XLSTAT TUTORIAL SOFTWARE
XLSTAT is a statistical software that can be employed to perform multivariate analysis of complex data sets. Principal component analysis (PCA) is a multivariate statistical technique applied to reduce the number of variables (i.e., volatile metabolites) into a few uncorrelated variables named principal components (or factors) based on patterns of correlation of the original variables. The volatile profile and sensory test analyses of the grilled meat were complex data sets (more than 100 volatile compounds were identified, and 9 sensory attributes were scored in each sample) requiring the use of multivariate statistics for their analysis. In a previous study, moose and beef steaks were marinated with two novel formulations of unfiltered beer-based marinades, and grilled. This process adds new compounds, which could have antioxidant properties and flavours, improving the sensory characteristics and preserving the meat nutritional quality. Meat marination is the process of incubating the meat into a seasoned liquid base before cooking. The nutritional and sensory quality (e.g., appearance, texture, aroma, and flavor) are 2 key factors which determine consumers meat choice. Meat is an excellent source of nutrients including proteins, dietary fatty acids, essential minerals, and vitamins. XLSTAT statistical and data analysis solution. “Novel unfiltered beer-based marinades to improve the nutritional quality, safety, and sensory perception of grilled ruminant meats” Food chemistry 302 (2020): 125326. The use of XLSTAT in conducting principal component analysis (PCA) when evaluating the relationships between sensory and quality attributes in grilled foods 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. 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.
0 kommentar(er)
