Multiple regression models and Computer Vision Systems to predict antioxidant activity and total phenols in pigmented carrots (Articolo in rivista)

Type
Label
  • Multiple regression models and Computer Vision Systems to predict antioxidant activity and total phenols in pigmented carrots (Articolo in rivista) (literal)
Anno
  • 2013-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1016/j.jfoodeng.2013.02.005 (literal)
Alternative label
  • Bernardo Pace, Maria Cefola, Floriana Renna, Massimiliano Renna, Francesco Serio, Giovanni Attolico (2013)
    Multiple regression models and Computer Vision Systems to predict antioxidant activity and total phenols in pigmented carrots
    in Journal of food engineering; Elsevier, Amsterdam (Paesi Bassi)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Bernardo Pace, Maria Cefola, Floriana Renna, Massimiliano Renna, Francesco Serio, Giovanni Attolico (literal)
Pagina inizio
  • 74 (literal)
Pagina fine
  • 81 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 117 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 1 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ISPA - CNR, ISSIA - CNR (literal)
Titolo
  • Multiple regression models and Computer Vision Systems to predict antioxidant activity and total phenols in pigmented carrots (literal)
Abstract
  • The relationships between colour parameters obtained by a Computer Vision System (CVS) and both antioxidant activity (AA) and total phenol contents (TP) on coloured carrots were expressed as multivariate models obtained by multiple linear regression. The AA and TP predicted by the proposed models showed a good correlation with the real AA (R2 = 0.97, P ? 0.001) and TP (R2 = 0.94, P ? 0.001) measurements on the data set including internal and external parts of carrots. The predictions on the data set including only the internal (unevenly pigmented) parts of the carrots exhibited lower determination coefficients (R2 = 0.93 for AA and R2 = 0.86 for TP, P ? 0.001). The effectiveness of the models was checked also on the colour information provided by a colorimeter whose measures proved to be more sensitive to the uneven pigmentation of the carrots. Finally, the proposed models were able to successfully estimate the AA and the TP contents of pigmented carrots when applied to colours measured by the CVS. (literal)
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