Chemotaxonomic classification of closed-related sweet oranges (Citrus sinensis L.) using principal component and cluster analysis of color and bi-oactive compounds in the orange peels

Abstract

Chemotaxonomy is a systematic approach to plant classification based on discernible variations and similarities in their biochemical compositions, with a particular emphasis on secondary metabolites that often exhibit specificity within taxonomically related plant species. In the context of our investigation, we conducted a comprehensive chemotaxonomic analysis of sweet oranges utilized in concentrated juice production. This involved a thorough examination of antioxidant activities, characterization of flavonoid and phenolic profiles, UV-visible spectra scanning, and the implementation of color analysis. The results from cluster analysis demonstrated the superior efficacy of color analysis in discerning subtle distinctions among orange varieties. Further refinement in the analytical process requires the application of supplementary techniques after an exhaustive and precise extraction facilitated by organic solvents. Notably, all employed methodologies successfully discriminated between distinct orange types. While the compilation of extensive datasets presents inherent challenges, the incorporation of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) enhances the interpretability of the obtained results. Considering that existing methodologies for assessing fresh fruit quality rely on subjective human visual inspection or orange juice analysis by ratio, which may lack precision in quantifying chemical constituents, there exists a growing demand for expedited techniques that can reliably ensure the quality of orange juice within the industry.