Establishment of a fast discriminant model with electronic nose for Polygonati Rhizoma mildew based on odor variation / 中国中药杂志

The odor fingerprint of Pollygonati Rhizoma samples with different mildewing degrees was analyzed and the relationship between the odor variation and the mildewing degree was explored. A fast discriminant model was established according to the response intensity of electronic nose. The α-FOX3000 electronic nose was applied to analyze the odor fingerprint of Pollygonati Rhizoma samples with different mildewing degrees and the radar map was used to analyze the main contributors among the volatile organic compounds. The feature data were processed and analyzed by partial least squares discriminant analysis(PLS-DA), K-nearest neighbor(KNN), sequential minimal optimization(SMO), random forest(RF) and naive Bayes(NB), respectively. According to the radar map of the electronic nose, the response values of three sensors, namely T70/2, T30/1, and P10/2, increased with the mildewing, indicating that the Pollygonati Rhizoma produced alkanes and aromatic compounds after the mildewing. According to PLS-DA model, Pollygonati Rhizoma samples of three mildewing degrees could be well distinguished in three areas. Afterwards, the variable importance analysis of the sensors was carried out and then five sensors that contributed a lot to the classification were screened out: T70/2, T30/1, PA/2, P10/1 and P40/1. The classification accuracy of all the four models(KNN, SMO, RF, and NB) was above 90%, and KNN was most accurate(accuracy: 97.2%). Different volatile organic compounds were produced after the mildewing of Pollygonati Rhizoma, and they could be detected by electronic nose, which laid a foundation for the establishment of a rapid discrimination model for mildewed Pollygonati Rhizoma. This paper shed lights on further research on change pattern and quick detection of volatile organic compounds in moldy Chinese herbal medicines.

Change pattern and correlation analysis of macroscopic characteristics, active components and rancidness degrees of Armeniacae Semen Amarum in deterioration process / 中国中药杂志

To discuss the effect of deterioration on the quality of Armeniacae Semen Amarum by observing the changes of macroscopic characteristics, active components and rancidness degrees of Armeniacae Semen Amarum in deterioration process. The traditional macroscopic identification was used to observe, identify and classify the morphologic and organleptic characteristics of Armeniacae Semen Amarum. The contents of amygdalin and fatty oil(two representatives of active components) were detected by HPLC and general rule 0713 in Chinese Pharmacopoeia, respectively. Acid value and peroxide value of the samples were selected as the representative indices of different rancidness degrees, and the general rule 2303 was adopted as the method for quantitative analysis. Then principal component analysis(PCA), partial least square analysis discrimination analysis(PLS-DA) were further utilized to establish the discriminative models of samples with different rancidness degrees, and also to screen out the largest contribution factors. In sensory evaluation, Armeniacae Semen Amarum samples were divided into three groups: non-rancid, slightly-rancid, and noticeably-rancid. The color of seed coat, cotyledon and surface of noticeably-rancid samples was deepened, and the odor differed much from non-rancid samples. Average content of amygdalin and fatty oil in non-rancid samples was 4.12% and 67.77%, respectively, both meeting the requirements of Chinese Pharmacopoeia; and decreased to some extent in slightly-rancid samples. However, the content of amygdalin sharply dropped to 0.074% in noticeably-rancid samples. The acid value and peroxide value were increased significantly with the intensifying of the rancidness degree, from only 1.363 and 0.016 74 in non-rancid samples to 1.865 and 0.023 70 in slightly-rancid samples, even doubled in noticeably-rancid samples(2.167 and 0.033 82). The discriminative models established by PCA and PLS-DA could complete the task of distinguishing the non-rancid samples from noticeably-rancid ones. The contribution degree of amygdalin content as one of the input attributes of discriminative model was higher than 1. Rancidness affected the quality of Armeniacae Semen Amarum, resulting in appearance changes, decrease in content of active components, and increase in acid value and peroxide value. Obviously, noticeably-rancid samples were non-conforming to Chinese Pharmacopoeia and no longer suitable for medicinal use. Rancidness can significantly reduce the quality of Armeniacae Semen Amarum, and even could possibly produce toxicity, which should attach more attention.

Discrimination of Armeniacae Semen Amarum from different processed products and various rancidness degrees by electronic nose and support vector machine / 中国中药杂志

This study was aimed to develop a simple, rapid and reliable method for identifying Armeniacae Semen Amarum from different processed products and various rancidness degrees. The objective odor information of Armeniacae Semen Amarum was obtained by electronic nose. 105 batches of Armeniacae Semen Amarum samples were studied, including three processed products of Armeniacae Semen Amarum, fried Armeniacae Semen Amarum and peeled Armeniacae Semen Amarum, as well as the samples with various rancidness degrees: without rancidness, slight rancidness, and rancidness. The discriminant models of different processed products and rancidness degrees of Armeniacae Semen Amarum were established by Support Vector Machine(SVM), respectively, and the models were verified based on back estimation of blind samples. The results showed that there were differences in the characteristic response radar patterns of the sensor array of different processed products and the samples with different rancidness degrees. The initial identification rate was 95.90% and 92.45%, whilst validation recognition rate was 95.38% and 91.08% in SVM identification models. In conclusion, differentiation in odor of different processed and rancidness degree Armeniacae Semen Amarum was performed by the electronic nose technology, and different processed and rancidness degrees Armeniacae Semen Amarum were successfully discriminated by combining with SVM. This research provides ideas and methods for objective identification of odor of traditional Chinese medicine, conducive to the inheritance and development of traditional experience in odor identification.

Identification of Curcuma herbs using XGBoost algorithm in electronic nose odor fingerprint / 中国中药杂志

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.

Rancidness of Armeniacae Semen Amarum involving Bianzhuang Lunzhi / 中国中药杂志

This article aims to compare the qualities of Armeniacae Semen Amarum before and after rancidness, in order to study the rancidness of Armeniacae Semen Amarum. In the experiment, content of fatty oil, acid value and peroxide value were determined before and after rancidness,respectively. Meanwhile, HPLC, GC-MS were utilized to analyze laetrile and fatty acid components. Besides, colorimeter and e-nose were introduced to quantify and compare "color and odor". A correlation analysis was conducted on the above results. The results showed that color of post-rancidness Armeniacae Semen Amarum changed from yellow to brown, with sour and lower content of laetrile. On the contrary, acid and peroxide values increased significantly, with changes in fatty acid component. There was a considerable correlation between appearance characteristics and changes in internal quality. The "sensory analysis-quality identification system" can provide a certain scientific basis for prediction of the content of chemical components in traditional Chinese medicine, preliminary judgment of quality of traditional Chinese medicine and real-time quality monitoring, which offers us novel ideas and reference for storage principles of traditional Chinese medicines of "pre-event prediction, during-event intervention and post-event identification".