Mathematical and Statistical Methods in Food Science and Technology

Mathematical and Statistical Approaches in Food Science and Technology offers an accessible guide to applying statistical and mathematical technologies in the food science field whilst also addressing the theoretical foundations. Using clear examples and case-studies by way of practical illustration, the book is more than just a theoretical guide for non-statisticians, and may therefore be used by scientists, students and food industry professionals at different levels and with varying degrees of statistical skill.

About the editors xiList of contributors xiiiAcknowledgements xviiSection 1 11 The use and importance of design of experiments (DOE) in process modelling in food science and technology 3Daniel Granato and Verônica Maria de Araújo Calado2 The use of correlation, association and regression to analyze processes and products 19Daniel Cozzolino3 Case study: Optimization of enzyme-aided extraction of polyphenols from unripe apples by response surface methodology 31Hu-Zhe Zheng and Shin-Kyo Chung4 Case study: Statistical analysis of eurycomanone yield using a full factorial design 43Azila Abdul-Aziz, Harisun Yaakob, Ramlan Aziz, Roshanida Abdul Rahman, Sulaiman Ngadiran, Mohd Faizal Muhammad, Noor Hafiza Harun, Wan Mastura Wan Zamri and Ernie Surianiy RoslySection 2 555 Applications of principal component analysis (PCA) in food science and technology 57Aurea Grane and Agnieszka Jach6 Multiple factor analysis: Presentation of the method using sensory data 87Jerôme Pagès and François Husson7 Cluster analysis: Application in food science and technology 103Gastón Ares8 Principal component regression (PCR) and partial least squares regression (PLSR) 121Rolf Ergon9 Multiway methods in food science 143Åsmund Rinnan, José Manuel Amigo and Thomas Skov10 Multidimensional scaling (MDS) 175Eva Derndorfer and Andreas Baierl11 Application of multivariate statistical methods during new product development - Case study: Application of principal component analysis and hierarchical cluster analysis on consumer liking data of orange juices 187Paula Varela12 Multivariate image analysis 201Marco S. Reis13 Case Study: Quality control of Camellia sinensis and Ilex paraguariensis teas marketed in Brazil based on total phenolics, flavonoids and free-radical scavenging activity using chemometrics 219Débora Cristiane Bassani, Domingos Sávio Nunes and Daniel GranatoSection 3 23114 Statistical approaches to develop and validate microbiological analytical methods 233Anthony D. Hitchins15 Statistical approaches to the analysis of microbiological data 249Basil Jarvis16 Statistical modelling of anthropometric characteristics evaluated on nutritional status 285Zelimir Kurtanjek and Jasenka Gajdos Kljusuric17 Effects of paediatric obesity: a multivariate analysis of laboratory parameters 303Tamas Ferenci and Levente Kovacs18 Development and application of predictive microbiology models in foods 321Fernando Pérez-Rodríguez19 Statistical approaches for the design of sampling plans for microbiological monitoring of foods 363Ursula Andrea Gonzales-Barron, Vasco Augusto Piláo Cadavez and Francis Butler20 Infrared spectroscopy detection coupled to chemometrics to characterize foodborne pathogens at a subspecies level 385Clara C. Sousa and João A. LopesSection 4 41921 Multivariate statistical quality control 421Jeffrey E. Jarrett22 Application of neural-based algorithms as statistical tools for quality control of manufacturing processes 431Massimo Pacella and Quirico Semeraro23 An integral approach to validation of analytical fingerprinting methods in combination with chemometric modelling for food quality assurance 449Grishja van der Veer, Saskia M. van Ruth and Jos A. Hageman24 Translating randomly fluctuating QC records into the probabilities of future mishaps 471Micha Peleg, Mark D. Normand and Maria G. Corradini25 Application of statistical approaches for analysing the reliability and maintainability of food production lines: a case study of mozzarella cheese 491Panagiotis H. TsarouhasIndex 511