ArticleBMC plant biology2023
The DNA barcode identification of Dalbergia odorifera T. Chen and Dalbergia tonkinensis Prain.
Article in BMC plant biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Article
- Reassessment of the Conservation Status of the Endemic and Endangered PlantEcology and evolution · 2025Article
- Identification ofFrontiers in pharmacology · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundDalbergia odorifera is a precious tree species with unique economic and medicinal values, which is difficult to distinguish from Dalbergia tonkinensis by traditional identification methods such as morphological characteristics and wood structure characteristics. It has been demonstrated that the identification of tree species can be effectively achieved using DNA barcoding, but there is a lack of study of the combined sequences used as DNA barcodes in the two tree species. In this study, 10 single sequences and 4 combined sequences were selected for analysis, and the identification effect of each sequence was evaluated by the distance-based method, BLAST-based search, character-based method, and tree-based method.
resultsAmong the single sequences and the combined sequences, the interspecies distance of trnH-psbA and ITS2 + trnH-psbA was greater than the intraspecies distance, and there was no overlap in their frequency distribution plots. The results of the Wilcoxon signed-rank test for the interspecies distance of each sequence showed that the interspecies differences of the single sequences except trnL-trnF, trnH-psbA, and ycf3 were significantly smaller than those of the combined sequences. The results of BLAST analysis showed that trnH-psbA could accurately identify D. odorifera and D. tonkinensis at the species level. In the character-based method, single sequences of trnL-trnF, trnH-psbA with all the combined sequences can be used for the identification of D. odorifera and D. tonkinensis. In addition, the neighbor-joining (NJ) trees constructed based on trnH-psbA and ITS2 + trnH-psbA were able to cluster D. odorifera and D. tonkinensis on two clades.
conclusionsThe results showed that the character-based method with the BLOG algorithm was the most effective among all the evaluation methods, and the combined sequences can improve the ability to identify tree species compared with single sequences. Finally, the trnH-psbA and ITS2 + trnH-psbA were proposed as DNA barcodes to identify D. odorifera and D. tonkinensis.
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