Statistical Methods in Food and Consumer Research continues to be the only book to focus solely on the statistical techniques used in sensory testing of foods, pharmaceuticals, cosmetics, and other consumer products. This new edition includes the most receent applications of statistical methods, and features significant updates as well as two new chapters. Covering the application of techniques including R-index, the Bayesian approach for sensory differences tests, and preference mapping in addition to several other methodologies, this is the comprehensive reference needed by those studying sensory evaluation and applied statistics in agriculture and biological sciences. Research professionals working with food, beverages, healthcare, cosmetics, and other related areas will find the book a valuable guide to the variety of statistical methods available.

Key Features

Key Features: * Provides comprehensive coverage of statistical techniques in sensory testing * Includes data compiled from real-world experiments * Covers the latest in data interpretation and analysis * Addresses key methods such as R-index, Thursonian Discriminal Distances, group sequential tests, beta-binomial tests, sensory difference and similarity tests, just-about-right data, signal-to-noise ratio, analysis of cosmetic data, Descriptive Analysis, claims substantiation and preference mapping


Students in sensory evaluation courses in both biological and agricultural departments can use this book as a text for their applied statistics requirements. Expanding industrial application of statistics to sensory science, foods, beverages and other related areas make this update ideal for professional reference use as well.

Table of Contents

1 INTRODUCTION 1.1 A Brief Review of Tools for Statistical Interference 1.2 Principles of Experimental Design 1.3 The Role of the Statistician in Research Exercises 2 STATISTICAL SENSORY TESTING 2.1 Psychophysical Aspects of Sensory Data 2.2 Scales of Measurement 2.3 Scale Structures 2.4 Construction of a Scale 2.5 Distribution of Sensory Data 2.6 Selection of Panel Members Exercises 3 THE ANALYSIS OF VARIANCE AND MULTIPLE COMPARISON TESTS 3.1 Analysis of Variance 3.2 Multiple-Comparison Tests 3.3 Sample Size Estimation Exercises 4 EXPERIMENTAL DESIGN 4.1 Simple Comparative Experiments 4.2 Completly Randomized Designs 4.3 Randomized Complete Block Designs 4.4 Latin Square Designs 4.5 Cross-Over Designs 4.6 Split Plot Designs Exercises 5 INCOMPLETE BLOCK EXPERIMENTAL DESIGNS 5.1 Balanced Incomplete Block Designs 5.2 Balanced Incomplete Block Designs Augmented with a Control 5.3 Doubly Balanced Incomplete Block Designs 5.4 Composite Complete-Incomplete Block Designs Exercises 6 FACTORAL EXPERIMENTS 6.1 The 2n Factorial Experiments 6.2 The 3n Factorial Experiments 6.3 The p x q and p x q x k Factorial Experiments 6.4 Simple Confounding and Fractional Factoral Experiments Exercises 7 RESPONSE SURFACE DESIGNS AND ANALYSIS 7.1 General Concepts 7.2 Fitting of Response Surfaces and Some Design Considerations 7.3 Illustrations of Fittings of First- and Second-


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© 2009
Academic Press
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About the authors

Maximo Gacula, Jr.

Affiliations and Expertise

Gacula Associates Consulting, Scottsdale, AZ, USA

Jagbir Singh

Affiliations and Expertise

Temple University, Philadelphia, PA, USA

Jian Bi

Affiliations and Expertise

Sensometrics Research and Service, Richmond, VA, USA

Stan Altan

Affiliations and Expertise

J&J Pharmaceutical R&D, Rantan, NJ, USA