Phenolic and fatty acid profiles, α-tocopherol and sucrose contents, and antioxidant capacities of understudied Portuguese almond cultivars

Ivo Oliveira*, Anne S. Meyer, Sílvia Afonso, Alfredo Aires, Piebiep Goufo, Henrique Trindade, Berta Gonçalves

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


Almonds have recognized health benefits, which are largely attributed to their chemical composition, including fatty acids, phenolics, vitamin E, and sucrose. This study was carried with the aim of providing information on the levels of the aforementioned bioactive compounds and antioxidant activities in six understudied Portuguese cultivars (Amendoão, Bonita, Casanova, Molar, Pegarinhos–Moncorvo, Pegarinhos–Murça and Refêgo), in comparison with two foreign cultivars (Ferragnès and Glorieta). A cultivar effect was observed for all the parameters evaluated, with some Portuguese cultivars comparing well and even favorably with the foreign ones. A multivariate analysis of the data allowed a clear discrimination of cultivars and that statistical tool could be used for authenticity purposes, especially for cultivars included in the Protected Designation of Origin “Amêndoa Douro.”. 

Practical applications: Almonds are among the most consumed nuts worldwide, with a considerable number of cultivars recorded around the world, although research has been neglecting the local cultivars. This work studies the chemical composition of several understudied cultivars and compares them to two widespread commercial ones. The results not only provide new information about these neglected cultivars, but also provide data for stakeholders to select more interesting cultivars with particular characteristics/or rich in compounds of interest.

Original languageEnglish
Article numbere12887
JournalJournal of Food Biochemistry
Issue number7
Number of pages12
Publication statusPublished - 2019


  • Chemical composition
  • Cultivar characterization
  • Cultivar discrimination
  • Linear discriminant analysis (LDA)
  • Principal component analysis (PCA)
  • Prunus dulcis

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