Ir para o conteúdo principal Ir para o menu de navegação principal Ir para o rodapé
Scientific Electronic Archives
Ciências Agrárias
DOI: 10.36560/15720221625
Enviado: 2022-07-05
Publicado: 2022-07-05

Comparison of quick descriptive sensory methods in the evaluation of dulce de leche

Universidade Federal de Minas Gerais
Universidade Federal de Minas Gerais
Universidade Federal de Minas Gerais
Universidade Federal de Minas Gerais
Universidade Federal de Minas Gerais
Universidade Federal de Minas Gerais
sensory analysis, pivot profile, projective mapping, check-all-that-apply

Resumo

Sensory analysis plays a significant role in the food industry that needs to characterize and evaluate its products. Although there are various studies and sensory methods, the fast, dynamic, and low-cost, descriptive evaluations are gaining space in the market, due to the saving of time and financial investment. The Pivot Profile (PP), Projective Mapping (PM), and Check-all-that-apply (CATA) are examples of these tests. This study aimed to evaluate the results obtained by different rapid descriptive methods to provide information on the tasters’ perceptions of different brands of dulces de leche, in addition to analyzing and comparing the evaluator opinions regarding the ease and understanding in the execution of sensory evaluations performed. The methods used (PP, PM, and CATA) presented similar results, indicating an excellent discriminative capacity of the attributes and similar sensory maps. Regarding the ease of execution concerning the evaluated test, the CATA method was selected by the tasters as the easiest to perform, followed by PP and PM respectively (p <0.05), strengthening the particularity of each methodology and reinforcing its potential in description of the sensory characteristics of dulces de leche. Therefore, it is possible to highlight the effectiveness of the three descriptive sensory methods used in the evaluation of dulce de leche pasty.

Referências

  1. Alcaire, F., Antúnez, L., Vidal, L., Zorn, S., Giménez, A., Castura, J. C., & Arés, G. (2017). Comparison of static and dynamic sensory product characterizations based on check-all-that-apply questions with consumers. Food Research International, 97, 215–222. DOI: https://doi.org/10.1016/j.foodres.2017.04.012.
  2. Alcantara, M., & Freitas-Sá, D. D. G. C. (2018). Metodologias sensoriais descritivas mais rápidas e versáteis – uma atualidade na ciência sensorial. Brazilian Journal of Food Technology, 21, e2016179. DOI: https://doi.org/10.1590/1981-6723.17916.
  3. Antúnez, L., Vidal, L., Saldamando, L., Giménez, A., & Ares, G. (2017). Comparison of consumer-based methodologies for sensory characterization: Case study with four sample sets of powdered drinks. Food Quality and Preference, 56, 149–163. DOI: https://doi.org/10.1016/j.foodqual.2016.09.013.
  4. Ares, G., Deliza, R., Barreiro, C., Giménez, A., & Gámbaro, A. (2010). Comparison of two sensory profiling techniques based on consumer perception. Food Quality and Preference, 21(4), 417–426. DOI: https://doi.org/10.1016/j.foodqual.2009.10.006.
  5. Belusso, A. C., Nogueira, B. A., Breda, L. S., & Mitterer-Daltoé, M. L. (2016). Check all that apply (CATA) as an instrument for the development of fish products. Food Science and Technology, 36(2), 275–281. DOI: https://doi.org/10.1590/1678-457X.0026.
  6. Brasil, Ministério da Agricultura, P. E A. (2017). Instrução Normativa n° 1, de 11 de janeiro de 2017. Registro de produtos de origem animal. Diário Oficial da União, p. 4.
  7. Bruzzone, F., Vidal, L., Antúnez, L., Giménez, A., Deliza, R., & Ares, G. (2015). 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, 44, 183–193. DOI: https://doi.org/10.1016/j.foodqual.2015.04.017.
  8. Cadena, R. S., Caimi, D., Jaunarena, I., Lorenzo, I., Vidal, L., Ares, G., … Giménez, A. (2014). Comparison of rapid sensory characterization methodologies for the development of functional yogurts. Food Research International, 64, 446–455. DOI: https://doi.org/10.1016/j.foodres.2014.07.027.
  9. Castura, J. C., Antúnez, L., Giménez, A., & Ares, G. Temporal Check-All-That-Apply (TCATA): A novel dynamic method for characterizing products. (2016). Food Quality and Preference, 47, 79–90. DOI: https://doi.org/10.1016/j.foodqual.2015.06.017.
  10. Costa, G. M., de Paula, M. M., Costa, G. N., Esmerino, E. A., Silva, R., de Freitas, M. Q., … Pimentel, T. C. (2020). Preferred attribute elicitation methodology compared to conventional descriptive analysis: A study using probiotic yogurt sweetened with xylitol and added with prebiotic components. Journal of Sensory Studies, 35(6), e12602. DOI: https://doi.org/10.1111/joss.12602.
  11. Cruz, A. G., Cadena, R. S., Castro, W. F., Esmerino, E. A., Rodrigues, J. B., Gaze, L., … Bolini, H. M. H. (2013). Consumer perception of probiotic yogurt: Performance of check all that apply (CATA), projective mapping, sorting and intensity scale. Food Research International, 54(1), 601–610. DOI: https://doi.org/10.1016/j.foodres.2013.07.056.
  12. Dehlholm, C. (2014). Projective Mapping and Napping. In: Ares, G.; Varela, P. In: Novel techniques in sensory characterization and consumer profiling. [s.l.] Boca Raton: CRC Press, 229-254.
  13. Della Lucia, S. M., Gomes, É. D., Nachtigall, A. M., Cavalcante, J. F. M., & Minim, V. P. R. (2003). Perfil Sensorial de doce de leite pastoso. Revista Instituto de Laticínios "Cândido Tostes". 54, 45-50.
  14. Deneulin, P., Reverdy, C., Rébénaque, P., Danthe, E., & Mulhauser, B. (2018). Evaluation of the Pivot Profile©, a new method to characterize a large variety of a single product: Case study on honeys from around the world. Food Research International, 106, 29–37. DOI: https://doi.org/10.1016/j.foodres.2017.12.044.
  15. Dooley, L., Lee, Y., & Meullenet, JF. (2010). 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, 21(4), 394–401. DOI: https://doi.org/10.1016/j.foodqual.2009.10.002.
  16. Esmerino, E. A., Filho, E. R. T., Carr, B. T., Ferraz, J. P., Silva, H. L. A., Pinto, L. P. F., … Bolini, H. M. A. (2017). Consumer-based product characterization using Pivot Profile, Projective Mapping and Check-all-that-apply (CATA): A comparative case with Greek yogurt samples. Food Research International, 99, 375–384. DOI: https://doi.org/10.1016/j.foodres.2017.06.001.
  17. Fleming, E. E., Ziegler, G. R., & Hayes, J. E. (2015). Check-all-that-apply (CATA), sorting, and polarized sensory positioning (PSP) with astringent stimuli. Food Quality and Preference, 45, 41–49. DOI: https://doi.org/10.1016/j.foodqual.2015.05.004.
  18. Fonseca, F. G. A., Esmerino, E. A., Filho, E. R. T., Ferraz, J. P., da Cruz, A. G., & Bolini, H. M. A. (2016). Novel and successful free comments method for sensory characterization of chocolate ice cream: A comparative study between pivot profile and comment analysis. Journal of Dairy Science, 99(5), 3408–3420. DOI: https://doi.org/10.3168/jds.2015-9982.
  19. Gambaro, A. (2018). Projective techniques to study consumer perception of food. Current Opinion in Food Science, 21, 46–50.
  20. Gaze, L. V., Oliveira, B. R., Ferrao, L. L., Granato, D., Cavalcanti, R. N., Conte Júnior, C. A., … Freita, M. Q. (2015). Preference mapping of dulce de leche commercialized in Brazilian markets. Journal of Dairy Science, 98(3), 1443–1454. DOI: https://doi.org/10.3168/jds.2014-8470.
  21. Giménez, A., Ares, G., & Gámbaro, A. (2008). Consumer reaction to changes in sensory profile of dulce de leche due to lactose hydrolysis. International Dairy Journal, 18(9), 951–955. DOI: https://doi.org/10.1016/j.idairyj.2007.12.007.
  22. Greenacre, M., & Blasius, J. (2006). Multiple Correspondence Analysis and Related Methods. [s.l.] Chapman and Hall/CRC.
  23. Guerrero, L., Claret, A., Verbeke, W., Enderli, G., Biemans, S. Z., Vanhonacker, F., … Hersleth, M. (2010). Perception of traditional food products in six European regions using free word association. Food Quality and Preference, 21(2), 225–233. DOI: https://doi.org/10.1016/j.foodqual.2009.06.003.
  24. Hough, G., Bratchell, N., & Macdougall, D. B. (1992). Sensory Profiling of Dulce de Leche, adairy based confectionary product. Journal of Sensory Studies, 7(3), 157–178. DOI: https://doi.org/10.1111/j.1745-459X.1992.tb00531.x.
  25. Kennedy, J., & Heymann, H. (2009). Projective mapping and descriptive analysis of milk and dark chocolates. Journal of Sensory Studies, 24(2), 220–233. DOI: https://doi.org/10.1111/j.1745-459X.2008.00204.x.
  26. Lazo, O., Claret, A., & Guerrero, L. A. (2016). Comparison of Two Methods for Generating Descriptive Attributes with Trained Assessors: Check-All-That-Apply (CATA) vs. Free Choice Profiling (FCP). Journal of Sensory Studies, 31(2), 163–176. DOI: https://doi.org/10.1111/joss.12202.
  27. Lee, Y., Findlay, C., & Meullenet, JF. (2013). Experimental consideration for the use of check-all-that-apply questions to describe the sensory properties of orange juices. International Journal of Food Science & Technology, 48(1), 215–219. DOI: https://doi.org/10.1111/j.1365-2621.2012.03165.x.
  28. Lelièvre-Desmas, M., Valentin, D., & Chollet, S. (2017). Pivot profile method: What is the influence of the pivot and product space? Food Quality and Preference, 61, 6–14. DOI: https://doi.org/10.1016/j.foodqual.2017.05.002.
  29. Meyners, M., Castura, J. C., & Carr, B. T. (2013). Existing and new approaches for the analysis of CATA data. Food Quality and Preference, 30(2), 309–319. DOI: https://doi.org/10.1016/j.foodqual.2013.06.010.
  30. Molognoni, L., Valese, A. C., Lorenzetti, A., Daguer, H., & De Dea Lindner, J. (2016). Development of a LC–MS/MS method for the simultaneous determination of sorbic acid, natamycin and tylosin in Dulce de leche. Food Chemistry, 211, 748–756. DOI: https://doi.org/10.1016/j.foodchem.2016.05.105.
  31. Moussaoui, K. A., & Varela, P. (2010). Exploring consumer product profiling techniques and their linkage to a quantitative descriptive analysis. Food Quality and Preference, 21(8), 1088–1099. DOI: https://doi.org/10.1016/j.foodqual.2010.09.005.
  32. Murtaza, M. A., Rehman, S. U., Anjum, F. M., & Huma, N. (2013). Descriptive sensory profile of cow and buffalo milk Cheddar cheese prepared using indigenous cultures. Journal of Dairy Science, 96(3), 1380–1386.
  33. Alcaire, F., Antúnez, L., Vidal, L., Zorn, S., Giménez, A., Castura, J. C., & Arés, G. (2017). Comparison of static and dynamic sensory product characterizations based on check-all-that-apply questions with consumers. Food Research International, 97, 215–222. DOI: https://doi.org/10.1016/j.foodres.2017.04.012.
  34. Alcantara, M., & Freitas-Sá, D. D. G. C. (2018). Metodologias sensoriais descritivas mais rápidas e versáteis – uma atualidade na ciência sensorial. Brazilian Journal of Food Technology, 21, e2016179. DOI: https://doi.org/10.1590/1981-6723.17916.
  35. Antúnez, L., Vidal, L., Saldamando, L., Giménez, A., & Ares, G. (2017). Comparison of consumer-based methodologies for sensory characterization: Case study with four sample sets of powdered drinks. Food Quality and Preference, 56, 149–163. DOI: https://doi.org/10.1016/j.foodqual.2016.09.013.
  36. Ares, G., Deliza, R., Barreiro, C., Giménez, A., & Gámbaro, A. (2010). Comparison of two sensory profiling techniques based on consumer perception. Food Quality and Preference, 21(4), 417–426. DOI: https://doi.org/10.1016/j.foodqual.2009.10.006.
  37. Belusso, A. C., Nogueira, B. A., Breda, L. S., & Mitterer-Daltoé, M. L. (2016). Check all that apply (CATA) as an instrument for the development of fish products. Food Science and Technology, 36(2), 275–281. DOI: https://doi.org/10.1590/1678-457X.0026.
  38. Brasil, Ministério da Agricultura, P. E A. (2017). Instrução Normativa n° 1, de 11 de janeiro de 2017. Registro de produtos de origem animal. Diário Oficial da União, p. 4.
  39. Bruzzone, F., Vidal, L., Antúnez, L., Giménez, A., Deliza, R., & Ares, G. (2015). 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, 44, 183–193. DOI: https://doi.org/10.1016/j.foodqual.2015.04.017.
  40. Cadena, R. S., Caimi, D., Jaunarena, I., Lorenzo, I., Vidal, L., Ares, G., … Giménez, A. (2014). Comparison of rapid sensory characterization methodologies for the development of functional yogurts. Food Research International, 64, 446–455. DOI: https://doi.org/10.1016/j.foodres.2014.07.027.
  41. Castura, J. C., Antúnez, L., Giménez, A., & Ares, G. Temporal Check-All-That-Apply (TCATA): A novel dynamic method for characterizing products. (2016). Food Quality and Preference, 47, 79–90. DOI: https://doi.org/10.1016/j.foodqual.2015.06.017.
  42. Costa, G. M., de Paula, M. M., Costa, G. N., Esmerino, E. A., Silva, R., de Freitas, M. Q., … Pimentel, T. C. (2020). Preferred attribute elicitation methodology compared to conventional descriptive analysis: A study using probiotic yogurt sweetened with xylitol and added with prebiotic components. Journal of Sensory Studies, 35(6), e12602. DOI: https://doi.org/10.1111/joss.12602.
  43. Cruz, A. G., Cadena, R. S., Castro, W. F., Esmerino, E. A., Rodrigues, J. B., Gaze, L., … Bolini, H. M. H. (2013). Consumer perception of probiotic yogurt: Performance of check all that apply (CATA), projective mapping, sorting and intensity scale. Food Research International, 54(1), 601–610. DOI: https://doi.org/10.1016/j.foodres.2013.07.056.
  44. Dehlholm, C. (2014). Projective Mapping and Napping. In: Ares, G.; Varela, P. In: Novel techniques in sensory characterization and consumer profiling. [s.l.] Boca Raton: CRC Press, 229-254.
  45. Della Lucia, S. M., Gomes, É. D., Nachtigall, A. M., Cavalcante, J. F. M., & Minim, V. P. R. (2003). Perfil Sensorial de doce de leite pastoso. Revista Instituto de Laticínios "Cândido Tostes". 54, 45-50.
  46. Deneulin, P., Reverdy, C., Rébénaque, P., Danthe, E., & Mulhauser, B. (2018). Evaluation of the Pivot Profile©, a new method to characterize a large variety of a single product: Case study on honeys from around the world. Food Research International, 106, 29–37. DOI: https://doi.org/10.1016/j.foodres.2017.12.044.
  47. Dooley, L., Lee, Y., & Meullenet, JF. (2010). 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, 21(4), 394–401. DOI: https://doi.org/10.1016/j.foodqual.2009.10.002.
  48. Esmerino, E. A., Filho, E. R. T., Carr, B. T., Ferraz, J. P., Silva, H. L. A., Pinto, L. P. F., … Bolini, H. M. A. (2017). Consumer-based product characterization using Pivot Profile, Projective Mapping and Check-all-that-apply (CATA): A comparative case with Greek yogurt samples. Food Research International, 99, 375–384. DOI: https://doi.org/10.1016/j.foodres.2017.06.001.
  49. Fleming, E. E., Ziegler, G. R., & Hayes, J. E. (2015). Check-all-that-apply (CATA), sorting, and polarized sensory positioning (PSP) with astringent stimuli. Food Quality and Preference, 45, 41–49. DOI: https://doi.org/10.1016/j.foodqual.2015.05.004.
  50. Fonseca, F. G. A., Esmerino, E. A., Filho, E. R. T., Ferraz, J. P., da Cruz, A. G., & Bolini, H. M. A. (2016). Novel and successful free comments method for sensory characterization of chocolate ice cream: A comparative study between pivot profile and comment analysis. Journal of Dairy Science, 99(5), 3408–3420. DOI: https://doi.org/10.3168/jds.2015-9982.
  51. Gambaro, A. (2018). Projective techniques to study consumer perception of food. Current Opinion in Food Science, 21, 46–50.
  52. Gaze, L. V., Oliveira, B. R., Ferrao, L. L., Granato, D., Cavalcanti, R. N., Conte Júnior, C. A., … Freita, M. Q. (2015). Preference mapping of dulce de leche commercialized in Brazilian markets. Journal of Dairy Science, 98(3), 1443–1454. DOI: https://doi.org/10.3168/jds.2014-8470.
  53. Giménez, A., Ares, G., & Gámbaro, A. (2008). Consumer reaction to changes in sensory profile of dulce de leche due to lactose hydrolysis. International Dairy Journal, 18(9), 951–955. DOI: https://doi.org/10.1016/j.idairyj.2007.12.007.
  54. Greenacre, M., & Blasius, J. (2006). Multiple Correspondence Analysis and Related Methods. [s.l.] Chapman and Hall/CRC.
  55. Guerrero, L., Claret, A., Verbeke, W., Enderli, G., Biemans, S. Z., Vanhonacker, F., … Hersleth, M. (2010). Perception of traditional food products in six European regions using free word association. Food Quality and Preference, 21(2), 225–233. DOI: https://doi.org/10.1016/j.foodqual.2009.06.003.
  56. Hough, G., Bratchell, N., & Macdougall, D. B. (1992). Sensory Profiling of Dulce de Leche, adairy based confectionary product. Journal of Sensory Studies, 7(3), 157–178. DOI: https://doi.org/10.1111/j.1745-459X.1992.tb00531.x.
  57. Kennedy, J., & Heymann, H. (2009). Projective mapping and descriptive analysis of milk and dark chocolates. Journal of Sensory Studies, 24(2), 220–233. DOI: https://doi.org/10.1111/j.1745-459X.2008.00204.x.
  58. Lazo, O., Claret, A., & Guerrero, L. A. (2016). Comparison of Two Methods for Generating Descriptive Attributes with Trained Assessors: Check-All-That-Apply (CATA) vs. Free Choice Profiling (FCP). Journal of Sensory Studies, 31(2), 163–176. DOI: https://doi.org/10.1111/joss.12202.
  59. Lee, Y., Findlay, C., & Meullenet, JF. (2013). Experimental consideration for the use of check-all-that-apply questions to describe the sensory properties of orange juices. International Journal of Food Science & Technology, 48(1), 215–219. DOI: https://doi.org/10.1111/j.1365-2621.2012.03165.x.
  60. Lelièvre-Desmas, M., Valentin, D., & Chollet, S. (2017). Pivot profile method: What is the influence of the pivot and product space? Food Quality and Preference, 61, 6–14. DOI: https://doi.org/10.1016/j.foodqual.2017.05.002.
  61. Meyners, M., Castura, J. C., & Carr, B. T. (2013). Existing and new approaches for the analysis of CATA data. Food Quality and Preference, 30(2), 309–319. DOI: https://doi.org/10.1016/j.foodqual.2013.06.010.
  62. Molognoni, L., Valese, A. C., Lorenzetti, A., Daguer, H., & De Dea Lindner, J. (2016). Development of a LC–MS/MS method for the simultaneous determination of sorbic acid, natamycin and tylosin in Dulce de leche. Food Chemistry, 211, 748–756. DOI: https://doi.org/10.1016/j.foodchem.2016.05.105.
  63. Moussaoui, K. A., & Varela, P. (2010). Exploring consumer product profiling techniques and their linkage to a quantitative descriptive analysis. Food Quality and Preference, 21(8), 1088–1099. DOI: https://doi.org/10.1016/j.foodqual.2010.09.005.
  64. Murtaza, M. A., Rehman, S. U., Anjum, F. M., & Huma, N. (2013). Descriptive sensory profile of cow and buffalo milk Cheddar cheese prepared using indigenous cultures. Journal of Dairy Science, 96(3), 1380–1386.
  65. Pagès, J. (2005). Collection and analysis of perceived product inter-distances using multiple factor analysis: Application to the study of 10 white wines from the Loire Valley. Food Quality and Preference, 16(7), 642–649. https://doi.org/10.1016/j.foodqual.2005.01.006.
  66. Pearson, W., Schmidtke, L., Francis, I. L., & Blackman, J. W. (2020). An investigation of the Pivot© Profile sensory analysis method using wine experts: Comparison with descriptive analysis and results from two expert panels. Food Quality and Preference, 83, 103858. DOI: https://doi.org/10.1016/j.foodqual.2019.103858.
  67. Penci, M. C., & Marín, M. A. (2016). Dulce de Leche: Technology, Quality, and Consumer Aspects of the Traditional Milk Caramel of South America. In: Kristbergsson K., Oliveira J. Traditional Foods. Integrating Food Science and Engineering Knowledge Into the Food Chain, 10. Springer, Boston, MA.
  68. Queiroz, V. A. V., Correia, V. T. V., de Menezes, C. B., Miguel, R. A., Conceição, R. R. P., Paiva, C. L., & Figueiredo, J. E. F. (2020). Retention of phenolic compounds and acceptability of gluten-free churros made with tannin or tannin-free sorghum flour. Pesquisa Agropecuária Brasileira, 55, e02288.
  69. Reinbach, H. C., Giacalone, D., Ribeiro, L. M., Bredie, W. L. P., & Frost, M. B. (2014). Comparison of three sensory profiling methods based on consumer perception: CATA, CATA with intensity and Napping®. Food Quality and Preference, 32, 160–166. DOI: https://doi.org/10.1016/j.foodqual.2013.02.004.
  70. Silva, R., Rocha, R. S., Guimarães, J. T., Balthazar, C. F., Scudino, H., Ramos, G. L. P. A., …, Esmerino, E. A. (2020). Dulce de leche submitted to ohmic heating treatment: Consumer sensory profile using preferred attribute elicitation (PAE) and temporal check-all-that-apply (TCATA). Food Research International, 134, 109217. https://doi.org/10.1016/j.foodres.2020.109217.
  71. Sokal, R. R., & Rohlf, F. J. (1962). The comparison of dendrograms by objective methods. Taxon, 11(2), 33–40.
  72. Stone, H.; Bleibaum, R.; Thomas, H. (2012). Sensory evaluation practices. 4th Editio ed. San Diego: [s.n.].
  73. Szymandera-Buszka, K., Waszkowiak, K., Jędrusek-Golińska, A., & Hes, M. (2020). Sensory Analysis in Assessing the Possibility of Using Ethanol Extracts of Spices to Develop New Meat Products. Foods, 9(2), 209.
  74. Tahir, H. E., Xiaobo, Z., Xiaowei, H., Jiyong, S., & Mariod, A. A. (2016). Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques. Food Chemistry, 206, 37–43. DOI: https://doi.org/10.1016/j.foodchem.2016.03.032.
  75. Tarancón, P., Salvador, A., Sanz, T., Fiszman, S., & Tárrega, A. Use of healthier fats in biscuits (olive and sunflower oil): changing sensory features and their relation with consumers’ liking. Food Research International, 69, 91–96. https://doi.org/10.1016/j.foodres.2014.12.013.
  76. Thuillier, B. (2007). Rôle du CO2 dans l’appréciation organoleptique des champagnes – Expérimentation et apports méthodologiques. (These de Docteur ) - Université de Reims.
  77. Thuillier, B., Valentin, D., Marchal, R., & Dacremont, C. (2015). Pivot© profile: A new descriptive method based on free description. Food Quality and Preference, 42, 66–77. DOI: https://doi.org/10.1016/j.foodqual.2015.01.012.
  78. Valentin, D., Chollet, S., Lelièvre, M., & Abdi, H. (2012). Quick and dirty but still pretty good: a review of new descriptive methods in food science. International Journal of Food Science & Technology, 47(8), 1563–1578. DOI: https://doi.org/10.1111/j.1365-2621.2012.03022.x.
  79. 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), 893–908. DOI: https://doi.org/10.1016/j.foodres.2012.06.037.
  80. Vicente, E., Varela, P., Saldamando, L., & Ares, G. (2014). Evaluation of the sensory characteristics of strawberry cultivars throughout the harvest season using projective mapping. Journal of the Science of Food and Agriculture, 94(3). DOI: https://doi.org/10.1002/jsfa.6307.
  81. Vicente, E., Ares, G., Rodríguez, G., Varela, P., Bologna, F., & Lado, J. (2017). Selection of promising sweet potato clones using projective mapping. Journal of the Science of Food and Agriculture, 97(1), 158–164. DOI: https://doi.org/10.1002/jsfa.7704.
  82. Vidal, L., Cadena, R. S., Antúnez, L., Giménez, A., Varela, P., & Ares, G. (2014). Stability of sample configurations from projective mapping: How many consumers are necessary? Food Quality and Preference, 34, 79–87. DOI: https://doi.org/10.1016/j.foodqual.2013.12.006.

Como Citar

Ramos, A. L. C. C., Correia, V. T. da V., Ortiz, P. A. M., D'Angelis, D. F., Dutra, V. L. M. ., & Fante, C. A. . (2022). Comparison of quick descriptive sensory methods in the evaluation of dulce de leche. Scientific Electronic Archives, 15(7). https://doi.org/10.36560/15720221625