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|Título: ||Chemical composition, sensory properties, provenance, and bioactivity of fruit juices as assessed by chemometrics: a critical review and guideline|
|Autor(es): ||Zielinski, Acácio A. F.|
Haminiuk, Charles W. I.
Nunes, Cleiton A.
Ruth, Saskia M. van
|Publicador: ||Institute of Food Technologists|
|Data de publicação: ||17-Jan-2014|
|Referência: ||ZIELINSKI, A. A. F. et al. Chemical composition, sensory properties, provenance, and bioactivity of fruit juices as assessed by chemometrics: a critical review and guideline. Comprehensive Reviews in Food Science and Food Safety, [S. l.], v. 13, n. 3, p. 300-316, May 2014.|
|Abstract: ||The use of univariate, bivariate, and multivariate statistical techniques, such as analysis of variance, multiple
comparisons of means, and linear correlations, has spread widely in the area of Food Science and Technology. However,
the use of supervised and unsupervised statistical techniques (chemometrics) in order to analyze and model experimental
data from physicochemical, sensory, metabolomics, quality control, nutritional, microbiological, and chemical assays in
food research has gained more space. Therefore, we present here a manuscript with theoretical details, a critical analysis
of published work, and a guideline for the reader to check and propose mathematical models of experimental results
using the most promising supervised and unsupervised multivariate statistical techniques, namely: principal component
analysis, hierarchical cluster analysis, linear discriminant analysis, partial least square regression,
-nearest neighbors, and
soft independent modeling of class analogy. In addition, the overall features, advantages, and limitations of such statistical
methods are presented and discussed. Published examples are focused on sensory, chemical, and antioxidant activity of a
wide range of fruit juices consumed worldwide.|
|Aparece nas coleções: ||DCA - Artigos publicados em periódicos|
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