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1.
Zhongguo Zhong Yao Za Zhi ; (24): 5375-5381, 2019.
Article in Chinese | WPRIM | ID: wpr-1008409

ABSTRACT

This article aims to identify four commonly applied herbs from Curcuma genus of Zingiberaceae family,namely Curcumae Radix( Yujin),Curcumae Rhizoma( Ezhu),Curcumae Longae Rhizoma( Jianghuang) and Wenyujin Rhizoma Concisum( Pianjianghuang). The odor fingerprints of those four herbal medicines were collected by electronic nose,respectively. Meanwhile,XGBoost algorithm was introduced to data analysis and discriminant model establishment,with four indexes for performance evaluation,including accuracy,precision,recall,and F-measure. The discriminant model was established by XGBoost with positive rate of returning to 166 samples in the training set and 69 samples in the test set were 99. 39% and 95. 65%,respectively. The top four of the contribution to the discriminant model were LY2/g CT,P40/1,LY2/Gh and LY2/LG,the least contributing sensor was T70/2. Compared with support vector machine,random forest and artificial neural network,XGBoost algorithms shows better identification capacity with higher recognition efficiency. The accuracy,precision,recall and F-measure of the XGBoost discriminant model forecast set were 95. 65%,95. 25%,93. 07%,93. 75%,respectively. The superiority of XGBoost in the identification of Curcuma herbs was verified. Obviously,this new method could not only be suitable for digitization and objectification of traditional Chinese medicine( TCM) odor indicators,but also achieve the identification of different TCM based on their odor fingerprint in electronic nose system. The introduction of XGBoost algorithm and more excellent algorithms provide more ideas for the application of electronic nose in data mining for TCM studies.


Subject(s)
Algorithms , Curcuma/classification , Discriminant Analysis , Drugs, Chinese Herbal/analysis , Electronic Nose , Medicine, Chinese Traditional , Odorants/analysis , Plants, Medicinal/classification
2.
Zhongguo Zhong Yao Za Zhi ; (24): 1134-1137, 2013.
Article in Chinese | WPRIM | ID: wpr-350645

ABSTRACT

<p><b>OBJECTIVE</b>To develop an effective identification method for accurately discriminating Psammosilene tunicoides and its confused species by the combined method of microscopic identification and molecular identification, so-called systematic identification of Chinese materia medica (SICMM).</p><p><b>METHOD</b>P. tunicoides and its confused species were accurately discriminated by SICMM method, which was established by comprehensively use of microscopic identification and DNA identification method. The DNA identification included the following analysis: the BLAST alignment, specific bases and N-J phylogenetic tree analysis.</p><p><b>RESULT</b>The cluster crystals were not observed in P. tunicoides, but great deals of them were found in Silene viscidula. Further more, big differences of ITS sequence were observed and analyzed between P. tunicoides and its confused specie of S. viscidula.</p><p><b>CONCLUSION</b>The system method is a scientific and accurate method for the identification of P. tunicoides and its counterfeit species.</p>


Subject(s)
Base Sequence , Caryophyllaceae , Chemistry , Classification , Cell Biology , Genetics , DNA, Intergenic , Phenotype , Phylogeny , Sequence Alignment
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