2014
DOI: 10.1016/j.foodres.2014.07.003
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Discrimination of Brazilian artisanal and inspected pork sausages: Application of unsupervised, linear and non-linear supervised chemometric methods

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Cited by 56 publications
(35 citation statements)
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“…4). The sensory data was also subjected to principal component analysis in order to detect if there was a pattern in the sensory data (Matera et al, 2014).
Fig.
…”
Section: Resultsmentioning
confidence: 99%
“…4). The sensory data was also subjected to principal component analysis in order to detect if there was a pattern in the sensory data (Matera et al, 2014).
Fig.
…”
Section: Resultsmentioning
confidence: 99%
“…Significance level was considered at P < 0.05. Chemometric methods such as hierarchical cluster analysis (HCA) and principal component analysis (PCA) were employed to discriminate yogurts with different culture and prebiotic combinations (Matera et al, 2014). The HCA categorized different yogurts into clusters based on their similarities by applying the squared Euclidean distance and Ward linkage methods to the standardized data set (z-scores).…”
Section: Statistical Analysesmentioning
confidence: 99%
“…Machine learning is thus closely related to the fields of statistics and data mining. Partial least squares (PLS) is long history and widely used method in multivariate analysis and machine learning, being used in several fields as food science (Cadena et al, 2012;Cruz et al, 2013;Matera et al, 2014) and others (Krishnan et al, 2011;Ma et al, 2014). LS-SVM is a relatively new but effective machine learning method that has been applied successfully in some fields.…”
Section: Introductionmentioning
confidence: 99%