Daniel Granato and Verônica Maria de Araújo CaladoDaniel CozzolinoHu-Zhe Zheng and Shin-Kyo ChungAzila Abdul-Aziz and Harisun Yaakob and Ramlan Aziz and Roshanida Abdul Rahman and Sulaiman Ngadiran and Mohd Faizal Muhammad and Noor Hafiza Harun and Wan Mastura Wan Zamri and Ernie Surianiy RoslyAurea Grané and Agnieszka JachJérôme Pagès and François HussonGastón AresRolf ErgonÅsmund Rinnan and Jose Manuel Amigo and Thomas SkovEva Derndorfer and Andreas BaierlPaula VarelaMarco S. ReisDébora Cristiane Bassani and Domingos Sávio Nunes and Daniel GranatoAnthony D. HitchinsBasil JarvisZelimir Kurtanjek and Jasenka Gajdos KljusuricTamas Ferenci and Levente KovacsFernando Pérez-RodríguezUrsula Andrea Gonzales-Barron and Vasco Augusto Pilão Cadavez and Francis ButlerClara C. Sousa and João A. LopesJeffrey E. JarrettMassimo Pacella and Quirico SemeraroGrishja van der Veer and Saskia M. van Ruth and Jos A. HagemanMicha Peleg and Mark D. Normand and Maria G. CorradiniPanagiotis H. Tsarouhas

About the editors	p. xi
List of contributors	p. xiii
Acknowledgements	p. xvii
Section 1 p. 1
1 The use and importance of design of experiments (DOE) in process modelling in food science and technology	p. 3
2 The use of correlation, association and regression to analyse processes and products	p. 19
3 Case study: Optimization of enzyme-aided extraction of polyphenols from unripe apples by response surface methodology	p. 31
4 Case study: Statistical analysis of eurycomanone yield using a full factorial design	p. 43
Section 2 p. 55
5 Applications of principal component analysis (PCA) in food science and technology	p. 57
6 Multiple factor analysis: Presentation of the method using sensory data	p. 87
7 Cluster analysis: Application in food science and technology	p. 103
8 Principal component regression (PCR) and partial least squares regression (PLSR)	p. 121
9 Multivvay methods in food science	p. 143
10 Multidimensional scaling (MDS)	p. 175
11 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	p. 187
12 Multivariate image analysis	p. 201
13 Case Study: Quality control of Camellia sinensis and Ilex paragnariensis teas marketed in Brazil based on total phenolics, flavonoids and free-radical scavenging activity using chemometrics	p. 219
Section 3 p. 231
14 Statistical approaches to develop and validate microbiological analytical methods	p. 233
15 Statistical approaches to the analysis of microbiological data	p. 249
16 Statistical modelling of anthropometric characteristics evaluated on nutritional status	p. 285
17 Effects of paediatric obesity: a multivariate analysis of laboratory parameters	p. 303
18 Development and application of predictive microbiology models in foods	p. 321
19 Statistical approaches for the design of sampling plans for microbiological monitoring of foods	p. 363
20 Infrared spectroscopy detection coupled to chemometrics to characterize foodborne pathogens at a subspecies level	p. 385
Section 4 p. 419
21 Multivariate statistical quality control	p. 421
22 Application of neural-based algorithms as statistical tools for quality control of manufacturing processes	p. 431
23 An integral approach to validation of analytical fingerprinting methods in combination with chemometric modelling for food quality assurance	p. 449
24 Translating randomly fluctuating QC records into the probabilities of future mishaps	p. 471
25 Application of statistical approaches for analysing the reliability and maintainability of food production lines: a case study of mozzarella cheese	p. 491
Index	p. 511