TITLE:
Application of Principal Component Analysis as Properties and Sensory Assessment Tool for Legume Milk Chocolates
AUTHORS:
Preethini Selvaraj, Arrivukkarasan Sanjeevirayar, Anhuradha Shanmugam
KEYWORDS:
Principal Component Analysis, Legume Milk Chocolate, Bioactive Plant Source, Nutritional and Sensory Properties
JOURNAL NAME:
American Journal of Computational Mathematics,
Vol.13 No.1,
March
23,
2023
ABSTRACT: Principal component analysis (PCA) was employed to examine the effect of
nutritional and bioactive compounds of legume milk chocolate as well as the
sensory to document the extend of variations and their 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.