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  • 标题:Variability of Chemical Profile in Almonds (Prunus dulcis) of Different Cultivars and Origins
  • 本地全文:下载
  • 作者:Ana Beltrán Sanahuja ; Salvador E. Maestre Pérez ; Nuria Grané Teruel
  • 期刊名称:Foods
  • 电子版ISSN:2304-8158
  • 出版年度:2021
  • 卷号:10
  • 期号:1
  • 页码:153
  • DOI:10.3390/foods10010153
  • 出版社:MDPI Publishing
  • 摘要:Almonds show a great variability in their chemical composition. This variability is a result of the existence of a diverse range of almond cultivars, the self-incompatibility of most almond cultivars, and the heterogeneous harvesting conditions found around the different locations where almons are grown. In the last years, the discrimination among almond cultivars has been the focal point of some research studies to avoid fraud in protected geographical indications in almond products and also for selecting the best cultivars for a specific food application or the most interesting ones from a nutritional point of view. In this work, a revision of the recent research works related to the chemical characterization and classification of almond cultivars from different geographical origins has been carried out. The content of macronutrients, tocopherols, phytosterols, polyphenols, minerals, amino acids, and volatile compounds together with DNA fingerprint have been reported as possible cultivar and origin markers. The analysis of the results showed that no individual almond compound could be considered a universal biomarker to find differences among different almond cultivars. Hence, an adequate selection of variables or the employment of metabolomics and the application of multivariate statistical techniques is necessary when classification studies are carried out to obtain valuable results. Meanwhile, DNA fingerprinting is the perfect tool for compared cultivars based on their genetic origin.
  • 关键词:almond ( Prunus dulcis ); cultivar; geographical authenticity; chemical profile; analytical techniques; multivariate analysis; classification almond ( Prunus dulcis ) ; cultivar ; geographical authenticity ; chemical profile ; analytical techniques ; multivariate analysis ; classification
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