Chemical Markers to Distinguish the Homo- and Heterozygous Bitter Genotype in Sweet Almond Kernels

Foods
Stefania VichiAgustí Romero

Abstract

Bitterness in almonds is controlled by a single gene (Sk dominant for sweet kernel, sk recessive for bitter kernel) and the proportions of the offspring genotypes (SkSk, Sksk, sksk) depend on the progenitors' genotype. Currently, the latter is deduced after crossing by recording the phenotype of their descendants through kernel tasting. Chemical markers to early identify parental genotypes related to bitter traits can significantly enhance the efficiency of almond breeding programs. On this basis, volatile metabolites related to almond bitterness were investigated by Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry coupled to univariate and multivariate statistics on 244 homo- and heterozygous samples from 42 different cultivars. This study evidenced the association between sweet almonds' genotype and some volatile metabolites, in particular benzaldehyde, and provided for the first time chemical markers to discriminate between homo- and heterozygous sweet almond genotypes. Furthermore, a multivariate approach based on independent variables was developed to increase the reliability of almond classification. The Partial Least Square-Discriminant Analysis classification model built with selected volatile metabolite...Continue Reading

References

Mar 21, 2002·Journal of Agricultural and Food Chemistry·F DicentaV Berenguer
Aug 25, 2004·Plant Physiology·Natalia DudarevaJonathan Gershenzon
Jul 1, 1923·Genetics·M J Heppner
Jan 15, 2008·Plant Physiology·Raquel Sánchez-PérezBirger Lindberg Møller
Jul 19, 2013·Journal of Agricultural and Food Chemistry·Jihyun LeeAlyson E Mitchell
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Feb 15, 2019·Journal of Agricultural and Food Chemistry·Lillian M Franklin, Alyson E Mitchell
Jun 15, 2019·Science·R Sánchez-PérezB Lindberg Møller

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Citations

Jan 17, 2021·Foods·Ana Beltrán SanahujaMaría Soledad Prats Moya
Jan 28, 2021·Foods·Ángel Calín-Sánchez, Ángel A Carbonell-Barrachina

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Methods Mentioned

BETA
Solid Phase Microextraction

Software Mentioned

DA
SIMCA
SPSS
Statgraphics Plus
PLS

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