Comparison of Rate-All-That-Apply (RATA) and Descriptive sensory Analysis (DA) of model double emulsions with subtle perceptual differences

Food Quality and Preference

Volumn 56, Issue , 2017, Pages 55-68

  Oppermann, A K L ^a   de Graaf, C ^a   Scholten, E ^a   Stieger, M ^a   Piqueras Fiszman, B ^a  

^a WAGENINGEN UNIVERSITY   (Netherlands)

Author keywords

CATA; Descriptive sensory profiling; Rate All That Apply (RATA); Research methodology; Sensory characterization

Indexed keywords

EID: 84991500800     PISSN: 09503293     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foodqual.2016.09.010     Document Type: Article

References (39)

1. Abdi, H., Valentin, D., Chollet, S., Chrea, C., Analyzing assessors and products in sorting tasks: DISTATIS, theory and applications. Food Quality and Preference 18:4 (2007), 627–640.
2. Adams, J., Williams, A., Lancaster, B., & Foley, M. (2007). Advantages and uses of check-all-that-apply response compared to traditional scaling of attributes for salty snacks. In 7th Pangborn sensory science symposium. Minneapolis, USA.
3. Akhtar, M., Stenzel, J., Murray, B., Dickinson, E., Factors affecting the perception of creaminess of oil-in-water emulsions. Food Hydrocolloids 19:3 (2005), 521–526.
4. Ares, G., Antúnez, L., Bruzzone, F., Vidal, L., Giménez, A., Pineau, B., et al. Comparison of sensory product profiles generated by trained assessors and consumers using CATA questions: Four case studies with complex and/or similar samples. Food Quality and Preference 45 (2015), 75–86.
5. Ares, G., Bruzzone, F., Gimenez, A.N.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 26:5 (2011), 363–370.
6. Ares, G., Bruzzone, F., Vidal, L., Cadena, R.S., Giménez, A., Pineau, B., et al. Evaluation of a rating-based variant of check-all-that-apply questions: Rate-all-that-apply (RATA). Food Quality and Preference 36 (2014), 87–95.
7. Ares, G., Deliza, R., Barreiro, C., Giménez, A., & Gámbaro, A. (2010). Comparison of two sensory profiling techniques based on consumer perception. 21(4), 417–426.
8. Ares, G., Jaeger, S.R., Examination of sensory product characterization bias when check-all-that-apply (CATA) questions are used concurrently with hedonic assessments. Food Quality and Preference 40:Part A(0) (2015), 199–208.
9. Balcaen, M., Vermeir, L., Declerck, A., Van Der Meeren, P., Influence of internal water phase gelation on the shear- and osmotic sensitivity of W/O/W-type double emulsions. Food Hydrocolloids 58 (2016), 356–363.
10. Benjamins, J., Vingerhoeds, M.H., Zoet, F.D., de Hoog, E.H.A., van Aken, G.A., Partial coalescence as a tool to control sensory perception of emulsions. Food Hydrocolloids 23:1 (2009), 102–115.
11. Chojnicka-Paszun, A., de Jongh, H.H.J., de Kruif, C.G., Sensory perception and lubrication properties of milk: Influence of fat content. International Dairy Journal 26:1 (2012), 15–22.
12. Chung, C., Smith, G., Degner, B., McClements, D.J., Reduced fat food emulsions: Physicochemical, sensory, and biological aspects. Critical Reviews in Food Science and Nutrition, 2015.
13. Escofier, B., Pagès, J., Multiple factor analysis (AFMULT package). Computational Statistics & Data Analysis 18:1 (1994), 121–140.
14. Giacalone, D., Hedelund, P.I., Rate-all-that-apply (RATA) with semi-trained assessors: An investigation of the method reproducibility at assessor-, attribute- and panel-level. Food Quality and Preference 51 (2016), 65–71.
15. Hayes, J.E., Sullivan, B.S., Duffy, V.B., Explaining variability in sodium intake through oral sensory phenotype, salt sensation and liking. Physiology & Behavior 100:4 (2010), 369–380.
16. Husson, F., Josse, J., Lê, S., & Mazet, J. (2013). FactoMineR: multivariate exploratory data analysis and data mining with R. R package version 1.24.
17. Husson, F., Le Dien, S., Pagès, J., Which value can be granted to sensory profiles given by consumers? Methodology and results. Food Quality and Preference 12:5–7 (2001), 291–296.
18. Jaeger, S.R., Cardello, A.V., Direct and indirect hedonic scaling methods: A comparison of the labeled affective magnitude (LAM) scale and best–worst scaling. Food Quality and Preference 20:3 (2009), 249–258.
19. Jaeger, S.R., Chheang, S.L., Yin, J., Bava, C.M., Gimenez, A., Vidal, L., et al. Check-all-that-apply (CATA) responses elicited by consumers: Within-assessor reproducibility and stability of sensory product characterizations. Food Quality and Preference 30:1 (2013), 56–67.
20. Jones, L.V., Peryam, D.R., Thurstone, L.L., Development of a scale for measuring soldiers’ food preferences. Journal of Food Science 20:5 (1955), 512–520.
21. Josse, J., Pagès, J., Husson, F., Testing the significance of the RV coefficient. Computational Statistics & Data Analysis 53:1 (2008), 82–91.
22. Kennedy, J., Evaluation of replicated projective mapping of granola bars. Journal of Sensory Studies 25:5 (2010), 672–684.
23. Lawless, H.T., Glatter, S., Consistency of multidimensional scaling models derived from odor sorting. Journal of Sensory Studies 5:4 (1990), 217–230.
24. Lê, S., Josse, J., Husson, F., FactoMineR: An R package for multivariate analysis. Journal of Statistical Software 25:1 (2008), 1–18.
25. Lelièvre, M., Chollet, S., Abdi, H., Valentin, D., What is the validity of the sorting task for describing beers? A study using trained and untrained assessors. Food Quality and Preference 19:8 (2008), 697–703.
26. Li, B., Hayes, J.E., Ziegler, G.R., Interpreting consumer preferences: Physicohedonic and psychohedonic models yield different information in a coffee-flavored dairy beverage. Food Quality and Preference 36 (2014), 27–32.
27. Manoukian, E.B., Mathematical nonparametric statistics. 1986, Gordon & Breach, New York.
28. Meyners, M., Jaeger, S.R., Ares, G., On the analysis of Rate-All-That-Apply (RATA) data. Food Quality and Preference 49 (2016), 1–10.
29. Oppermann, A.K.L., Piqueras-Fiszman, B., De Graaf, C., Scholten, E., Stieger, M., Descriptive sensory profiling of double emulsions with gelled and non-gelled inner water phase. Food Research International 85 (2016), 215–223.
30. Oppermann, A.K.L., Renssen, M., Schuch, A., Stieger, M., Scholten, E., Effect of gelation of inner dispersed phase on stability of (w1/o/w2) multiple emulsions. Food Hydrocolloids 48 (2015), 17–26.
31. Reinbach, H. C., Giacalone, D., Ribeiro, L. M., Bredie, W. L. P., & Frøst, M. B. (2014). Comparison of three sensory profiling methods based on consumer perception: CATA, CATA with intensity and Napping®. 32, 160–166.
32. Robert, P., Escoufier, Y., A unifying tool for linear multivariate statistical methods: The RV coefficient. Applied Statistics 25 (1976), 257–265.
33. Stone, H., Sidel, J.L., Sensory evaluation practices. 2004, Academic Press, Orlando, FL.
34. Stone, H., Sidel, J.L., Oliver, S., Woolsey, A., Singleton, R.C., Sensory evaluation by quantitative descriptive analysis. Food Technology, 28(11), 1974, 24.
35. van Aken, G.A., de Hoog, E.H.A., Nixdorf, R.R., Zoet, F.D., Vingerhoeds, M.H., Aspects of sensory perception of food emulsions thickened by polysaccharides. Williams, P.A., Phillips, G.O., (eds.) Gums and stabilisers for the food industry 13, 2006, Royal Society of Chemistry, Cambridge.
36. van Aken, G.A., Vingerhoeds, M.H., de Wijk, R.A., Textural perception of liquid emulsions: Role of oil content, oil viscosity and emulsion viscosity. Food Hydrocolloids 25:4 (2011), 789–796.
37. 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 48:2 (2012), 893–908.
38. Varela, P., Ares, G., Novel techniques in sensory characterization and consumer profiling. 2014, CRC Press.
39. Worch, T., Lê, S., Punter, P., How reliable are the consumers? Comparison of sensory profiles from consumers and experts. Food Quality and Preference 21:3 (2010), 309–318.