214
14.6 Correlation Loadings Plot 217
14.7 Standardisation 219
14.8 Calculations and Missing Values 220
14.9 Validation 220
14 10 Outlier Diagnostics 221
14.11 Tucker-1 223
14.12 The Relation between PCA and Factor Analysis (FA) 224
15 Multiple Regression, Principal Components Regression and Partial Least Squares Regression 227
15.1 Introduction 227
15.2 Multivariate Linear Regression 229
15.3 The Relation between ANOVA and Regression Analysis 232
15.4 Linear Regression Used for Estimating Polynomial Models 233
15.5 Combining Continuous and Categorical Variables 234
15.6 Variable Selection for Multiple Linear Regression 235
15.7 Principal Components Regression (PCR) 236
15.8 Partial Least Squares (PLS) Regression 237
15.9 Model Validation: Prediction Performance 238
15.10 Model Diagnostics and Outlier Detection 241
15.11 Discriminant Analysis 244
15.12 Generalised Linear Models- Logistic Regression and Multinomial Regression 245
16 Cluster Analysis: Unsupervised Classification 249
16.1 Introduction 249
16.2 Hierarchical Clustering 251
16 3 Partitioning Methods 254
16.4 Cluster Analysis for Matrices 259
17 Miscellaneous Methodologies 263
17.1 Three-Way Analysis of Sensory Data 263
17.2 Relating Three-Way Data to Two-Way Data 269
17.3 Path Modelling 269
17.4 MDS-Multidimensional Scaling 271
17.5 Analysing Rank Data 271
17.6 The L-PLS Method 273
17.7 Missing Value Estimation 273
Nomenclature, Symbols and Abbreviations 277
Index 283
