Descriptive sensory profiling of thandai using principal component analysis
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Authors
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Rekha Chawla
Assistant Professor (Dairy Technology)
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Manpinder Kaur
M.Tech student
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S Sivakumar
Deptt. of Dairy Technology
Asstt. Scientist (DT)
Keywords:
Milk beverage, 100-point scale, Principal component analysis, Quantitative descriptive analysis.Abstract
Thandai being nutrient crammed pabulum is relished as a traditional milk-based beverage in India. Being indigenous drink, international and national level research work and the literature pertaining to the same is not available. Thus, the present study was undertaken to investigate and characterize the sensory attributes of commercially available thandai using Quantitative Descriptive Analysis (QDA) and Principal Component Analysis (PCA). QDA revealed statistically significant (p<0.05) difference in sensory attributes of thandai amongst the market samples. PCA identified three significant principal components that accounted for 93.01 per cent of the variation in the sensory data. Correlation matrix revealed many linear relationships between independent terms of sensory attributes.
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