Application of principal component analysis (PCA) method to study the qualitative and quantitative parameters of muffin with reduced sugar containing maltodextrin and traditional ghavoot
2023
nafiseh zolfaghari | Esmaeil Ataye salehi | Zahra Sheikholeslami
In this study, the principal component analysis method was used to evaluate the relationships between quantitative and qualitative parameters of muffin with reduced sugar. The principal component analysis (PCA) method is a useful tool for interpreting and finding relationships in a set of parameters with various dimensions and characteristics in each observation. This tool provides useful help in increasing the interpretability of data and multidimensional visualization of the relationship between them. In order to replace sugar, a formulation based on three levels of maltodextrin (0, 25 and 50%) and four levels of ghavoot (0, 3, 6 and 10%) was used in a completely random design. Based on the study of the principal component analysis plot, it was determined that the relationships between the studied parameters are influenced by changes in the sugar substitute formulation. Based on this, new relationships between the studied parameters on muffins are formed by changing the level and type of sugar substitute composition. The evaluation of the change in the relationship between the parameters under the influence of the replacement of maltodextrin and ghavoot in the muffin formulation with reduced sugar shows the changes made in the structural substrates and the influence of a set of parameters on each other under the applied treatment. The results of this research show the efficiency and importance of using data mining methods to create an understanding of the relationships between quantitative and qualitative parameters of baking products with changes in formulation.
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