Abstract：
:In recent years, much analysis has been carried out regarding the chemical compositions of nonalcoholic and alcoholic beverages. However, no study has ever considered the compositional pitfalls inherent in such studies, which may lead to arbitrary results. Two approaches were compared in this paper, compositional data analysis (CoDa) and classical statistical analyses, to demonstrate (1) how aging affects beer and (2) how the results vary depending on the applied approach. Exemplarily, chemical compounds of 43 beer samples were analyzed. Our work has led us to obtain different results when the correlation analysis and principal component analysis were conducted on the unmodified-, log-transformed-, or closed-data in contrary to the analyses of log-ratio coordinates. The outcome of the latter provided better separation between aged and fresh beer samples and also easier interpretability. These results lead us to advise the usage of CoDa methods for the analyses of chemical compositions of beverages.
journal_name
Food Chemjournal_title
Food chemistryauthors
Templ M,Templ Bdoi
10.1016/j.foodchem.2020.126755subject
Has Abstractpub_date
2020-04-06 00:00:00pages
126755eissn
0308-8146issn
1873-7072pii
S0308-8146(20)30617-8journal_volume
325pub_type
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