Influence of harvest method and period on olive oil composition: An NMR and statistical study

Marco D'Imperio, Marco Gobbino, Antonio Picanza, Simona Costanzo, Anna Della Corte, Luisa Mannina

Research output: Contribution to journalArticlepeer-review

Abstract

The influence of harvest period and harvest method on olive oil composition was investigated by nuclear magnetic resonance (NMR) spectroscopy and by some quality parameters such as free acidity, peroxide value, and UV spectrophotometric indices. This work focuses on two secondary factors (harvest period and harvest method) and investigated their interactions with primary (genetic and pedoclimatic) and secondary (agronomic practices and technological procedures) factors. To avoid misinterpretation, the general linear model analysis (GLM) was used to adjust the result obtained from the analysis of variance (ANOVA). In this way, the effect of the factor of interest was corrected for the effects of the other factors that might influence the variable under investigation. The weight of each factor was evaluated by the variance component analysis (VCA). Finally, multivariate statistical analyses, namely, principal component analysis (PCA) and linear discriminant analysis (LDA), were applied. Samples were grouped according to the harvest period and harvest method. Volatile compounds, that is, hexanal and trans-2-hexenal, as well as the sn-1,3-diglycerides and squalene, significantly decreased during the ripening. The relative value of the ?K parameter and the hexanal amount were higher in the olive oils obtained from olives harvested by one type of hand-held machine (shaker), whereas the unsaturated fatty chains in the olive oils were higher when another type (comb) was used.

Original languageEnglish
Pages (from-to)11043-11051
Number of pages9
JournalJournal of Agricultural and Food Chemistry
Volume58
Issue number20
DOIs
Publication statusPublished - Oct 27 2010

Keywords

  • ANOVA
  • General linear model analysis (GLM)
  • Harvest method
  • Harvest period
  • Linear discriminant analysis (LDA)
  • NMR
  • Olive oil
  • Principal component analysis (PCA)
  • Quality parameters
  • Variance component analysis (VCA)

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Chemistry(all)
  • Medicine(all)

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