Statistical experimental design is currently used as a quality control technique to achieve product excellence at the lowest overall cost. It can also function as a powerful tool to optimize food products and/or processes, to accelerate food development cycles, reduce research costs, facilitate the transition of products from research and development to manufacturing and troubleshoot manufacturing problems. Food Product Design: A Computer-Aided Statistical Approach familiarizes readers with the methodology of statistical experimental design, and its application in food product design, with the aid of commonly available modern commercial software.
Food Product Design presents basic concepts of food product design, then focuses on the most effective statistical techniques and corresponding computer applications for trial design, modeling, and experimental data analysis. The book presents very few theories about mathematics and statistics. Instead, it contains detailed descriptions of how to use popular computer software to solve the real mathematical and statistical problems that occur in product design. Even those with very limited knowledge of statistics and mathematics will find this a useful and highly practical book. Food Product Design: A Computer-Aided Statistical Approach will be a valuable tool for professional food engineers, technologists, scientists, and industrial personnel who want to update and expand their knowledge about computer-aided statistical methods in the field of food product design. Those involved in applied research at universities in food and agriculture, biological and chemical engineering, and statistics will also find it useful and informative.
Introduction
Problems of Food Product Design
Classical One-Factor Experimental Method
General Remarks about Statistical Methods
Software: A Step toward Simplicity
A Brief Historical Perspective
Problems of Food Product Design
System Identification and Definition
Black-Box Modeling and Input-Output Consideration
Production Process Problem
Recipe Problem
Difference of Modeling for Process and Recipe
Food Process Modeling and Optimization
Basic Concepts of Food Process Design
Identification of Modeling System
Selection of Suitable Models
Design of Statistical Experimental Plans
Realization of experimental Designs
Model Building
Effect Analysis of Process Variables
Prediction and Optimization
Exploration and Confirmation
Transfer of Optimum Results and Evolutionary Operation
A Complete Practical Example
Food Recipe Modeling And Optimization
Introduction
Target Definition and Food Ingredient Screening
Design of Mixture Experimental Plan
Realization of Mixture Experimental Designs
Model Building
Validity of Established Models
Analysis of Components Effect
Recipe Optimization and Prediction
Modeling and Optimization for Both Food Recipe and Process
Introduction
Principle of Combined Designs
Model Building
Analysis of Variable Effects
Food Quality Optimization and Prediction
Practical Example
Expert System for Food Product Development
Introduction
Structure of Expert Systems
Theory of Fuzzy Logic
Principle of Neural Network
Building of an Expert System
Bibliography
Appendix
Index
Biography
Hu, Ruguo
