%0 Journal Article
%T Application of Principal Component Analysis as Properties and Sensory Assessment Tool for Legume Milk Chocolates
%A Preethini Selvaraj
%A Arrivukkarasan Sanjeevirayar
%A Anhuradha Shanmugam
%J American Journal of Computational Mathematics
%P 136-152
%@ 2161-1211
%D 2023
%I Scientific Research Publishing
%R 10.4236/ajcm.2023.131006
%X Principal component analysis (PCA) was employed to examine the effect of
nutritional and bioactive compounds of legume milk chocolate as well</span></span><span><span><span style=\"font-family:&quot;\"> </span></span></span><span><span><span style=\"font-family:&quot;\">as the
sensory to document the extend of variations and </span></span></span><span><span><span style=\"font-family:&quot;\">their</span></span></span><span><span><span style=\"font-family:&quot;\"> significance with plant sources. PCA identified eight significant principle
components, that reduce the size of the variables into one principal component
in physiochemical analysis interpreting 73.5% of the total variability with/and
78.6% of total variability explained in sensory evaluation. Score plot
indicates that Double Bean milk chocolate in-corporated with MOL and CML in
nutritional profile have high positive correlations. In nutritional evaluation,
carbohydrates and fat content shows negative/minimal correlations whereas no
negative correlations were found in sensory evaluation which implies every
sensorial variable had high correlation with each other.
%K Principal Component Analysis
%K Legume Milk Chocolate
%K Bioactive Plant Source
%K Nutritional and Sensory Properties
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=123816