Castanea spp. Nut Traceability: A Multivariate Strategy Based on Phytochemical Data

Featured Application The present work, based on a multivariate approach, may represent a rapid, effective, and low-cost tool, preliminary to genetic analysis, for the assessment of the traceability and quality of Castanea spp. nuts with no information on their origin.The phytochemical characterization of Castanea spp. fruits is very important for the development of effective strategies for the biodiversity conservation and traceability of chestnuts, as the chestnut is one of the most important Italian and European nut and forest species. In this study, several cultivars of C. sativa (sweet chestnuts and marrone-type), C. crenata, and hybrids of C. sativa x C. crenata were characterized by spectrophotometric (Folin-Ciocalteu assay for the total polyphenolic content and ferric reducing antioxidant power test for the antioxidant capacity) and chromatographic (high-performance liquid chromatography coupled to a diode array UV-Vis detector) protocols to define their phytochemical composition and nutraceutical properties. The phytochemical results were then used to build a multivariate statistical model (by principal component analysis) and obtain an effective and rapid tool to discriminate unknown cultivars (i.e., no information about their origin) belonging to different species. The multivariate approach showed that the genotype was a significantly discriminating variable (p < 0.05) for the phytochemical composition. Polyphenols (in particular, phenolic acids and tannins) have been identified as the main bioactive classes with the highest discriminating power among the different genotypes. The total polyphenol content (TPC) and antioxidant capacity (AOC) showed a rich presence of bioactive compounds (74.09 +/- 15.10 mg(GAE) 100 g(-1) DW and 11.05 +/- 1.35 mmol Fe2+ kg(-1) DW, respectively), underlining the potential health benefits and functional traits of chestnuts. The principal component analysis applied to phytochemical variables has proved to be an excellent and effective tool for genotype differentiation to be used as a preliminary method for identifying the species of Castanea spp. fruits with an unknown origin. The present study showed that a multivariate approach, based on phytochemical data and preliminary to genetic analysis, may represent a rapid, effective, and low-cost tool for the traceability and quality evaluation of chestnuts from different species and hybrids with no information on their origin.

Automated summary

This study used a multivariate approach to investigate the phytochemical characteristics of Castanea spp. fruits. The results showed that the genotype was the main discriminating variable for the phytochemical composition, with polyphenols identified as the main bioactive compounds. By establishing a multivariate statistical model, this study provided a rapid, effective, and low-cost method for discriminating unknown cultivars of chestnuts.