Canonical Correlation Model for Understanding Fig (Ficus carica L.) Mislabeling Using Biochemical and Morphometric Markers

Abstract

This study investigated potential mislabeling within 23 fig cultivars from northern Morocco by integrating morphometric and biochemical markers through multivariate analysis. The aim was to assess cultivar identification accuracy and explore efficient germplasm management strategies. Canonical correlation analysis (CCA) revealed a statistically significant and substantial correlation between the morphometric and biochemical datasets (Wilk’s λ = 0.004, F [84, 179.49] = 3.18, p < 0.0001), a key step unveiling the interconnected nature of these traits and their combined potential for accurate cultivar discrimination. The interplay of datasets demonstrated that dark-colored figs exhibited higher levels of total phenols, anthocyanin, and radical 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, with the ‘Ghoudan’ cultivar consistently showing the highest concentrations. However, total phenol content did not correlate significantly with fruit color parameters, suggesting a more complex relationship. Proanthocyanidin levels were minimal across cultivars, and the ABTS assay consistently indicated higher antioxidant activity compared to DPPH. Total soluble sugars exhibited minimal variation among fruits. Leveraging CCA results, hierarchical clustering identified potential homonymy instances within ‘Ghoudan,’ ‘El Quoti Lbied,’ and ‘Nabout’ cultivars, where fruit weight, width, skin color coordinates, total phenols, flavonoids, and DPPH radical scavenging activity emerged as influential factors for discerning mislabeling. These findings underscore the efficacy of integrating morphometric and biochemical characterization for accurate fig cultivar identification and mislabeling detection within germplasm collections. The strong CCA correlation emphasizes this approach’s potential as a preliminary screening tool for large germplasm collections. By efficiently identifying potential mislabeling cases, resources can be directed towards molecular confirmation, ensuring the integrity and effective management of valuable fig genetic resources.