Metabolite profiles of essential oils in citrus peels and their taxonomic implications
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China is an important center of origin for the genus Citrus L. of the family Rutaceae and is rich in wild Citrus species. The taxonomy of Citrus has been a subject of controversy for more than a half century. We propose that the metabolite profiles of Chinese native Citrus species can be used for classification and understanding of the taxonomic relationships within the Citrus germplasm. In this study, triplicate gas chromatography–mass spectrometry (GC–MS) metabolite profiles of 20 Citrus species/varieties were acquired, including 10 native varieties originating in China. R-(+)-limonene, α-pinene, sabinene and α-terpinene were found to be major characteristic components of the essential oils analyzed in this study, and these compounds contributed greatly to the metabolic classification. The three basic species of the subgenus Eucitrus (Swingle’s system), i.e., C. reticulata Blanco, C. medica L. and C. grandis Osb., were clearly differentiated based upon their metabolite profiles using hierarchical cluster analysis (HCA) and partial least square-discriminant analysis (PLS-DA). All the presumed hybrid genotypes, including sweet orange (C. sinensis Osb.), sour orange (C. aurantium L.), lemon (C. limon Burm.f.), rough lemon (C. jambhiri Lush.), rangpur lime (C. limonia Osb.) and grapefruit (C. paradisi Macf.), were grouped closely together with one of their suggested parent species in the HCA-dendrogram and the PLS-DA score plot. These results clearly demonstrated that the metabolite profiles of Citrus species could be utilized for the taxonomic classification of the genus and are complementary to the existing taxonomic evidence, especially for the identification and differentiation of hybrid species.
KeywordsCitrus L. Chinese native species Essential oils Metabolite profiling GC–MS Taxonomy
Gas chromatography–mass spectrometry
Hierarchical cluster analysis
Nuclear magnetic resonance
Principal component analysis
Partial least square
Partial least square-discriminant analysis
Total ion chromatogram
This work was supported by the National Natural Science Foundation of China (No. 31171930), the Fundamental Research Funds for the Central Universities (XDJK2014A014), the Graduate Student Innovation Fund of Southwest University to Li Jing (kb2011005), the China Scholarship Council (CSC), Program for Chongqing Innovation Team of University (KJTD201333), and the “111” Project (B12006). LJ and LWS were supported by the Samuel Roberts Noble Foundation. LWS was supported in part by National Science Foundation awards (No. 1139489, 1024974 and 1124719).
Conflict of interest
Li Jing, Zhentian Lei, Guiwei Zhang, Alan Cesar Pilon, David V Huhman, Rangjin Xie, Wanpeng Xi, Zhiqin Zhou, and Lloyd W. Sumner declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals.
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