title: Applying parallel factor analysis and Tucker-3 methods on sensory and instrumental data to establish preference maps: case study on sweet corn varieties.
abstract: BACKGROUND
  Traditional internal and external preference mapping methods are based on principal component analysis (PCA). However, parallel factor analysis (PARAFAC) and Tucker-3 methods could be a better choice. To evaluate the methods, preference maps of sweet corn varieties will be introduced.
  
  
  RESULTS
  A preference map of eight sweet corn varieties was established using PARAFAC and Tucker-3 methods. Instrumental data were also integrated into the maps. The triplot created by the PARAFAC model explains better how odour is separated from texture or appearance, and how some varieties are separated from others.
  
  
  CONCLUSIONS
  Internal and external preference maps were created using parallel factor analysis (PARAFAC) and Tucker-3 models employing both sensory (trained panel and consumers) and instrumental parameters simultaneously. Triplots of the applied three-way models have a competitive advantage compared to the traditional biplots of the PCA-based external preference maps. The solution of PARAFAC and Tucker-3 is very similar regarding the interpretation of the first and third factors. The main difference is due to the second factor as it differentiated the attributes better. Consumers who prefer 'super sweet' varieties (they place great emphasis especially on taste) are much younger and have significantly higher incomes, and buy sweet corn products rarely (once a month). Consumers who consume sweet corn products mainly because of their texture and appearance are significantly older and include a higher ratio of men.
authors.affiliation: Sensory Laboratory, Faculty of Food Science, Corvinus University of Budapest, H-1118, Budapest, Villányi út, 29-43, Hungary.
authors.forename: Attila
authors.initials: A
authors.lastname: Gere
authors.forename: Viktor
authors.initials: V
authors.lastname: Losó
authors.forename: Annamária
authors.initials: A
authors.lastname: Györey
authors.forename: Sándor
authors.initials: S
authors.lastname: Kovács
authors.forename: László
authors.initials: L
authors.lastname: Huzsvai
authors.forename: András
authors.initials: A
authors.lastname: Nábrádi
authors.forename: Zoltán
authors.initials: Z
authors.lastname: Kókai
authors.forename: László
authors.initials: L
authors.lastname: Sipos
mesh_terms: D000328:Adult; D003258:Consumer Behavior / Q000706:statistics & numerical data*; D005163:Factor Analysis, Statistical; D005260:Female; D005518:Food Preferences; D006801:Humans; D008297:Male; D025341:Principal Component Analysis; D012677:Sensation; D013045:Species Specificity; D013649:Taste; D003313:Zea mays
keywords: Tucker-3; parallel factor analysis; preference mapping algorithm; sensory analysis; sweet corn