Comparison of intensity scales and CATA questions in new product development: Sensory characterisation and directions for product reformulation of milk desserts

Food Quality and Preference

Volumn 44, Issue , 2015, Pages 183-193

  Bruzzone, Fernanda ^a   Vidal, Leticia ^a   Antúnez, Lucía ^a   Giménez, Ana ^a   Deliza, Rosires ^b   Ares, Gastón ^a  

^a UNIVERSIDAD DE LA REPÚBLICA   (Uruguay)

^b EMBRAPA AGROINDÚSTRIA DE ALIMENTOS   (Brazil)

Author keywords

Check all that apply questions; Drivers of liking; Ideal Profile; Intensity scales; Product reformulation

Indexed keywords

EID: 84929460393     PISSN: 09503293     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foodqual.2015.04.017     Document Type: Article

References (53)

1. Albert A., Varela P., Salvador A., Hough G., Fiszman S. Overcoming the issues in the sensory description of hot served food with a complex texture. Application of QDA®, flash profiling and projective mapping using panels with different degrees of training. Food Quality and Preference 2011, 22:463-473.
2. Ares G., Antúnez L., Giménez A., Roigard C.M., Pineau B., Hunter D.C., et al. Further investigations into the reproducibility of check-all-that-apply (CATA) questions for sensory product characterization elicited by consumers. Food Quality and Preference 2014, 36:111-121.
3. Ares G., Barreiro C., Deliza R., Giménez A., Gámbaro A. Application of a check-all-that-apply question to the development of chocolate milk desserts. Journal of Sensory Studies 2010, 25:67-86.
4. Ares G., Bruzzone F., Giménez A. Is a consumer panel able to reliably evaluate the texture of dairy desserts using unstructured intensity scales? Evaluation of global and individual performance. Journal of Sensory Studies 2011, 26:363-370.
5. Ares G., Dauber C., Fernández E., Giménez A., Varela P. Penalty analysis based on CATA questions to identify drivers of liking and directions for product reformulation. Food Quality and Preference 2014, 32:65-76.
6. Ares G., Etchemendy R., Antúnez L., Vidal L., Giménez A., Jaeger S. Visual attention by consumers to check-all-that-apply questions: Insights to 4 support methodological development. Food Quality and Preference 2014, 32:210-220.
7. Ares G., Varela P., Rado G., Giménez A. Identifying ideal products using three different consumer profiling methodologies. Comparison with external preference mapping. Food Quality and Preference 2011, 22:581-591.
8. Ares G., Varela P., Rado G., Giménez A. Are consumer profiling techniques equivalent for some product categories? The case of orange-flavoured powdered drinks. International Journal of Food Science & Technology 2011, 46:1600-1608.
9. Blancher G., Clavier B., Egoroff C., Duineveld K., Parcon J. A method to investigate the stability of a sorting map. Food Quality and Preference 2012, 23:36-43.
10. Bruzzone F., Ares G., Giménez A. Consumers' texture perception of milk desserts. II - Comparison with trained assessors' data. Journal of Texture Studies 2012, 43:214-226.
11. Costa A.I.A., Jongen W.M.F. New insights into consumer-led food product development. Trends in Food Science & Technology 2006, 17:457-465.
12. Dairou V., Sieffermann J.-M. A comparison of 14 jams characterized by conventional profile and a quick original method, flash profile. Journal of Food Science 2002, 67:826-834.
13. Damasio M.H., Costell E. Análisis sensorial descriptivo: generación de descriptores y selección de catadores. Revista de Agroquímica y Tecnología de Alimentos 1991, 32:165-177.
14. Dehlholm C., Brockhoff P., Meinert L., Aaslyng M., Bredie W. Rapid descriptive sensory methods-Comparison of free multiple sorting, partial napping, napping, flash profiling and conventional profiling. Food Quality and Preference 2012, 26:267-277.
15. Dooley L., Lee Y.S., Meullenet J.F. The application of check-all-that-apply (CATA) consumer profiling to preference mapping of vanilla ice cream and its comparison to classical external preference mapping. Food Quality and Preference 2010, 21:394-401.
16. Grunert K.G., van Trijp H.C.M. Consumer-oriented new product development. Encyclopedia of agriculture and food systems 2014, Vol. 2:375-386. Academic Press, San Diego, CA.
17. Guerrero L., Gou P., Arnau J. Descriptive analysis of toasted almonds: A comparison between expert and semi-trained assessors. Journal of Sensory Studies 1996, 12:39-54.
18. Sensory analysis: General guidance for the design of test rooms, ISO 8589 1998, ISO 8589, International Organization for Standardization, Geneva, Switzerland.
19. Jaeger S.R., Ares G. Lack of evidence that concurrent sensory product characterization using CATA questions bias hedonic scores. Food Quality and Preference 2014, 35:1-5.
20. Jaeger S., Chheang S.L., Christina M.B., Giménez A., Vidal L., Ares G. Check-all-that-apply (CATA) responses elicited by consumers: Within-assessor reproducibility and stability of sensory product characterizations. Food Quality and Preference 2013, 30:56-67.
21. Jaeger S., Giacalone D., Roigard C.M., Pineau B., Vidal L., Giménez A., et al. Investigation of bias of hedonic scores when co-eliciting product attribute information using CATA questions. Food Quality and Preference 2013, 30:242-249.
22. Josse J., Husson F., Pagès J. Testing the significance of the RV coefficient. IASC 07, August 30th - September 1st (2007). Aveiro 2007, International Association for Statistical Computing, Portugal.
23. Labbe D., Rytz A., Hugi A. Training is a critical step to obtain reliable product profiles in a real food industry context. Food Quality and Preference 2004, 15:341-348.
24. Lagrange V., Norback J.P. Product optimization and the acceptor set size. Journal of Sensory Studies 1987, 2:119-136.
25. Lawless H.T., Heymann H. Sensory evaluation of food. Principles and practices 2010, Springer, New York. 2nd ed.
26. Lawless H.T., Sheng N., Knoops S.S.C.P. Multidimensional scaling of sorting data applied to cheese perception. Food Quality and Preference 1995, 6:91-98.
27. Lê S., Josse J., Husson F. Factominer: An R package for multivariate analysis. Journal of Statistical Software 2008, 25:1-18.
28. Linnemann A.R., Benner M., Verkerk R., van Boekel M.A.J.S. Consumer-driven food product development. Trends in Food Science & Technology 2006, 17:184-190.
29. Manoukian E.B. Mathematical nonparametric statistics 1986, Gordon & Breach, New York.
30. Meilgaard M., Civille G.V., Carr B.T. Sensory evaluation techniques 1991, CRC Press, Boca Raton, FL.
31. Meyners M., Castura J.C., Carr B.T. Existing and new approaches for the analysis of CATA data. Food Quality and Preference 2013, 30:309-319.
32. Meyners M., Castura J.C. Check-all-that-apply questions. Novel techniques in sensory characterization and consumer profiling 2014, 271-305. CRC Press, Boca Raton. P. Varela, G. Ares (Eds.).
33. Moskowitz H., Hartmann J. Consumer research: Creating a solid base for innovative strategies. Trends in Food Science & Technology 2008, 19:581-589.
34. Moussaoui K.A., Varela P. Exploring consumer product profiling techniques and their linkage to a quantitative descriptive analysis. Food Quality and Preference 2010, 21:1088-1099.
35. Parente M.E., Ares G., Manzoni A.V. Application of two cosmetic profiling techniques to cosmetic emulsions. Journal of Sensory Studies 2011, 25:685-705.
36. Plaehn D. CATA penalty/reward. Food Quality and Preference 2012, 24:141-152.
37. Popper R., Rosenstock W., Schraidt M., Kroll B.J. The effect of attribute questions on overall liking ratings. Food Quality and Preference 2004, 15:853-858.
38. R: A language and environment for statistical computing 2013, R Core Team, R foundation for statistical computing, Vienna, Austria.
39. Robert P., Escoufier Y. A unifying tool for linear multivariate statistical methods: The RV coefficient. Applied Statistics 1976, 25:257-265.
40. Roberts A.K., Vickers Z.M. A comparison of trained and untrained judges, evaluation of sensory attribute intensities and liking of Cheddar cheeses. Journal of Sensory Studies 1994, 9:1-20.
41. Stewart-Knox B., Mitchell P. What separates the winners from the losers in new food product development?. Trends in Food Science & Technology 2003, 14:58-64.
42. Symoneaux R., Galmarini M.V., Mehinagic E. Comment analysis of consumer's likes and dislikes as an alternative tool to preference mapping. A case study on apples. Food Quality and Preference 2012, 24:59-66.
43. van Kleef E., van Trijp H.C.M., Luning P. Internal versus external preference analysis: An exploratory study on end-user evaluation. Food Quality and Preference 2006, 17:387-399.
44. van Trijp H.C.M., Punter P., Mickartz F., Kruithof L. The quest for the ideal product: Comparing different methods and approaches. Food Quality and Preference 2007, 18:729-740.
45. Varela P., Ares G. Sensory profiling, the blurred line between sensory and consumer science. A review of novel methods for product characterization. Food Research International 2012, 48:893-908.
46. Wolters C.J., Allchurch E.M. Effect of training procedure on the performance of descriptive panels. Food Quality and Preference 1994, 5:203-214.
47. Worch, T. (2012). The ideal profile analysis: from the validation to the statistical analysis of ideal profile data [Ph.D. thesis]. Rennes, France: Agrocampus-Ouest.
48. Worch T., Dooley L., Meullenet J.F., Punter P. Comparison of PLS dummy variables and fishbone method to determine optimal product characteristics from ideal profiles. Food Quality and Preference 2010, 21:1077-1087.
49. Worch T., Lê S., Punter P., Pagés J. Assessment of the consistency of ideal profiles according to non-ideal data for IPM. Food Quality and Preference 2012, 24:99-110.
50. Worch T., Lê S., Punter P., Pagés J. Construction of an Ideal Map (IdMap) based on the ideal profiles obtained directly from consumers. Food Quality and Preference 2012, 26:93-104.
51. Worch T., Lê S., Punter P., Pagés J. Extension of the consistency of the data obtained with the Ideal Profile Method: Would the ideal products be more liked than the tested products?. Food Quality and Preference 2012, 26:74-80.
52. Worch T., Punter P. Ideal profiling. Novel techniques in sensory characterization and consumer profiling 2014, 85-136. CRC Press, Boca Raton. P. Varela, G. Ares (Eds.).
53. Xiong R., Meullenet J.F. A PLS dummy variable approach to assess the impact of JAR attributes on liking. Food Quality and Preference 2006, 17:188-198.