Preference mapping of dulce de leche commercialized in Brazilian markets

J Dairy Sci. 2015 Mar;98(3):1443-54. doi: 10.3168/jds.2014-8470. Epub 2014 Dec 31.

Abstract

Dulce de leche samples available in the Brazilian market were submitted to sensory profiling by quantitative descriptive analysis and acceptance test, as well sensory evaluation using the just-about-right scale and purchase intent. External preference mapping and the ideal sensory characteristics of dulce de leche were determined. The results were also evaluated by principal component analysis, hierarchical cluster analysis, partial least squares regression, artificial neural networks, and logistic regression. Overall, significant product acceptance was related to intermediate scores of the sensory attributes in the descriptive test, and this trend was observed even after consumer segmentation. The results obtained by sensometric techniques showed that optimizing an ideal dulce de leche from the sensory standpoint is a multidimensional process, with necessary adjustments on the appearance, aroma, taste, and texture attributes of the product for better consumer acceptance and purchase. The optimum dulce de leche was characterized by high scores for the attributes sweet taste, caramel taste, brightness, color, and caramel aroma in accordance with the preference mapping findings. In industrial terms, this means changing the parameters used in the thermal treatment and quantitative changes in the ingredients used in formulations.

Keywords: dulce de leche; optimization; sensometric technique.

MeSH terms

  • Brazil
  • Candy
  • Carbohydrates
  • Choice Behavior*
  • Cluster Analysis
  • Color
  • Consumer Behavior*
  • Dairy Products*
  • Food Preferences*
  • Humans
  • Least-Squares Analysis
  • Logistic Models
  • Odorants
  • Principal Component Analysis
  • Smell
  • Taste

Substances

  • Carbohydrates
  • caramel coloring