Descriptive analysis in sensory evaluation (phép thử mô tả)

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Descriptive analysis in sensory evaluation (phép thử mô tả)

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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

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  • Title Page

  • Copyright Page

  • Contents

  • Editor Biographies

  • List of Contributors

  • Preface to the Series

  • Preface

  • Section 1 Introduction

    • Chapter 1 Introduction to Descriptive Analysis

      • 1.1 Introduction

      • 1.2 Development of Descriptive Analysis

      • 1.3 Descriptive Analysis as a Technique in Sensory Evaluation

      • 1.4 Application of Descriptive Analysis

      • 1.5 Contributions of Descriptive Analysis

      • 1.6 Summary

      • 1.7 Future Developments

      • 1.8 Overview of Book

      • References

    • Chapter 2 General Considerations

      • 2.1 General Introduction

      • 2.2 Aims of Descriptive Analysis

      • 2.3 Choices of Methodology

      • 2.4 Generic Procedure for Descriptive Analysis

      • 2.5 Factors Affecting Results in Descriptive Analysis

      • 2.6 Data Analysis

      • 2.7 Reporting Results

      • 2.8 Summary

      • 2.9 Future Developments

      • References

    • Chapter 3 Setting Up and Training a Descriptive Analysis Panel

      • 3.1 Introduction: Descriptive Analysis

      • 3.2 Types of Panel Resource

      • 3.3 Panel Leader

      • 3.4 Recruitment and Screening Programme

      • 3.5 Initial Screening

      • 3.6 Main Screening and Selection of Assessors

      • 3.7 Panel Training

      • 3.8 Panel Motivation

      • 3.9 Panel Attrition

      • 3.10 Summary

      • 3.11 The Future

      • References

    • Chapter 4 Panel Quality Management: Performance, Monitoring and Proficiency

      • 4.1 Introduction to Panel Quality Management

      • 4.2 Panel Performance

      • 4.3 Panel Monitoring

      • 4.4 Proficiency Testing

      • 4.5 Further Panel Quality Management Concerns

      • 4.6 Standards

      • 4.7 Statistics and Data Collection and Visualization

      • 4.8 Summary

      • 4.9 Future Developments

      • References

    • Chapter 5 Statistical Analysis of Descriptive Data

      • 5.1 Introduction

      • 5.2 Analysis of Variance

      • 5.3 Multivariate Data Display

      • 5.4 Modelling Relationships between Variables

      • 5.5 Summary

      • 5.6 Future Developments

      • References

      • Appendix 5.1  Mixed Models

  • Section 2 Techniques

    • Chapter 6 Consensus Methods for Descriptive Analysis

      • 6.1 Introduction

      • 6.2 Method Overview

      • 6.3 Applications

      • 6.4 Case Study

      • 6.5 Advantages

      • 6.6 Disadvantages

      • 6.7 Future Developments

      • 6.8 Summary

      • References

    • Chapter 7 Original Flavor and Texture Profile and Modified/Derivative Profile Descriptive Methods

      • 7.1 Introduction/Historical Perspective

      • 7.2 Fundamental and Philosophical Principles of Profile/Technical Descriptive Methodology

      • 7.3 Methodology – The Profile Methods

      • 7.4 Advantages and Disadvantages of Profile Methods

      • 7.5 Applications: Profile Descriptive Analysis

      • 7.6 General Recommendations: Profile Methods

      • 7.7 Modifications of Original Profile Methods

      • 7.8 Statistical Analysis

      • 7.9 Case Study: Use of Profile Descriptive Analysis in Optimization Research Guidance

      • 7.10 Summary

      • 7.11 Future Directions

      • References

    • Chapter 8 Quantitative Descriptive Analysis

      • 8.1 Introduction

      • 8.2 Background

      • 8.3 Method Description

      • 8.4 Practical Considerations

      • 8.5 Statistical Analysis of Tragon QDA Data

      • 8.6 Advantages

      • 8.7 Case Studies

      • 8.8 Additional Applications

      • 8.9 Summary

      • 8.10 Future Development

      • References

    • Chapter 9 Spectrum™ Method

      • 9.1 Introduction

      • 9.2 Theory: History Based on Flavor and Texture Profile Methods

      • 9.3 Traditional Methodology for the Spectrum Method

      • 9.4 New Developments: Combining Spectrum with Other Methods

      • 9.5 Statistical Analysis

      • 9.6 Applications with Case Studies

      • 9.7 Practical Hints/Tips

      • References

    • Chapter 10 Quantitative Flavour Profiling

      • 10.1 Introduction

      • 10.2 Theory

      • 10.3 From Traditional to Modern Quantitative Flavour Profiling

      • 10.4 Statistical Analysis

      • 10.5 Applications of QFP

      • 10.6 Practical Considerations

      • 10.7 Case Studies

      • 10.8 Summary

      • 10.9 Future Development

      • References

    • Chapter 11 A5daptive Profile Method®

      • 11.1 Introduction and Fundamental Principles

      • 11.2 Methodology

      • 11.3 Advantages and Disadvantages of the A5daptive Profile Method

      • 11.4 Applications of the A5daptive Profile Method

      • 11.5 Practical Considerations

      • 11.6 Statistical Analysis of A5daptive Profile Data

      • 11.7 Case Studies

      • 11.8 Summary

      • 11.9 Future Directions

      • References

    • Chapter 12 Ranking and Rank-Rating

      • 12.1 Introduction

      • 12.2 History and Background

      • 12.3 Methodology

      • 12.4 Experimental Design

      • 12.5 Analysis of Ranking Data

      • 12.6 Analysis of Rank-Rating Data

      • 12.7 Applications

      • 12.8 Case Studies

      • 12.9 Summary

      • 12.10 Future Directions

      • Appendix 12.1: Critical Values for the Friedman Test

      • References

    • Chapter 13 Free Choice Profiling

      • 13.1 Introduction

      • 13.2 Methodology of Free Choice Profiling

      • 13.3 Generalized Procrustes Analysis

      • 13.4 Case Study

      • 13.5 Options/Practical Considerations

      • 13.6 Summary

      • 13.7 Future Considerations

      • References

    • Chapter 14 Flash Profile Method

      • 14.1 Introduction

      • 14.2 Theoretical Framework

      • 14.3 Overview of the Flash Profile Method

      • 14.4 Case Studies

      • 14.5 Summary

      • 14.6 Future Developments

      • References

    • Chapter 15 Projective Mapping & Sorting Tasks

      • 15.1 Introduction

      • 15.2 Projective Mapping

      • 15.3 Sorting Task

      • 15.4 Pros and Cons of Projective Mapping and the Sorting Task

      • 15.5 Summary

      • 15.6 Future Developments

      • References

    • Chapter 16 Polarized Sensory Positioning

      • 16.1 Introduction

      • 16.2 Description of Polarized Sensory Positioning

      • 16.3 Practical Considerations for the Implementation of Polarized Sensory Positioning

      • 16.4 Data Analysis

      • 16.5 Applications of Polarized Sensory Positioning

      • 16.6 Advantages, Disadvantages and Limitations

      • 16.7 Case Study

      • 16.8 Extensions of Polarized Sensory Positioning

      • 16.9 Summary

      • 16.10 Future Developments

      • Acknowledgements

      • References

    • Chapter 17 Check-All-That-Apply and Free Choice Description

      • 17.1 Introduction

      • 17.2 Rationale for Use

      • 17.3 CATA Methodology

      • 17.4 Open-Ended Questioning

      • 17.5 Practical Considerations

      • 17.6 Advantages and Disadvantages

      • 17.7 Applications

      • 17.8 Case Studies

      • 17.9 Summary

      • 17.10 Future Developments

      • References

  • Section 3 Applications

    • Chapter 18 Application of Descriptive Sensory Analysis to Food and Drink Products

      • 18.1 Introduction

      • 18.2 General Principles of Descriptive Sensory Analysis Methods as Applied to Food and Drink Products

      • 18.3 Descriptive Sensory Analysis Application in Food and Drink Product Development

      • 18.4 Application of Descriptive Sensory Analysis in Food and Drink Quality Control and Quality Assurance

      • 18.5 Considerations Relating to Specific Food and Drink Products

      • 18.6 Case Studies

      • 18.7 Summary

      • 18.8 Future Developments

      • References

    • Chapter 19 Application of Descriptive Analysis to Non-Food Products

      • 19.1 Introduction

      • 19.2 Why is Descriptive Analysis of Non-Food Products Important?

      • 19.3 General Considerations in Applying Descriptive Analysis to Non-Food Products

      • 19.4 Development of Descriptive Language

      • 19.5 Considerations Relevant to Specific Non-Food Products

      • 19.6 Summary

      • 19.7 Future Developments

      • References

  • Section 4 Summary

    • Chapter 20 Comparison of Descriptive Analysis Methods

      • 20.1 Introduction

      • 20.2 Relevant Comments on the Presentation of the Methods’ Key Characteristics and Their Comparison

      • 20.3 Overall Comparison of Descriptive Methods

      • 20.4 Comparison of Methods Based on Key Characteristics

      • 20.5 Summary

      • 20.6 Future Developments

      • References

  • Index

  • EULA

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