BACKGROUND: The growing demand for high-quality virgin olive oils (VOOs) has increased the interest in olive breeding programs. Cross-breeding is considered, within these programs, the best strategy to generate new cultivars as an attempt to improve the present cultivars. In this research, the phenolic profile of VOOs from target crosses (Arbequina × Arbosana, Picual × Koroneiki and Sikitita × Arbosana) and their corresponding genitors (Arbequina, Arbosana, Koroneiki, Picual and Sikitita) has been evaluated using a targeted metabolomics approach. RESULTS: The phenolic profiles were obtained by liquid chromatographic-hybrid quadrupole time-of-flight mass spectrometric targeted analysis of 37 phenols or compounds involved in the main pathways for their biosynthesis. Statistical multivariate analysis by principal component analysis was applied to study the influence of genotype on phenol composition. Phenolic compounds with the highest contribution to explain the observed variability associated to genotype were identified through fold change algorithms (cut-off > 2.0) and t-test analysis. CONCLUSION: A total of nine phenols (viz. quercetin, ligstroside aglycon (p-HPEA-EA), demethyl oleuropein aglycon, oleuropein aglycon (3,4-DHPEA-EA), hydroxypinoresinol, hydroxytyrosol and phenolic acids such as p-coumaric acid, ferulic acid and protocatechuic acid) contributed to explain the observed variability with 99% confidence (P<0.01).
BACKGROUND: The growing demand for high-quality virgin olive oils (VOOs) has increased the interest in olive breeding programs. Cross-breeding is considered, within these programs, the best strategy to generate new cultivars as an attempt to improve the present cultivars. In this research, the phenolic profile of VOOs from target crosses (Arbequina × Arbosana, Picual × Koroneiki and Sikitita × Arbosana) and their corresponding genitors (Arbequina, Arbosana, Koroneiki, Picual and Sikitita) has been evaluated using a targeted metabolomics approach. RESULTS: The phenolic profiles were obtained by liquid chromatographic-hybrid quadrupole time-of-flight mass spectrometric targeted analysis of 37 phenols or compounds involved in the main pathways for their biosynthesis. Statistical multivariate analysis by principal component analysis was applied to study the influence of genotype on phenol composition. Phenolic compounds with the highest contribution to explain the observed variability associated to genotype were identified through fold change algorithms (cut-off > 2.0) and t-test analysis. CONCLUSION: A total of nine phenols (viz. quercetin, ligstroside aglycon (p-HPEA-EA), demethyl oleuropein aglycon, oleuropein aglycon (3,4-DHPEA-EA), hydroxypinoresinol, hydroxytyrosol and phenolic acids such as p-coumaric acid, ferulic acid and protocatechuic acid) contributed to explain the observed variability with 99% confidence (P<0.01).