#Xlstat principal component analysis software#

UM: unmarinated moose, UB: unmarinated beef, MM: marinated moose with unfiltered beer based marinate 1, MS: marinated moose with unfiltered beer based marinate 2, BM: marinated beef with unfiltered beer based marinate 1 BS: marinated beef with unfiltered beer based marinate 2. PCA biplot performed with the abundances of the volatile terpenes and thiols detected in the headspace of unmarinated and marinated grilled moose and beef, together with the scores of sensory attributes as supplementary quantitative variables. Grilled ruminant meat Principal component analysis SPME-GC/MS Sensory analysis Unfiltered beer-based marinades Volatile metabolites. PCA could be applied to explore relationships between volatile compounds and sensory attributes in different food systems.PCA clustered marinated and unmarinated meats based on the presence and abundances of volatile terpenes, thiols and consumer sensory attribute scores.XLSTAT PCA output successfully reduced the number of variables into 2 components that explained 90.47% of the total variation of the data set.PCA was conducted to determine the correlations between the abundances of volatile terpenes and thiols and sensory attribute scores in marinated grilled meats, as well as to analyze if there was any clustering based on the type of meat and marination treatments employed. As a case of study, multivariate analysis is used to study the effects of unfiltered beer-based marination on the volatile terpenes and thiols, and sensory attributes of grilled ruminant meats.

#Xlstat principal component analysis software#

Interests in XLSTAT as statistical software program of choice for routine multivariate statistics has been growing due in part to its compatibility with Microsoft Excel data format. Principal component analysis (PCA) is an unsupervised multivariate analysis technique that simplifies the complexity of data by transforming them in a few dimensions showing their trends and correlations. Multivariate statistics is a tool for examining the relationship of multiple variables simultaneously.