English
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Journal of Agricultural and Food Chemistry 2012-Sep

Supervised chemical pattern recognition in almond ( Prunus dulcis ) Portuguese PDO cultivars: PCA- and LDA-based triennial study.

Only registered users can translate articles
Log In/Sign up
The link is saved to the clipboard
João C M Barreira
Susana Casal
Isabel C F R Ferreira
António M Peres
José Alberto Pereira
M Beatriz P P Oliveira

Keywords

Abstract

Almonds harvested in three years in Trás-os-Montes (Portugal) were characterized to find differences among Protected Designation of Origin (PDO) Amêndoa Douro and commercial non-PDO cultivars. Nutritional parameters, fiber (neutral and acid detergent fibers, acid detergent lignin, and cellulose), fatty acids, triacylglycerols (TAG), and tocopherols were evaluated. Fat was the major component, followed by carbohydrates, protein, and moisture. Fatty acids were mostly detected as monounsaturated and polyunsaturated forms, with relevance of oleic and linoleic acids. Accordingly, 1,2,3-trioleoylglycerol and 1,2-dioleoyl-3-linoleoylglycerol were the major TAG. α-Tocopherol was the leading tocopherol. To verify statistical differences among PDO and non-PDO cultivars independent of the harvest year, data were analyzed through an analysis of variance, a principal component analysis, and a linear discriminant analysis (LDA). These differences identified classification parameters, providing an important tool for authenticity purposes. The best results were achieved with TAG analysis coupled with LDA, which proved its effectiveness to discriminate almond cultivars.

Join our facebook page

The most complete medicinal herbs database backed by science

  • Works in 55 languages
  • Herbal cures backed by science
  • Herbs recognition by image
  • Interactive GPS map - tag herbs on location (coming soon)
  • Read scientific publications related to your search
  • Search medicinal herbs by their effects
  • Organize your interests and stay up do date with the news research, clinical trials and patents

Type a symptom or a disease and read about herbs that might help, type a herb and see diseases and symptoms it is used against.
*All information is based on published scientific research

Google Play badgeApp Store badge