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Logit modeling for classification of monocultivar olive oils from southwest Spain: A preliminary study
Author(s) -
Sayago Ana,
de la Luz Pizarro María,
Beltrán María,
Beltrán Rafael
Publication year - 2011
Publication title -
european journal of lipid science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.614
H-Index - 94
eISSN - 1438-9312
pISSN - 1438-7697
DOI - 10.1002/ejlt.201100054
Subject(s) - peroxide value , olive oil , cultivar , mathematics , food science , logistic regression , regression analysis , horticulture , statistics , chemistry , biology
A characterization study of the main olive oil cultivars of southwest Spain (Picual, Arbequina, and Verdial) has been performed in order to establish logistic regression models. Several quality characteristics (free acidity, peroxide value, K 232 , K 270 , oxidative stability index) and chemical data (fatty acids, sterols, erythrodiol–uvaol composition) were measured. Logit regressions were used to evaluate the correlation of the parameters and to create models that allow saving costs on identifying oils as Arbequina, Picual, or Verdial type. Multiple logit regression models were developed: one for Arbequina, three models for Picual, and two models for Verdial cultivar, allowing in this way to minimize the cost for classifying oil samples. Practical application: The olive oil marketing is increasingly focused on the chemical differentiation and characterization of the product because the chemical composition of these virgin oils is responsible for their valuable sensory and nutritional properties. Here we present a characterization study (quality characteristics and chemical data) from the main olive oil cultivars of southwest Spain, Picual, Arbequina, and Verdial, as a first step for the traceability of these three types of monocultivar virgin olive oils. The results may be used as a training to create models for other olive oil cultivars.