Triple Concentrated Tomato Paste: Discrimination between Italian and Chinese Products (Articolo in rivista)

Type
Label
  • Triple Concentrated Tomato Paste: Discrimination between Italian and Chinese Products (Articolo in rivista) (literal)
Anno
  • 2009-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1021/jf804004z (literal)
Alternative label
  • Consonni roberto; Cagliani laura ruth; Stocchero matteo; Porretta sebastiano (2009)
    Triple Concentrated Tomato Paste: Discrimination between Italian and Chinese Products
    in Journal of agricultural and food chemistry
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Consonni roberto; Cagliani laura ruth; Stocchero matteo; Porretta sebastiano (literal)
Pagina inizio
  • 4506 (literal)
Pagina fine
  • 4513 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://pubs.acs.org/doi/abs/10.1021/jf804004z (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 57 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 11 (literal)
Note
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Consonni roberto, Istituto per lo Studio delle Macromolecole Cagliani laura ruth, Istituto per lo Studio delle Macromolecole Stocchero matteo, S-In soluzioni informatiche Porretta sebastiano, Staz Sperimentale Ind Conserve Alimentari (literal)
Titolo
  • Triple Concentrated Tomato Paste: Discrimination between Italian and Chinese Products (literal)
Abstract
  • (1)H NMR spectroscopy was applied to discriminate triple concentrated tomato paste coming from two different countries. Notwithstanding different tomato cultivars and ripening stages employed to obtain the final product, significant discrimination between Italian and Chinese samples was obtained by combining NMR data and principal component analysis. Supervised orthogonal projection to latent structure discriminant analysis (OPLS-DA) technique was used to build robust classification models, while S-plot was employed to identify statistically significant variables responsible for class separation. Citrate content resulted in being the most relevant chemical compound for Chinese and Italian sample differentiation. In order to highlight other compounds able to contribute to sample differentiation, citrate content was excluded, and a new classification model was built. This latter model indicated aspartate, glutamine, and sugars as important variables in sample differentiation. (literal)
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