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https://doi.org/10.1007/s11694-018-9814-4

has been cited by the following article:

• 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.