LEADER 05395nam 2200649Ia 450 001 9910830893903321 005 20230421045212.0 010 $a1-281-45026-X 010 $a9786611450267 010 $a0-470-38505-7 010 $a0-470-38483-2 035 $a(CKB)1000000000687201 035 $a(EBL)353505 035 $a(OCoLC)476175064 035 $a(SSID)ssj0000354521 035 $a(PQKBManifestationID)11275367 035 $a(PQKBTitleCode)TC0000354521 035 $a(PQKBWorkID)10302799 035 $a(PQKB)11656050 035 $a(MiAaPQ)EBC353505 035 $a(EXLCZ)991000000000687201 100 $a19971202d1997 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMultivariate data analysis in sensory and consumer science$b[electronic resource] /$fby Garmt B. Dijksterhuis 210 $aTrumbull, Conn. $cFood & Nutrition Press$dc1997 215 $a1 online resource (320 p.) 225 1 $aPublications in food science and nutrition 300 $aDescription based upon print version of record. 311 $a0-917678-41-9 320 $aIncludes bibliographical references and index. 327 $aMULTIVARIATE DATA ANALYSIS IN SENSORY AND CONSUMER SCIENCE; Prologue and Acknowledgements; CONTENTS; Introduction to Part IV; 1 Introduction; 1.2 Sensory Science; 1.1 Research Question; 1.3 Sensory Research and Sensory Profiling Data; 1.4 Sensory Profiling; 1.5 Individual Differences; 1.6 Measurement Levels; 1.7 Sensory-Instrumental Relations; 1.8 Time-Intensity Data Analysis; 1.9 Data Analysis. Confirmation and Exploration; 1.10 Structure of the Book; PART I: INDIVIDUAL DIFFERENCES; Introduction to Part I; 2 Assessing Panel Consonance; 2.1 Introduction; 2.2 Data Structure; 2.3 Method 327 $a2.4 Examples2.5 Conclusion; 3 Interpreting Generalized Procrustes Analysis "Analysis of Variance" Tables; 3.1 Introduction; 3.2 Two Different Procrustes Methods; 3.3 Sums-of-squares in Generalized Procrustes Analysis; 3.4 Scaling the Total Variance; 3.5 Generalized Procrustes Analysis of a Conventional Profiling Experiment; 3.6 Generalized Procrustes Analysis of a Free Choice Profiling Experiment; 3.7 Conclusion; Concluding Remarks Part I; Introduction to Part II; 4 Multivariate Analysis of Coffee Images; 4.1 Introduction; 4.2 Data; 4.3 Methodology; 4.4 Analyses; 4.5 Conclusion 327 $a5 Nonlinear Canonical Correlation Analysis of Multiway Data5.1 Introduction; 5.2 K-Sets Homogeneity Analysis; 5.3 K-Sets Canonical Correlation Analysis; 5.4 An Application of Overals to Multiway Data; 5.5 Conclusion; 6 Nonlinear Generalised Canonical Analysis: Introduction and Applicationfrom Sensory Research; 6.1 Introduction; 6.2 Generalised Canonical Analysis; 6.3 Nonlinear Generalised Canonical Analysis; 6.4 Application from Sensory Research; 6.5 Results; 6.6 Conclusion; Concluding Remarks Part II; PART III: SENSORY-INSTRUMENTAL RELATIONS; Introduction to Part I11 327 $a7 An Application of Nonlinear Redundancy Analysis7.1 Introduction; 7.2 Redundancy Analysis; 7.3 Optimal Scaling; 7.4 Apple Data; 7.5 Results For Cox Apples; 7.6 Results For Elstar; 7.7 Conclusion; 8 An Application of Nonlinear Redundancy Analysis and Canonical Correlation Analysis; 8.1 Introduction; 8.2 Techniques; 8.3 Description of the Data; 8.4 REDUNDALS Results; 8.5 CANALS Results; 8.6 Conclusions; 9 Procrustes Analysis in Studying Sensory-Instrumental Relations; 9.1 Introduction; 9.2 Data; 9.3 Procrustes Analysis; 9.4 A First Look at the Data: PCA 327 $a9.5 Matching the Sensory and Instrumental Data Sets9.6 Conclusion; Concluding Remarks Part I11; PART IV: TIME-INTENSITY DATA ANALYSIS; 10 Principal Component Analysis of Time-Intensity Bitterness Curves; 10.1 Introduction; 10.2 Data; 10.3 Principal Curves; 10.4 Non-Centered PCA; 10.5 Further Considerations; 11 Principal Component Analysis of Time-Intensity Curves: Three Methods Compared; 11.1 Introduction; 11.2 Method; 1 1.3 Principal Curve Analysis; 1 1.4 Non-Centered Principal Curves; 11.5 Covariance Principal Curves; 11.6 Correlation Principal Curves; 11.7 Conclusion 327 $a12 Matching the Shape of Time-Intensity Curves 330 $aThis book is an outgrowth of research done by Dr. Gamt Dijsterhuis for his doctoral thesis at the University of Leiden. However, there are also contributions by several other authors, as well, including Eeke van der Burg, John Gower, Pieter Punter, Els van den Broek, and Margo Flipsen. This book discusses the use of Multivariate Data Analysis to solve problems in sensory and consumer research. More specifically the focus is on the analysis of the reactions to certain characteristics of food products, which are in the form of scores given to attributes perceived in the food stimuli; the 410 0$aPublications in food science and nutrition. 606 $aFood$xSensory evaluation 606 $aMultivariate analysis 615 0$aFood$xSensory evaluation. 615 0$aMultivariate analysis. 676 $a664 676 $a664.07 676 $a664.072 700 $aDijksterhuis$b Garmt B$0146972 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830893903321 996 $aMultivariate data analysis in sensory and consumer science$9517027 997 $aUNINA