Résumé
Background and Aims Phenolic compounds contribute to food quality and have potential health benefits. Consequently, they are an important target of selection for Citrus species. Numerous studies on this subject have revealed new molecules, potential biosynthetic pathways and linkage between species. Although polyphenol profiles are correlated with gene expression, which is responsive to developmental and environmental cues, these factors are not monitored in most studies. A better understanding of the biosynthetic pathway and its regulation requires more information about environmental conditions, tissue specificity and connections between competing sub-pathways. This study proposes a rapid method, from sampling to analysis, that allows the quantitation of multiclass phenolic compounds across contrasting tissues and cultivars. Methods Leaves and fruits of 11 cultivated citrus of commercial interest were collected from adult trees grown in an experimental orchard. Sixty-four phenolic compounds were simultaneously quantified by ultra-high-performance liquid chromatography coupled with mass spectrometry. Key Results Combining data from vegetative tissues with data from fruit tissues improved cultivar classification based on polyphenols. The analysis of metabolite distribution highlighted the massive accumulation of specific phenolic compounds in leaves and the external part of the fruit pericarp, which reflects their involvement in plant defence. The overview of the biosynthetic pathway obtained confirmed some regulatory steps, for example those catalysed by rhamnosyltransferases. The results suggest that three other steps are responsible for the different metabolite profiles in `Clementine' and `Star Ruby' grapefruit. Conclusions The method described provides a high-throughput method to study the distribution of phenolic compounds across contrasting tissues and cultivars in Citrus, and offers the opportunity to investigate their regulation and physiological roles. The method was validated in four different tissues and allowed the identification and quantitation of 64 phenolic compounds in 20 min, which represents an improvement over existing methods of analysing multiclass polyphenols.