Mathematical And Statistical Methods In Food Science

About the editors xi

List of contributors xiii

Acknowledgements xvii

Section 1 1

1 The use and importance of design of experiments (DOE) inprocess modelling in food science and technology 3 Daniel Granato and Veronica Maria de AraujoCalado

2 The use of correlation, association and regression to analyzeprocesses and products 19 Daniel Cozzolino

3 Case study: Optimization of enzyme-aided extraction ofpolyphenols from unripe apples by response surface methodology31 Hu-Zhe Zheng and Shin-Kyo Chung

4 Case study: Statistical analysis of eurycomanone yield using afull factorial design 43 Azila Abdul-Aziz, Harisun Yaakob, Ramlan Aziz, Roshanida AbdulRahman, Sulaiman Ngadiran, Mohd Faizal Muhammad, Noor Hafiza Harun,Wan Mastura Wan Zamri and Ernie Surianiy Rosly

Section 2 55

5 Applications of principal component analysis (PCA) in foodscience and technology 57 Aurea Grane and Agnieszka Jach

6 Multiple factor analysis: Presentation of the method usingsensory data 87 Jerome Pages and Francois Husson

7 Cluster analysis: Application in food science and technology103 Gaston Ares

8 Principal component regression (PCR) and partial least squaresregression (PLSR) 121 Rolf Ergon

9 Multiway methods in food science 143 Asmund Rinnan, Jose Manuel Amigo and ThomasSkov

10 Multidimensional scaling (MDS) 175 Eva Derndorfer and Andreas Baierl

11 Application of multivariate statistical methods during newproduct development Case study: Application of principalcomponent analysis and hierarchical cluster analysis on consumerliking data of orange juices 187 Paula Varela

12 Multivariate image analysis 201 Marco S. Reis

13 Case Study: Quality control of Camellia sinensis and Ilexparaguariensis teas marketed in Brazil based on total phenolics,flavonoids and free-radical scavenging activity using chemometrics219 Debora Cristiane Bassani, Domingos Savio Nunes andDaniel Granato

Section 3 231

14 Statistical approaches to develop and validatemicrobiological analytical methods 233 Anthony D. Hitchins

15 Statistical approaches to the analysis of microbiologicaldata 249 Basil Jarvis

16 Statistical modelling of anthropometric characteristicsevaluated on nutritional status 285 Zelimir Kurtanjek and Jasenka Gajdos Kljusuric

17 Effects of paediatric obesity: a multivariate analysis oflaboratory parameters 303 Tamas Ferenci and Levente Kovacs

18 Development and application of predictive microbiology modelsin foods 321 Fernando Perez-Rodriguez

19 Statistical approaches for the design of sampling plans formicrobiological monitoring of foods 363 Ursula Andrea Gonzales-Barron, Vasco Augusto Pilao Cadavezand Francis Butler

20 Infrared spectroscopy detection coupled to chemometrics tocharacterize foodborne pathogens at a subspecies level 385 Clara C. Sousa and Joao A. Lopes

Section 4 419

21 Multivariate statistical quality control 421 Jeffrey E. Jarrett

22 Application of neural-based algorithms as statistical toolsfor quality control of manufacturing processes 431 Massimo Pacella and Quirico Semeraro

23 An integral approach to validation of analyticalfingerprinting methods in combination with chemometric modellingfor food quality assurance 449 Grishja van der Veer, Saskia M. van Ruth and Jos A.Hageman

24 Translating randomly fluctuating QC records into theprobabilities of future mishaps 471 Micha Peleg, Mark D. Normand and Maria G. Corradini

25 Application of statistical approaches for analysing thereliability and maintainability of food production lines: a casestudy of mozzarella cheese 491 Panagiotis H. Tsarouhas

Index 511



Author Biography:

Dr Daniel Granato, Research Fellow, Department of FoodEngineering, State University of Ponta Grossa, Parana,Brazil.

Dr Gaston Ares, Assistant Professor, Department ofFood Science and Technology, Facultad de Quimica, Universidadde la Republica, Uruguay