Abstract
The original methods proposed by Ledyard R. Tucker during the 1960s present the rotational freedom problem, making the interpretation of their results rather difficult to be carried out. Aiming to make the multi-way data analysis more acceptable, this work suggests a methodology for extracting meaningful information from the data set. This methodology is based on the decomposition of data set in three-way blocks by using Tucker models. With the aim of keeping in one block similar information about the data properties, a decomposition based on a constrained Tucker model was used, where the core array has some of its elements fixed to zero. This methodology is successfully applied to a data set formed by physical and physicochemical properties of starches of four cassava cultivars, harvested at different ages during the period usually taken for harvest of industrial uses.
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