2 resultados para Hierarchical cluster analysis
em Bioline International
Resumo:
Purpose: To develop a high-performance liquid chromatography (HPLC) fingerprint method for the quality control and origin discrimination of Gastrodiae rhizoma . Methods: Twelve batches of G. rhizoma collected from Sichuan, Guizhou and Shanxi provinces in china were used to establish the fingerprint. The chromatographic peak (gastrodin) was taken as the reference peak, and all sample separation was performed on a Agilent C18 (250 mm×4.6 mmx5 μm) column with a column temperature of 25 °C. The mobile phase was acetonitrile/0.8 % phosphate water solution (in a gradient elution mode) and the flow rate of 1 mL/min. The detection wavelength was 270 nm. The method was validated as per the guidelines of Chinese Pharmacopoeia. Results: The chromatograms of the samples showed 11 common peaks, of which no. 4 was identified as that of Gastrodin. Data for the samples were analyzed statistically using similarity analysis and hierarchical cluster analysis (HCA). The similarity index between reference chromatogram and samples’ chromatograms were all > 0.80. The similarity index of G. rhizoma from Guizhou, Shanxi and Sichuan is evident as follows: 0.854 - 0.885, 0.915 - 0.930 and 0.820 - 0.848, respectively. The samples could be divided into three clusters at a rescaled distance of 7.5: S1 - S4 as cluster 1; S5 - S8 cluster 2, and others grouped into cluster 3. Conclusion: The findings indicate that HPLC fingerprinting technology is appropriate for quality control and origin discrimination of G. rhizoma.
Resumo:
Phenotypic variation in plants can be evaluated by morphological characterization using visual attributes. Fruits have been the major descriptors for identification of different varieties of fruit crops. However, even in their absence, farmers, breeders and interested stakeholders require to distinguish between different mango varieties. This study aimed at determining diversity in mango germplasm from the Upper Athi River (UAR) and providing useful alternative descriptors for the identification of different mango varieties in the absence of fruits. A total of 20 International Plant Genetic Resources Institute (IPGRI) descriptors for mango were selected for use in the visual assessment of 98 mango accessions from 15 sites of the UAR region of eastern Kenya. Purposive sampling was used to identify farmers growing diverse varieties of mangoes. Evaluation of the descriptors was performed on-site and the data collected were then subjected to multivariate analysis including Principal Component Analysis (PCA) and Cluster analysis, one- way analysis of variance (ANOVA) and Chi square tests. Results classified the accessions into two major groups corresponding to indigenous and exotic varieties. The PCA showed the first six principal components accounting for 75.12% of the total variance. A strong and highly significant correlation was observed between the color of fully grown leaves, leaf blade width, leaf blade length and petiole length and also between the leaf attitude, color of young leaf, stem circumference, tree height, leaf margin, growth habit and fragrance. Useful descriptors for morphological evaluation were 14 out of the selected 20; however, ANOVA and Chi square test revealed that diversity in the accessions was majorly as a result of variations in color of young leaves, leaf attitude, leaf texture, growth habit, leaf blade length, leaf blade width and petiole length traits. These results reveal that mango germplasm in the UAR has significant diversity and that other morphological traits apart from fruits can be useful in morphological characterization of mango.