Abstract
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.
Highlights
According to the International Nuts & Dried Fruits Statistical Yearbook 2018/2019, almonds are the most consumed nut in high-income economies, accounting for 39% and followed by walnuts, cashews and hazelnuts [1]
Beltrán et al [15] achieved a classification of four almond cultivars (Butte from USA, Marcona, Guara and Garrigues from Spain) by using parameters related to the oil degradation
The obtained results indicate that, concerning the mineral concentration, the variability of the major mineral was lower than that of minor components when dealing with the different cultivar effect, interesting is the fact that K and Mg content variability was mainly explained by the cultivar rather than the harvest year of kernels
Summary
According to the International Nuts & Dried Fruits Statistical Yearbook 2018/2019, almonds are the most consumed nut in high-income economies, accounting for 39% and followed by walnuts, cashews and hazelnuts [1]. A recent study reported a proper classification of almonds from different geographical origins (Sicily, Spain and California) by the combination of chemometric techniques and the data related to fatty acid composition achieving an 87% of correctly classified samples. In this way, linear discriminant analysis (LDA) is the most predominant chemometric technique used with this purpose among the supervised pattern recognition methods [17]. Beltrán et al [15] achieved a classification of four almond cultivars (Butte from USA, Marcona, Guara and Garrigues from Spain) by using parameters related to the oil degradation As it was expected, the main fatty acids found in the almond samples were oleic, linoleic, stearic, palmitic and palmitoleic. GC-FID: gas chromatography-flame ionization detector; PCA: principal component analysis; GC-MS: gas chromatography-mass spectrometry
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