Olive oil characteristics of eleven cultivars produced in a high-density grove in Valladolid province (Spain)

• Type: Article in International Scientific Journal
• Date: 2021

Authors

Rodrigues, N (Author) Other; Susana Casal (Author) FFUP; Pinho, T (Author) Other; Cruz, R (Author) Other; Baptista, P (Author) Other; Martin, H (Author) Other; Asensio S Manzanera, MC (Author) Other; Peres, AM (Author) Other; Pereira, JA (Author) Other

Journal

The Journal is awaiting validation by the Administrative Services.

Title: EUROPEAN FOOD RESEARCH AND TECHNOLOGY

Vol. 247

Pages: 3113-3122

ISSN: 1438-2377

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-00V-FCV

DOI: 10.1007/s00217-021-03858-z

Abstract (EN): The olive oil composition of eleven cultivars (cvs. Arbequina, Arbosana, Arroniz, Cornicabra, Frantoio, Hojiblanca, Manzanilla, Picual, Picudo, Redondilla and Royuela) cultivated in a high-density olive grove located in a non-traditional producing region (Valladolid, Spain) was studied during four consecutive crop seasons. The results showed that the 122 monovarietal olive oils studied could be classified as extra virgin oils, according to the quality parameters. Furthermore, the olive cultivar had a marked effect on the chemical composition and antioxidant activity. In general, olive oils from cvs. Picual and Cornicabra showed the highest total phenolic contents, oxidative stability, and tocopherols contents, whereas the worst results for oxidative stability were observed for cv. Redondilla olive oils, probably associated to the lowest contents of phenolics and tocopherols and the highest amounts of polyunsaturated fatty acids. Finally, it was found that, despite the different crop years evaluated, the quality-chemical profiles could be used to successfully discriminate the monovarietal oils under study (linear discriminant analysis sensitivities: 92 +/- 5% for the repeated K-fold cross-validation), using the data of 15 non-redundant variables identified by the simulated annealing variable selection algorithm.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10