Descriptive Analysis in Sensory Evaluation A series of books on selected topics in the field of Sensory Evaluation The first book in the Sensory Evaluation series is Sensory Evaluation: A Practical Handbook, published in May 2009 It focuses on the practical aspects of sensory testing, presented in a simple, ‘how to’ style for use by industry and academia as a step‐by‐step guide to carrying out a basic range of sensory tests In‐depth coverage was deliberately kept to a minimum Subsequent books in the series cover selected topics in sensory evaluation They are intended to give theoretical background, more complex techniques and in‐depth discussion on application of sensory evaluation that were not covered in the Practical Handbook However, they will seek to maintain the practical approach of the handbook and chapters will include a clear case study with sufficient detail to enable practitioners to carry out the techniques presented Descriptive Analysis in Sensory Evaluation EDITED BY Sarah E Kemp Consultant and formerly Head of Global Sensory and Consumer Guidance, Cadbury Schweppes, UK Joanne Hort Massey Institute of Food Science and Technology Massey University New Zealand Tracey Hollowood Sensory Dimensions Ltd Nottingham, UK This edition first published 2018 © 2018 John Wiley & Sons Ltd All rights reserved No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law Advice on how to obtain permission to reuse material from this titleis available at http://www.wiley.com/go/permissions The right of Sarah E Kemp, Joanne Hort and Tracey Hollowood to be identified as authors of the editorial material in this work has been asserted in accordance with law Registered Office(s) John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK Editorial Office The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com Wiley also publishes its books in a variety of electronic formats and by print‐on‐demand Some content that appears in standard print versions of this book may not be available in other formats Limit of Liability/Disclaimer of Warranty While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make This work is sold with the understanding that the publisher is not engaged in rendering professional services The advice and strategies contained herein may not be suitable for your situation You should consult with a specialist where appropriate Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages Library of Congress Cataloging‐in‐Publication Data Names: Kemp, Sarah E., editor | Hort, Joanne, editor | Hollowood, Tracey, editor Title: Descriptive analysis in sensory evaluation / [edited] by Sarah E Kemp, Joanne Hort, Tracey Hollowood Description: Hoboken, NJ : John Wiley & Sons, 2018 | Includes bibliographical references and index | Identifiers: LCCN 2017028435 (print) | LCCN 2017043923 (ebook) | ISBN 9781118991671 (pdf) | ISBN 9781118991664 (epub) | ISBN 9780470671399 (cloth) Subjects: LCSH: Sensory evaluation Classification: LCC TA418.5 (ebook) | LCC TA418.5 D47 2018 (print) | DDC 660.072–dc23 LC record available at https://lccn.loc.gov/2017028435 Cover Design: Wiley Cover Image: © nepstock/Gettyimages Set in 10/12pt Meridien by SPi Global, Pondicherry, India 10 9 8 7 6 5 4 3 2 1 To George, Elizabeth, George and William To Mike, Holly and Socks To Campbell, Emma and Lara In memory of Pieter Punter Contents Editor Biographies, ix List of Contributors, xi Preface to the Series, xv Preface, xix Section 1: Introduction Introduction to Descriptive Analysis, Sarah E Kemp, May Ng, Tracey Hollowood and Joanne Hort General Considerations, 41 Sylvie Issanchou Setting Up and Training a Descriptive Analysis Panel, 81 Margaret A Everitt Panel Quality Management: Performance, Monitoring and Proficiency, 113 Carol Raithatha and Lauren Rogers Statistical Analysis of Descriptive Data, 165 Anne Hasted Section 2: Techniques Consensus Methods for Descriptive Analysis, 213 Edgar Chambers IV Original Flavor and Texture Profile and Modified/Derivative Profile Descriptive Methods, 237 Alejandra M Muñoz and Patricia A Keane Quantitative Descriptive Analysis, 287 Joel L Sidel, Rebecca N Bleibaum and K.W Clara Tao Spectrum™ Method, 319 Clare Dus, Lee Stapleton, Amy Trail, Annlyse Retiveau Krogmann and Gail Vance Civille vii viii Contents 10 Quantitative Flavour Profiling, 355 Sophie Davodeau and Christel Adam ® 11 A daptive Profile Method , 389 Alejandra M Muñoz 12 Ranking and Rank‐Rating, 447 Graham Cleaver 13 Free Choice Profiling, 493 Pieter H Punter 14 Flash Profile Method, 513 Wender L.P Bredie, Jing Liu, Christian Dehlholm and Hildegarde Heymann 15 Projective Mapping & Sorting Tasks, 535 Dominique Valentin, Sylvie Chollet, Michael Nestrud and Hervé Abdi 16 Polarized Sensory Positioning, 561 Gastón Ares, Lucía Antúnez, Luis de Saldamando and Ana Giménez 17 Check‐All‐That‐Apply and Free Choice Description, 579 Dominic Buck and Sarah E Kemp Section 3: Applications 18 Application of Descriptive Sensory Analysis to Food and Drink Products, 611 Cindy Beeren 19 Application of Descriptive Analysis to Non‐Food Products, 647 Anne Churchill and Ruth Greenaway Section 4: Summary 20 Comparison of Descriptive Analysis Methods, 681 Alejandra M Muñoz, Sarah E Kemp, Tracey Hollowood and Joanne Hort Index, 711 Index A5daptive Profile Method® 273–281, 389–444, 685 advantages 420, 421 applications 422 assessment prior to implementation 396–400 assessors 398 company‐wide support 400 facilities 398 management support 396–398 number of test requests 398 staff 398–400 assessor screening 400–405 case studies 428–440 audit and improvement process 432–440 body lotions and creams 428–431 constraints 422–426 attrition 426 budget constraints 422–424 lack of support 426 staff limitations 426 time constraints 425–426 disadvantages 420–421 existing programmes 396, 397 future directions 442–444 implementation 400–417 methodology 417–420 panel activities 417–418 pre‐project activities 417, 418 product evaluations 419 reporting results 419–420 new programmes 391–396 panel maintenance 421 principles 389–390 statistical analysis 419, 426–428 complex project descriptive data 428 panel performance 427 routine project descriptive data 427 training 405–417, 423–424, 425–426 see also comparisons of methods; profile methods acoustic studies, cars 671–672 action standards 144 active ingredients, food and drink products 632–633 adaptation 64–65 flavour perception 367 gustatory 64–65 olfactory 64–65 sensory fatigue 472 Tragon QDA® methodology 298–299 see also A5daptive Profile Method® advertising claims substantiation 314, 315, 348 for assessors 87 ageing 62 agency panels 83 air fresheners 667 malodour reduction case study 348, 349 alcohol‐containing food and drinks 634 amplitude/arrangement test 250–251 analysis of variance (ANOVA) 9, 166–175 A5daptive Profile Method® 427 assumptions 174–175 comparison of means 170–171 flash profiling 520–521 mean square error (MSE) 128–130 models 168–170 multiple comparison tests 171–172 multivariate (MANOVA) 175, 186 panel variation 166–168 performance assessment 106–107, 120, 128–131 Procrustes analysis of variance (PANOVA) 502–503, 505–506 quantitative flavour profiling 368 ranking data 462 Spectrum™ Method validation 333 Descriptive Analysis in Sensory Evaluation, First Edition Edited by Sarah E. Kemp, Joanne Hort and Tracey Hollowood © 2018 John Wiley & Sons Ltd Published 2018 by John Wiley & Sons Ltd 711 712 Index analysis of variance (ANOVA) (cont’d) statistical significance 172–173 Tragon QDA® 302–303 visualizing sample differences 173–174 see also statistical analysis androstenone sensitivity 61 ANOVA see analysis of variance (ANOVA) Anscombe’s Quartet 192 antiperspirants 659–660 applicability testing 588 application form for assessors 87 response assessment 88 aromas see odours/olfactory stimuli assessors 18 check‐all‐that‐apply studies 586 food and drink products 613–614 method comparisons 693–694 non‐food products 653–654 performance, ranking studies 477–480 see also panel performance polarized sensory positioning 565 profile methods 271 A5daptive Profile Method® 398 ranking methods 449 see also panels; recruitment; screening; training association effects 101 astringency 64–65, 92 attribute descriptions 100–101 association effects 101 attribute distinction 101 consolidation of attributes 102 attribute rating 103–104 frame of reference 103–104 quantitative rating scale 103 see also rating scales audit process, A5daptive Profile Method® 432–440 automotive products 670–673 aversions to food products 88 balanced incomplete block (BIB) design 59 behavioural traits, assessors 94, 249 beverages see food and drink products bias consensus methods 227–228 dumping effect 67 expectation bias 65 positional bias 67–68 sensory adaptation 64–65 see also error bitterness 47, 65 sensitivity differences 61–62, 74, 91 sensitivity screening 91 body lotions and creams case study 428–431 bottled water off‐flavour case study 640–641 brand marketing 314 see also marketing build‐up effects 64–65 see also adaptation butter cookie flavour case study 372–375 sample flavour case study 223 canonical variates analysis (CVA) 72, 159–160, 186–188 carry‐over effect 472–473 cars 670–673 case studies body lotions and creams 428–431 butter samples, consensus method 223 cheese 598–599 smoked fresh cheese 524–527 cheese cracker 273–281 cookie butter flavours 372–375 curry powder 539–541 dessert sweetness 484–488 dinner napkins 348, 350 extra virgin olive oils 309–312 hand lotion 306–307 ice cream 377–385 malodour reduction 348, 349 mascara attributes 349–351 meat‐based snack products 599–602 mint candy 307–309 orange juice 547–551 perfumes 503–508 rank‐rating study 487 ranking studies 475–488 complete block example 475–484 incomplete block example 484–486 salted snack rancidity/staleness 596–598 savoury product crispiness 475–483 vanilla flavour optimization 377–385 water off‐flavour 640–641 wine, model system 527–529 yoghurt 570–572 category scales 51–52 central error 68 central location tests (CLT) 7, 310, 379, 475 check‐all‐that‐apply (CATA) methods 16, 579, 581–589, 602–603, 683, 686 advantages 593 applications 595–596 Index 713 assessors 586 case studies 596–602 data collection 586–587 descriptor elicitation 582 disadvantages 593–595 future developments 603 practical considerations 592 questionnaire design 583–586 attribute number 583 attribute order 584–585 inclusion of other questions 585–586 response method 585 terms 583 samples 586 statistical analysis 587–588 variants 588–589 cheese case study 598–599 smoked cheese 524–527 cheese cracker case study 273–281 chewing efficiency test 92–94 chocolate bar case study 636–640 claim substantiation 314, 315, 348, 649 cleaning products 665–667 cluster analysis hierarchical 159 quantitative flavour profiling 369–370 of attributes 190–191 of samples 188–190 Cochran’s Q test 599–600 colour vision tests 89–90 comfort, cars 673 comparisons of methods 681–688 applications 703–708 assessors’ characteristics 693–694 data analysis 702–703 data collection type 700–702 implementation needs 691–692 panel leader’s role 694–695 philosophies 688–690 results/output 690–691 sensory terminology 696–699 training characteristics 695–696 training references 699–700 competitive advantage, protection of 24 competitive assessment 649 complaint handling, food and drink products 628 complete block design 457–458, 475–484 Compusense® software 161 concentration ability test 48 consensus methods 8, 213–215, 684 advantages 223–226 adaptability 223–225 data collection time 225–226 group decision 225 time sequence information 225 applications 221–222 case study 223 disadvantages 226–232 data comparison 230–232 individual variation 227 lack of statistical treatment 228–229 panel discussion and bias 227–228 panel size 230 time and cost 226–227 future developments 232–233 overview 215–221 profile methods 283 A5daptive Profile Method® 419 Spectrum™ Method 340–341 terminology development 261 training 215–217, 226–227 see also comparisons of methods consistency 118, 121 evaluation 131–135 panel monitoring 145 consumer panels acceptability testing, chocolate bar 636–637 product benchmarking 630 context effect 68 continuous scales 52, 103 continuous time–intensity (CTI) techniques 10 contrast effect 68 convergence effect 68 cookie butter flavour case study 372–375 correspondence analysis (CA) polarized sensory positioning 568 sorting task 545 cosmetics, tactile properties 657–659 cross‐modal interactions 66–67 cross‐over effects 105 curry powder case study 539–541 customized 17 CV ANOVA 161 data analysis see statistical analysis data collection 165–166 check‐all‐that‐apply studies 586–587 consensus methods 225–226 flash profiling 519–520 food and drink studies 621–622 free choice profiling 496–497 method comparisons 700–702 panel monitoring 143–144 quantitative flavour profiling 367–368 714 Index degree of difference (DOD) scales polarized sensory positioning 562–563 statistical analysis 566–568 Spectrum™ Method combination 341–342 deodorants 659–660 derivative profile methods see modified/ derivative profile methods descriptive analysis 3–4 advantages and disadvantages 21–22 applications 23–26 marketing 25–26 product development and design 23–24 quality assurance and control 24–25 research 26 as a tool 17–22 benefits of 20–21 contributions of 26–29 to industry 26–27 to physico‐chemistry 28 to physiology 28 to psychology 27–28 to statistical analysis 29 customized modification 17 evolution of 4–7 factors affecting results 61–69 physiological factors 61–65 psychological factors 65–69 future developments 30, 73–75 historical background 7–17 reporting results 72–73 descriptor generation 49–51 check‐all‐that‐apply method 582 dessert sweetness case study 484–488 detergents 663–665 deviation from reference profiling 10 diagnostic descriptive analysis (DDA) 301 difference for control (DFC) method, Spectrum™ Method combination 341–342 difference from control profiling 10 difference testing 67, 230, 364 dilution flavour profile dinner napkin case study 348, 350 discrimination, panel performance 118, 121–122 evaluation 130–131 monitoring 145 see also stimulus discrimination ability dishwashing products 665–667 disposable razors 669 DISTATIS method 549–551 drinks see food and drink products dual‐attribute time–intensity (DATI) studies 13 dumping effect 67 dynamic flavour profile method 13 electronic tongue 674 engagement 118 environmental considerations 367 food and drink products 618–619 storage area 619 error central 68 expectation 65 logical 66 range‐frequency effect 68 stimulus 66 suggestion 65 see also bias evolution of descriptive analysis 4–7 expectation error 65 experimental design balanced incomplete block (BIB) design 59 complete block design 457–458, 475–484 incomplete block designs 59, 458–459, 484–488 see also sample presentation external preference mapping 381 extra virgin olive oil case study 309–312 F test 172 fabric assessment 667–669 fabric care products 663–665 Farnsworth–Munsell 100 hue test 90 fast thinking 580–581 fatigue, sensory 136, 453, 471, 472, 552 feedback panel motivation 108–109, 372 panel quality management 117, 119 quantitative flavour profiling 366–367 training sessions 54–55 feedback calibration method (FCM) 161 FIZZ® software 139, 161 flash profiling 14, 497, 513–530, 686 advantages and disadvantages 522–524 alternative approaches 517–519 applications 524 case studies 524–529 one‐shot analysis 524–527 small sensory differences 527–529 future developments 530 panel 516 practical considerations 518–519 Index 715 process 516–517 statistical analysis 519–522 theoretical framework 514–516 Flash table 70, 71 flavor profile method (FPM) 7–8, 237, 281–282, 283, 320–321, 684 historical perspective 238–239 methodology 247–266, 320–321 acuity screening 250–251, 256 pre‐screening 247–250, 256 staff requirements 253–254 terminology development 261–262 training 255–264, 320–321 pharmaceuticals 674 principles 246 project work 264–266 statistical analysis 273 see also comparisons of methods; modified/ derivative profile methods; profile methods flavourists 355–356 see also quantitative flavour profiling (QFP) flavours 355 creation of 355–356 see also flavor profile method (FPM); quantitative flavour profiling (QFP); taste food allergies 620 food and drink products 611–644 active ingredients 632–633 alcohol‐containing products 634 aversions 88 case studies 636–643 chocolate bar 636–640 quality control testing 642–643 water off‐flavour 640–641 changes during shelf‐life 626–627 data collection 621–622 fresh produce 635 frozen products 634–635 future developments 644 hot served products 630–632 new product compliance 626–627 non‐standard products 633–634 panel selection 613–616 screening 614, 615–616 training 614, 616 product development 623–626 development design 623–624 implementation 625 sensory specification development 625–626 purchasing choices 611–612 quality assurance and control 627–630, 642–643 competitive benchmarking 630 complaint handling 628 compliance with descriptive specifications 628 reporting results 622–623 sample treatment 617–618 test environment 618–619 storage area 619 test method identification 612–613 test objective 612 test protocols 619–621 forced choice CATA 588 formulations, pharmaceutical products 673–674 fragrance profile method, acuity screening 252 fragrances 663 luxury perfume case study 503–508 frame of reference 53–54, 103–104 A5daptive Profile Method® 392–396 audit and improvement process 437–438 qualitative 392–393, 413–415 quantitative 393–396, 415–417 method comparisons 699–700 Spectrum™ Method 323–326 qualitative 323–324 quantitative 325–326 free choice description (FCD) 579, 582, 602–603, 686 advantages 593 applications 595–596 case study 598–599 disadvantages 593–595 future developments 603 see also open‐ended questioning free choice profiling (FCP) 11, 493–510, 515 applications 494, 499 case study 503–508 data gathered 496–497 future directions 510 historical background 48 methodology 499–503 notation 496 principle 493–494, 499 statistical analysis 497, 499–503 vocabulary 495 interpretation issues 495 free comment 590 fresh produce 635 716 Index Friedman analysis 460, 462–463, 480 critical values 490 frozen foods 634–635 gender influence on sensitivities 62–63 generalized labelled magnitude scale (gLMS) 53 generalized Procrustes analysis (GPA) 6, 159, 497–498, 509–510 flash profiling 521–522 free choice description study 598–599 history 498 polarized sensory positioning 566–567 software packages 503 globalization 5 green tea lexicon 336–339 group behaviour, A5daptive Profile Method® 404–405 gustatory stimuli see flavours; taste hair care products 661–663 hair switches 662 hand lotion case study 306–307 handfeel evaluation 252 Happy Cow Dairy Company case study 223 hierarchical cluster analysis 159 quantitative flavour profiling 369–370 historical background 7–17 HITS profiling 15 honest significant difference (HSD) test 171–172, 368 hormonal influence on sensitivities 62–63 household products air fresheners 667 malodour reduction case study 348, 349 claim substantiation 348 cleaning products 665–667 laundry products 663–665 toilet cleaners 667 see also personal care products hunger influence on sensitivities 63–64 ice cream, vanilla flavour case study 377–385 ideal profile method (IPM) 9–10 identity profiles 221–222 incomplete block designs 59 ranking studies 458–459, 484–488 independent judgement test 251 individual vocabulary profiling 14, 517–518 intensity reference scales 239–240 A5daptive Profile Method® 403–404, 415–417 development 242 quantitative flavour profiling 365–366 see also rating scales intensity variation descriptive method 11 internal preference mapping 381 interview for assessors 88–89 Ishihara Colour Vision Test 89–90 judge performance graph 136–140 labelled magnitude scale (LMS) 52–53 language audit and improvement process 432–437 fabric assessment 668 fabric care products 664 fragrances 663 free choice profiling 495 household cleaning products 666, 667 method comparisons 696–699 personal care products 658, 660, 662–663 quantitative flavour profiling, Sense It® language 357, 358–362 vanilla flavour case study 377 Tragon QDA® 304–305 language development 49–51 A5daptive Profile Method® 392–393, 413–415 audit and improvement process 432–437 method comparisons 696–697 non‐food products 654–656, 658 case study 655–657 profile methods 258–263 free choice profiling 495 quantitative flavour profiling 364–365 Sense It® language 360–362 Spectrum™ Method 323–324, 331, 334–340 Tragon QDA® 294–295 Latin square 457–458 laundry products 663–665 leader see panel leader least significant difference (LSD) 170–171 lexicon see language; language development line scales 51–52, 103 linear regression 192–199 logical error 66 luxury perfume case study 503–508 Lyon Clinical Olfactory Test (LCOT) 46–47 make‐up, tactile properties 657–659 malodour reduction case study 348, 349 MAM model 208 management support, profile methods 270 A5daptive Profile Method® 396–398 Index 717 market mapping 649 marketing 25–26 profile data use 269 Tragon QDA® applications 314 mascara case study 349–351 mean square error (MSE) 128–129 p‐MSE plot 136–138 square root (RMSE) 129–130 meat‐based snack product case study 599–602 memory, odour memorizing ability 48 methodologies choice of 43–44 comparisons of 18 see also specific methods mint candy case study 307–309 mint products 624 modelling 191–207 mixed models 209–210 multiple regression 200–202 partial least squares regression 203–205 principal component regression 202–203 simple linear regression 192–199 modified diagram method modified/derivative profile methods 237, 271–273, 281–282 case study 273–281 definition and characteristics 244–246 historical perspective 241–246 methodology 242–243, 247–266 acuity screening 251–252, 256 pre‐screening 247–250, 256 staff requirements 253–254 terminology development 262–263 training 255–264 principles 246–247 project work 264–266 statistical analysis 273 see also profile methods motivation 44, 108–109, 372 long‐term panellists 157–158 multiple regression 200–202 multidimensional scaling (MDS) polarized sensory positioning 566 sorting tasks 543–545, 548 multiple factor analysis (MFA) flash profiling 522 polarized sensory positioning 566–567 projective mapping 538, 541 multisensory perception 101 multivariate analysis 29, 42–44, 70–72, 158–160, 175–190 canonical variates analysis (CVA) 72, 159–160, 186–188 cluster analysis of attributes 190–191 cluster analysis of samples 188–190 consensus methods 220, 233 correlation 176–179, 192 covariance 176 flash profiling 521–522 modelling relationships 191–207 mixed models 209–210 multiple regression 200–202 partial least squares regression 203–205 principal component regression 202–203 simple linear regression 192–199 multivariate ANOVA (MANOVA) 175, 186 principal component analysis (PCA) 70–72, 159, 176, 179–186 Spectrum™ Method 347 Tragon QDA® 302, 304, 316, 345 see also statistical analysis Napping® 13, 524, 537 new product development 23 compliance studies 626–627 noise 581 non‐food products 647–648 air fresheners 667 assessment design 651–652 assessment protocol 650–651 automotive 670–673 cleaning products 665–667 fabric assessment 667–669 fragrances 663 future development 675 importance of descriptive analysis 648–649 language development 654–656 case study 655–657 laundry products 663–665 panellists 653–654 paper products 669–670 personal care products 657–663, 669 pharmaceuticals 673–674 sample number 652 test objective 650 textiles 667–669 non‐standard food and drink products 633–634 number of assessors see panels number of samples 57–58, 618, 652 polarized sensory positioning 565 718 Index objectives food and drink studies 612 non‐food product studies 650 odours/olfactory stimuli 355 cars 670–671 memorizing ability 48 odour recognition test 250, 251 olfactory acuity testing 46–47 profile assessors 250 sensitivity variation 61 ageing effect 62 gender and hormonal influences 62–63 hunger influence 63–64 sensory adaptation 64–65 olfactory acuity testing 46–47 profile assessors 250, 402 sensory impairment testing 90 olive oil case study 309–312 open‐ended questioning 16–17, 590–592 statistical analysis 591 optimal sensory profile 383–384 optimized descriptive profile (ODP) 15–16 oral shape recognition test 92 orange juice case study 547–551 order of appearance 225 order of presentation 58 positional bias 67–68 orientation see training p‐MSE plot 136–138 pairwise comparisons 170–172, 461–469, 481, 483, 487 palate cleansers 64–65, 620, 621 panel leader 83–85, 110 A5daptive Profile Method® 399 knowledge and skills 84 method comparisons 694–695 profile methods 253–254 role 84–85 Spectrum™ Method 329–330 panel maintenance 271 A5daptive Profile Method® 421, 426 quantitative flavour profiling 366–367 Spectrum™ Method 332 panel monitoring 113, 117, 142–151 action standards 144 consistency 145 data collection 143–144 discrimination 145 links to training and appraisals 151 long‐standing panellist issues 157–158 new panellist issues 156–157 ongoing project‐based monitoring 146–147 repeatability 144–145 scheduled diagnostic checks 147–150 validity 146 panel performance 113, 118–142 evaluation 55–56, 69, 104–108, 116, 118–142 A5daptive Profile Method® 411, 427 consistency 121, 131–135 discrimination 121–122, 130–131 future developments 111 general data quality 122–127 long‐standing panellist issues 157–158 new panellist issues 156–157 repeatability 120, 127–130 validity 122, 135–142 poor performance management 109 proficiency testing 113, 152–154 reproducibility 120–121 results evaluation 106–108 panel quality management 113–114 approaches 116–118 comparing different panels 154–156 context and 115–116 future developments 163 importance of 114 see also panel monitoring; panel performance; proficiency testing panel training see training PanelCheck V1.4.0 software 161 panellist performance see panel performance panellist recruitment see recruitment panels engagement 118 motivation 44, 108–109, 372 new assessor integration 109–110 size 45–46, 86 consensus methods 230 types of 81–83 agency panels 83 dedicated assessors 83 employees 82–83 virtual 7 see also assessors; recruitment; training paper products 669–670 parametric analysis 460–461, 466–469, 483, 484 partial least squares (PLS) regression 203–205 path PLS modelling 207 particle size discrimination test 92 Index 719 path PLS modelling 207 Pearson’s correlation coefficient 176–179 perception, multisensory 101 see also odours/olfactory stimuli; taste; touch performance see panel performance perfumes 663 luxury perfume case study 503–508 permutation test 504–505 personal care products cosmetics 657–659 fragrances 663 luxury perfume case study 503–508 hair care products 661–663 personal washing products 660 shaving products 669 tactile properties 657–659 underarm products 659–660 see also non‐food products personality traits, assessors 94, 249 A5daptive Profile Method® 404 pharmaceuticals 673–674 phenylthiocarbamide (PTC) 62, 91 pick K/pick K from N 588 pilot studies, Tragon QDAđ296297 Pivot Profileâ 15, 574 polarized projective mapping (PPM) 15, 573–574 polarized sensory positioning (PSP) 14, 561–575, 687 advantages 570 applications 569 case study 570–572 data analysis 566–569 degree of difference scales 562, 566–568 disadvantages and limitations 570 extensions of 572–574 future developments 574–575 practical considerations 563–566 assessors 565 pole selection 563–565 replication 566 sample number 565 triadic polarized sensory positioning 563, 568–569 positional bias 67–68 practice sessions see training preference mapping vanilla flavour case study 377–383 pregnancy influence on odour sensitivity 63 pre‐screening profile methods assessors 247–250, 256 Spectrum™ Method panellists 327–328 presentation see sample presentation principal component analysis (PCA) 70–72, 159, 176, 179–186 polarized sensory positioning 566 quantitative flavour profiling 369 principal component regression 202–203 Procrustes analysis of variance (PANOVA) 502–503, 505–506 product development 23–24 compliance studies 626–627 food and drink products 623–626 Tragon QDA® applications 313 product optimization 24 proficiency testing 113, 152–154 profile attribute analysis (PAA) 8, 241 profile methods 237–283 advantages 266–267 applications 268–269 case study 273–281 disadvantages 267–268 future directions 282–283 historical perspective 238–246 methodology 247–266 maintenance programme 271 management support 270 modifications 271–273 project work 264–266 screening 247–252 staff requirements 253–254, 270–271 training 255–264, 271 principles 246–247 statistical analysis 273 see also flash profiling; flavor profile method (FPM); free choice profiling (FCP); modified/derivative profile methods; quantitative flavour profiling (QFP); texture profile method (TPM) profile trainer 253, 270 A5daptive Profile Method® 398–399 progressive profiling 13 projective mapping 12–13, 535–536, 537–541, 687 advantages and disadvantages 551–553 applications 539 case example 539–541 data analysis 538 future developments 553 methodology 537–538 propylthiouracil (PROP) 62, 91 purchasing choices, food products 611–612 720 Index QDA see quantitative descriptive analysis quality assurance and control 24–25 food and drink products 627–630 non‐food products 649 panel quality management see panels profile data use 269 Tragon QDA® applications 313–314 quality rating assignment, Spectrum™ Method 342–343 quantitative descriptive analysis (QDA) 8–9, 237, 304, 683, 685 chocolate bar case study 637–640 consensus method 221 criticism of 305 see also comparisons of methods; Tragon QDA® quantitative flavour profiling (QFP) 12, 355–387, 684 applications 370–371 case studies 372–385 cookie butter flavours 372–375 vanilla flavour optimization 377–385 data collection 367–368 future development 386–387 panel maintenance 366–367 panel training 362–367 special projects 364–366 product and sample preparation 367–368 Sense It® language 357, 358–362 language selection on project 362 sensory testing environment 367 statistical analysis 368–370 theory 356–358 see also comparisons of methods; flavor profile method (FPM) quantitative frame of reference 53–54, 103–104 method comparisons 699–700 questionnaire for check‐all‐that‐apply method 583–586 for ranking task 453, 454 R‐Index analysis 460, 463–466, 480–483, 484 rancidity/staleness case study 596–598 range‐frequency effect 68 rank descriptive data (RDA) 14 rank‐rating 448, 683, 685 case study 487 choice of methodology 473–475 data analysis 469–470 methodology 454–457 see also comparisons of methods ranking 447, 683, 685 aim of 448 applications 470–475 not well‐suited test situations 472–473 well‐suited test situations 470–472 assessment protocol 453–454 attribute selection 451 case studies 475–488 choice of methodology 473–475 experimental design 457–460 complete block design 457–458, 475–484 incomplete block design 458–459, 484–488 study size and replication 459–460 future directions 489 historical background 447–449 methodology 449–457 assessor selection 449 product presentation 452 product selection 451–452 ranking direction 453 statistical analysis 460–469 Friedman analysis 460, 462–463, 480 parametric analysis 460–461, 466–469, 483, 484 R‐Index analysis 460, 463–466, 480–483, 484 ties 453 training 450–451 see also comparisons of methods ranking descriptive analysis (RDA) 518 rapid techniques 17–18, 41–42 rate‐all‐that‐apply (RATA) method 588 see also check‐all‐that‐apply (CATA) methods rating scales 103, 239–240, 580 A5daptive Profile Method® 393–395, 415–417 consistency in scale use 121 development 242 idiosyncratic scale use 69 intensity rating 239–240, 242 issues with 580–581 quantitative flavour profiling 365–366 rank‐rating method 455–457 Spectrum™ Method 322–323, 322–326 training 330–331 texture profile 239–240 see also degree of difference (DOD) scales razors, disposable 669 recruitment 44–48, 86–87 advertising for assessors 87 Index 721 application form 87 response assessment 88 non‐food product studies 653 numbers 86 offer of employment 97–98 quantitative flavour profiling 363–364 Spectrum™ Method 326–328 Tragon QDA® 294, 300–301 see also screening; specific methods regression multiple 200–202 partial least squares (PLS) 203–205 principal component 202–203 simple linear 192–199 repeatability 118, 120 evaluation 127–129 panel monitoring 144–145 repertory grid method 495, 514 replicates 60–61 food and drink studies 621 polarized sensory positioning 566 ranking study 460 reporting results 72–73 A5daptive Profile Method® 419–420 reproducibility 118, 120–121 research 26, 649 profile data use 268–269 response scales 51–54 category scales 51–52 continuous scales 52 labelled magnitude scale (LMS) 52–53 line scales 51–52 quantitative frame of reference 53–54, 103–104 response surface methodology (RSM) ring‐testing 152–153 safety, pharmaceutical testing 673–674 saliva flow measurement 92 salted snack rancidity/staleness case study 596–598 sample preparation, food and drink studies 617–618 sample presentation 56–57 check‐all‐that‐apply study 586 food and drink studies 618 incomplete block designs 59 number of samples 57–58, 618, 652 polarized sensory positioning 565 order of presentation 58 positional bias 67–68 replicates 60–61 sequence effects 68 simultaneous versus sequential presentation 57 see also experimental design savoury product crispiness case study 475–483 scales see rating scales scatter plots 140–141 scheduled diagnostic checks 147–150 screening 89–97 behavioural traits 94 food and drink assessors 614, 615–616 initial screening 87–89 application form responses 88 interview 88–89 method comparisons 693 number and length of sessions 95 profile assessors 247–252, 256 A5daptive Profile Method® 400–405 acuity screening 250–252, 402–403 pre‐screening 247–250, 256 quantitative flavour profiling 363–364 scoring screening exercises 252 programme and timetable planning 94 ranking methods 449 selection criteria and mark scheme 95–97 sensory impairment 89–94 sight 89–90 smell 90 taste 90–91 touch 91–94 Spectrum™ Method panellists 328 tests 89 Tragon QDA® 293–294 see also recruitment selection of food 50 see also panels; screening SENPAQ software 107–108, 161 Sense It® language 357, 358–362 development 360–362 language selection on project 362 see also quantitative flavour profiling (QFP) sensitivity, individual differences 61–62 sensitivity cards 384 sensory acuity testing 46–47 sensory adaptation see adaptation sensory booths 367 sensory claims substantiation 314, 315 sensory fatigue 136, 453, 471, 472, 552 sensory impairment assessment 89–94 sight 89–90 smell 90 taste 90–91 touch 91–94 722 Index sensory map 74 sensory panel see panels sensory perception measurement 291–292 see also quantitative descriptive analysis (QDA) see also odours/olfactory stimuli; taste; touch sensory profile 41 sensory profiling 73 future developments 73–75 see also descriptive analysis sensory specification generation 625–626 sequential profiling 15 shampoo 661–663 shaving products 669 shelf‐life evaluation 626–627 shower gel 660 similarity measurement 536 simple linear regression 192–199 size of panels see panels skin cream case study 428–431 language development 655–657 tactile properties 657–659 skinfeel evaluation 252 slow thinking 580–581 smell see odours/olfactory stimuli; olfactory acuity testing smoked fresh cheese case study 524–527 soap 660 sorting task 11–12, 535–536, 541–551, 686 advantages and disadvantages 551–553 application 546–547 case example 547–551 data analysis 543–545 DISTATIS method 549–551 future developments 553 methodology 542–543 sound studies, cars 671–672 Spearman’s correlation 521 Spectrum™ Method 9, 43, 50, 54, 319–351, 684 case studies 348–351 consensus method 221 historical background 320–321 independent versus consensus ratings 340–341 lexicon development 323–324, 331, 334–340 new developments 341–346 combination with DOD/DFC rating 341–342 data analysis from large numbers of samples 344–345 in sequence mapping 345–346 predictive use of descriptive data 345 product grouping/sorting 343–344 quality rating assignment 342–343 panel leader 329–330 qualifications 329 roles 329–330 panel maintenance 332 panel validation 332–334 panellist selection 326–328 pre‐screening 327–328 screening 328 source of pool 327 qualitative references 323–324 quantitative references 325–326 statistical analysis 346–347 training 330–331 universal scale 322–323 see also comparisons of methods spirits, lexicon example 335–340 spray cleaning products 665–667 standard error of mean 170 standards panel performance 158 vocabulary development 50 star diagram 173–174 staticized decisions 214–215 STATIS method 538 statistical analysis 29, 69–72 A5daptive Profile Method® 419, 426–428 check‐all‐that‐apply studies 587–588 consensus methods 228–229, 230–232 future developments 208 method comparisons 702–703 multivariate analysis 70–72, 158–160, 175–191 canonical variates analysis (CVA) 72, 159–160, 186–188 cluster analysis of attributes 190–191 cluster analysis of samples 188–190 correlation 176–179, 192 covariance 176 modeling relationships between variables 191–207 open‐ended questioning 591 panel performance 158–162 polarized sensory positioning 566–569 preliminary analysis 166 principal component analysis (PCA) 70–72, 159, 176, 179–186 product differences 69–72 Index 723 profile methods 273 flash profiling 519–522 free choice profiling 497, 499–503 projective mapping 538 quantitative flavour profiling 368–370 rank‐rating data 469–470 ranking data 460–469 Friedman analysis 460, 462–463, 480 parametric analysis 460–461, 466–469, 483, 484 R‐Index analysis 460, 463–466, 480–483, 484 software developments 160–162 sorting task 543–545 Spectrum™ Method 346–347 Spectrum™ Method, with large numbers of samples 344–345 Tragon QDA® 302–304 univariate analyses 69–70 see also analysis of variance statistical significance 172–173 stimulus discrimination ability 47 evaluation 55–56, 130–131 see also discrimination stimulus error 66 structural equation modelling 206–207 substantiation of advertising claims 314, 315, 348 suggestion error 65 supertasters 91 sweetness, dessert case study 484–488 tape plot 173–174 taste 355 acuity measurement 47 profile assessors 250, 402 sensory impairment testing 90–91 adaptation 367 pharmaceutical palatability 673–674 sensitivity variation 62 hormonal influence 62–63 hunger influence 64 sensory adaptation 64–65 see also flavours TDS see temporal dominance of sensations tea lexicon 336–339 technician, profile methods 254 A5daptive Profile Method® 400 temporal check‐all‐that‐apply (TCATA) studies 16, 589 temporal dominance of sensations (TDS) 15, 589 temporal order of sensations (TOS) 15 terminology see language; language development textiles 667–669 fabric care products 663–665 texture perception testing 92–94, 403 texture profile method (TPM) 8, 237, 281–282, 283, 321, 684 applications 243 contributions of 240–241 historical perspective 239–241 methodology 247–266, 321 acuity screening 251, 256 pre‐screening 247–250, 256 staff requirements 253–254 terminology development 262 training 255–264, 321 principles 247 project work 264–266 statistical analysis 273 see also comparisons of methods; modified/ derivative profile methods; profile methods tick‐all‐that‐apply methods see check‐all‐ that‐apply (CATA) methods time sequence information 225 time–intensity (TI) techniques 10–11 see also individual techniques toilet cleaners 667 tongue, electronic 674 TOS see temporal order of sensations touch acuity testing 403 sensory impairment testing 91–94 Tragon QDA® 8–9, 287–317, 683 advantages 304–305 applications 312–315 marketing 314 procurement team 315 product development 313 quality control 313–314 sensory claims substantiation for advertising 314, 315 case studies 306–312 extra virgin olive oils 309–312 hand lotion 306–307 mint candy 307–309 central thesis 291–292 criticism of 305 cross‐functional collaboration 301–302 future development 316–317 historical background 287–291 methodology 292–297 724 Index Tragon QDA® (cont’d) adding products to the test 299–300 language development 294–295 managing sensory attributes 299 multiple category testing 300 pilot test and validation 296–297 reference use 297 scale usage 296 screening 293–294 situational adaptations 298–299 subjects 292–293 over‐recruiting 300–301 resource constraints 301 statistical analysis 302–304 see also comparisons of methods; quantitative descriptive analysis (QDA) training 48–49, 54–55, 99–108 aids 102 aims of 99 attribute descriptions 100–101 association effects 101 attribute distinction 101 consolidation of attributes 102 attribute rating stage 103–104 frame of reference 103–104 quantitative rating scale 103 consensus methods 215–217 time and cost 226–227 feedback 54–55 food and drink assessors 614, 616 links to panel monitoring 151 method comparisons 695–696 multisensory perception 101 non‐food product studies 653–654 panel quality management 117 performance measurement 104–108 profile methods 255–264, 320–321 A5daptive Profile Method® 405–417, 423–424, 425–426 modified/derivative methods 244 practice sessions 263 profile trainer 253, 270, 398–399 quantitative flavour profiling 362–367 terminology/lexicon development 258–263 training materials 271 training sessions 255–258 validation 263–264 rank‐rating 456–457 ranking methods 450–451 Spectrum™ Method 330–331 training period 108 triadic descriptor elicitation 582 triadic polarized sensory positioning 563 statistical analysis 568–569 Tukey HSD test 171–172, 368 ultra‐flash profiling 524 underarm products 659–660 univariate analyses 69–70 flash profiling 520–521 see also statistical analysis University of Pennsylvania Smell Identification Test (UPSIT) 90 validation A5daptive Profile Method® 411–412 quantitative flavour profiling case study 375–376 Spectrum™ Method 332–334 Tragon QDA® 296–297 validity 118, 122 evaluation 135–142 panel monitoring 146 vanilla flavour case study 377–385 vehicles 670–673 verbally based qualitative methods 579 rationale 580–581 virtual descriptive panels washing powders 663–664 water off‐flavour case study 640–641 Williams Latin square 457–458 wine case study 527–529 yoghurt case study 570–572 WILEY END USER LICENSE AGREEMENT Go to www.wiley.com/go/eula to access Wiley’s ebook EULA ... Descriptive Analysis in Sensory Evaluation A series of books on selected topics in the field of Sensory Evaluation The first book in the Sensory Evaluation series is Sensory Evaluation: ... perception She obtained her Chair in 2013 and her multidisciplinary approach combining analytical, brain imaging and sensory techniques provides rich insight into multisensory interactions, individual... book is structured in four sections Section 1 is an introduction covering general topics in descriptive analysis, including panel training, panel monitoring and statistical analysis Section 2