Application of Principal Component Analysis as Properties and Sensory Assessment Tool for Legume Milk Chocolates

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.

Sensory properties of selected biofortified common bean (Phaseolus vulgaris) varieties grown in Burundi

“…These results are close to those from an earlier study assessing flavor and texture qualities in a dry yellow bean population that indicated an overall variation of 63% for three of its principal components (Bassett et al, 2021). Results from a study by Selvaraj et al (2023) on the sensory attributes of milk chocolates containing common bean and chickpea powder had a total of eight significant principal components and showed a higher variation of 78.6% in the tested data set. Results from another study by Oh et al (2022) had two significant principal components and recorded a variation of 89.6% of descriptive sensory data for different types of beans (black, kidney beans, mung beans, soybeans, red beans, and green kernel black beans) and chickpeas cultivated and consumed in TA B L E 5 Varimax rotated principal component factor loading for sensory attributes of selected common bean varieties.…”

“…PC1 was strongly correlated to stickiness, broken grains, juiciness, beany aroma, and chewability, thus primarily measuring the enhancement of sensory properties in the various common bean varieties (Table 5 ). In a different study assessing the sensory attributes of milk chocolate containing different levels of bean and chickpea powder, PC1 was positively correlated to appearance, texture, aroma, and mouthfeel (Selvaraj et al., 2023 ), an equivalence of broken grains classified under appearance, beany aroma and juiciness, stickiness, and chewability categorized under texture(mouthfeel) in this study. PC1 was also negatively correlated with astringency, metallic aroma, peeling of skin, particles, and hardness.…”

“…Results from a study by Selvaraj et al. ( 2023 ) on the sensory attributes of milk chocolates containing common bean and chickpea powder had a total of eight significant principal components and showed a higher variation of 78.6% in the tested data set. Results from another study by Oh et al.…”

“…Principal component analysis (PCA) was also employed to measure descriptive sensory attributes, according to Selvaraj et al. ( 2023 ). The main intention of using PCA was to ensure data compression and to examine the number of components required for describing the superior part of variation among the cooked dry bean varieties with less information loss (Demšar et al., 2013 ).…”

“…Principal component analysis (PCA) was also employed to measure descriptive sensory attributes, according to Selvaraj et al (2023).…”