DEVELOPMENT OF A SENSORY TEXTURE PROFILE OF COOKED POTATOES BY MULTIVARIATE DATA-ANALYSIS

A sensory texture profile of cooked potatoes (Solanum tuberosum) was d eveloped through two training periods in 1995 and 1997 Training time n ecessary to obtain a reliable sensory panel in assessing texture attri butes was studied by the use of univariate and multivariate data analy sis. The panel was interviewed and introduced to the Texture Profile M ethod. A list of texture attributes, ranging from non oral terms to te rm evaluated after the first bite and the following mastications, was developed resulting in 14 texture attributes. Analysis of variance (AN OVA), discriminant partial least squares regression (DPLSR) and princi pal component analysis (PCA) was used to reduce the texture profile to 8 reliable sensory attributes covering the geometrical (reflection, m ealiness, graininess), mechanical (firmness, hardness, springiness che winess) and moistness characteristics. These variables explained 89% a nd 86% of the total variance in 1995 and 1997 respectively. Relevant c riteria for studying panel performance are discussed. Training for mor e than one day did not significantly improve panel performance. Geomet rical attributes as well as moistness were found easier to evaluate th an the mechanical attributes.