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  • 标题:Physical and Thermal Evaluation of Olive Oils from Minor Italian Cultivars
  • 本地全文:下载
  • 作者:Maria Paciulli ; Graziana Difonzo ; Paola Conte
  • 期刊名称:Foods
  • 电子版ISSN:2304-8158
  • 出版年度:2021
  • 卷号:10
  • 期号:5
  • 页码:1004
  • DOI:10.3390/foods10051004
  • 出版社:MDPI Publishing
  • 摘要:Authentication of extra virgin olive oils is a key strategy for their valorization and a way to preserve olive biodiversity. Physical and thermal analysis have been proposed in this study as fast and green techniques to reach this goal. Thirteen extra virgin olive oils (EVOOs) obtained from minor olive cultivars, harvested at three different ripening stages, in four Italian regions (Abruzzo, Apulia, Sardinia, and Calabria) have been studied. Thermal properties, viscosity and color, as influenced by fatty acid composition and chlorophyll content, have been investigated. The thermal curves of EVOOs, obtained by differential scanning calorimetry, were mostly influenced by the oleic acid content: a direct correlation with the cooling and heating enthalpy and an indirect correlation with the cooling transition range were observed. The minor fatty acids, and particularly arachidic acid, showed an influence, mostly on the heating thermograms. Viscosity and color showed respectively a correlation with fatty acids composition and chlorophyll content, however they didn’t result able to discriminate between the samples. Thanks to the principal component analysis, the most influencing thermal parameters and fatty acids were used to cluster the samples, based on their botanical and geographical origin, resulting instead the harvesting time a less influential variable.
  • 关键词:extra virgin olive oil; authenticity; biodiversity; differential scanning calorimetry; color; chlorophyll; harvesting time; geographical origin; botanical origin; principal component analysis extra virgin olive oil ; authenticity ; biodiversity ; differential scanning calorimetry ; color ; chlorophyll ; harvesting time ; geographical origin ; botanical origin ; principal component analysis
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