紹介
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.
目次
About the editors xi List of contributors xiii Acknowledgements xvii Section 1 1 1 The use and importance of design of experiments (DOE) in process modelling in food science and technology 3 Daniel Granato and Veronica Maria de Araujo Calado 2 The use of correlation, association and regression to analyze processes and products 19 Daniel Cozzolino 3 Case study: Optimization of enzyme-aided extraction of polyphenols from unripe apples by response surface methodology 31 Hu-Zhe Zheng and Shin-Kyo Chung 4 Case study: Statistical analysis of eurycomanone yield using a full factorial design 43 Azila Abdul-Aziz, Harisun Yaakob, Ramlan Aziz, Roshanida Abdul Rahman, 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 food science and technology 57 Aurea Grane and Agnieszka Jach 6 Multiple factor analysis: Presentation of the method using sensory data 87 Jerome Pages and Francois Husson 7 Cluster analysis: Application in food science and technology 103 Gaston Ares 8 Principal component regression (PCR) and partial least squares regression (PLSR) 121 Rolf Ergon 9 Multiway methods in food science 143 Asmund Rinnan, Jose Manuel Amigo and Thomas Skov 10 Multidimensional scaling (MDS) 175 Eva Derndorfer and Andreas Baierl 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 187 Paula Varela 12 Multivariate image analysis 201 Marco S. Reis 13 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 219 Debora Cristiane Bassani, Domingos Savio Nunes and Daniel Granato Section 3 231 14 Statistical approaches to develop and validate microbiological analytical methods 233 Anthony D. Hitchins 15 Statistical approaches to the analysis of microbiological data 249 Basil Jarvis 16 Statistical modelling of anthropometric characteristics evaluated on nutritional status 285 Zelimir Kurtanjek and Jasenka Gajdos Kljusuric 17 Effects of paediatric obesity: a multivariate analysis of laboratory parameters 303 Tamas Ferenci and Levente Kovacs 18 Development and application of predictive microbiology models in foods 321 Fernando Perez-Rodriguez 19 Statistical approaches for the design of sampling plans for microbiological monitoring of foods 363 Ursula Andrea Gonzales-Barron, Vasco Augusto Pilao Cadavez and Francis Butler 20 Infrared spectroscopy detection coupled to chemometrics to characterize 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 tools for quality control of manufacturing processes 431 Massimo Pacella and Quirico Semeraro 23 An integral approach to validation of analytical fingerprinting methods in combination with chemometric modelling for food quality assurance 449 Grishja van der Veer, Saskia M. van Ruth and Jos A. Hageman 24 Translating randomly fluctuating QC records into the probabilities of future mishaps 471 Micha Peleg, Mark D. Normand and Maria G. Corradini 25 Application of statistical approaches for analysing the reliability and maintainability of food production lines: a case study of mozzarella cheese 491 Panagiotis H. Tsarouhas Index 511
