ABSTRACT
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.
Subject(s)
Electronic Nose , Odorants/analysis , Volatile Organic Compounds/analysis , Bayes Theorem , Drugs, Chinese Herbal/analysis , Discriminant AnalysisABSTRACT
This study adopted headspace-gas chromatography-mass spectrometry(HS-GC-MS) and electronic nose to detect volatile components from Myristicae Semen samples with varying degrees of mildew, aiming at rapidly identifying odor changes and substance basis of Myristicae Semen mildew. The experimental data were analyzed by electronic nose and principal component analysis(PCA). The results showed that Myristicae Semen samples were divided into the following three categories by electronic nose and PCA: mildew-free samples, slightly mildewy samples, and mildewy samples. Myristicae Semen samples with different degrees of mildew greatly varied in volatile components. The volatile components in the samples were qualitatively and quantitatively detected by HS-GC-MS, and 59 compounds were obtained. There were significant differences in the composition and content in Myristicae Semen samples with different degrees of mildew. The PCA results were the same as those by electronic nose. Among them, 3-crene, D-limonene, and other terpenes were important indicators for the identification of mildew. Bicyclo[3.1.0]hexane, 4-methylene-1-(1-methylethyl)-, terpinen-4-ol, and other alcohols were key substances to distinguish the degree of mildew. In the later stage of mildew, Myristicae Semen produced a small amount of hydroxyl and aldehyde compounds such as acetaldehyde, 2-methyl-propionaldehyde, 2-methyl-butyraldehyde, and formic acid, which were deduced as the material basis of the mildew. The results are expected to provide a basis for the rapid identification of Myristicae Semen with different degrees of mildew, odor changes, and the substance basis of mildew.
Subject(s)
Electronic Nose , Gas Chromatography-Mass Spectrometry , Odorants/analysis , Semen/chemistry , Solid Phase Microextraction , Volatile Organic Compounds/analysisABSTRACT
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.
Subject(s)
Drugs, Chinese Herbal , Electronic Nose , Medicine, Chinese Traditional , Semen , Support Vector MachineABSTRACT
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.
Subject(s)
Amygdalin , Chromatography, High Pressure Liquid , Drugs, Chinese Herbal , SemenABSTRACT
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/classificationABSTRACT
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".
ABSTRACT
<p><b>OBJECTIVE</b>Moxibustion is an important traditional Chinese medicine therapy using heat from ignited moxa floss for disease treatment. The purpose of the present study is to establish a reproducible method to assess the color of moxa floss, discriminate the samples based on chromatic coordinates and explore the relationship between chromatic coordinates and total flavonoid content (TFC).</p><p><b>METHODS</b>Moxa floss samples of different storage years and production ratios were obtained from a moxa production factory in Henan Province, China. Chromatic coordinates (L*, a* and b*) were analyzed with an ultraviolet-visible spectrophotometer and the chroma (C*) and hue angle (h°) values were calculated. TFC was determined by a colorimetric method. Data were analyzed with correlation, principal component analysis (PCA).</p><p><b>RESULTS</b>Significant differences in the chromatic values and TFC were observed among samples of different storage years and production ratios. Samples of higher production ratio displayed higher chromatic characteristics and lower TFC. Samples of longer storage years contained higher TFC. Preliminary separation of moxa floss production ratio was obtained by means of color feature maps developed using L*-a* or L*-b* as coordinates. PCA allowed the separation of the samples from their storage years and production ratios based on their chromatic characteristics and TFC.</p><p><b>CONCLUSION</b>The use of a colorimetric technique and CIELAB coordinates coupled with chemometrics can be practical and objective for discriminating moxa floss of different storage years and production ratios. The development of color feature maps could be used as a model for classifying the color grading of moxa floss.</p>
Subject(s)
Color , Flavonoids , MoxibustionABSTRACT
This study aims to investigate the relationship between odor and contents of the chemical compounds in Lonicera japonica, including chlorogenic acid, galuteolin and polyphenols. High performance liquid chromatography (HPLC) was applied to determine the contents of chlorogenic acid and galuteolin in L. japonica. The ponptent of polyphenols was determined by UV-Vis Spectrophotometry. Electronic nose was used to extract and measure the odor of L. japonica. Then SPSS 17.0 software was employed for data processing. There is a significant positive correlation between the comprehensive index value of aroma and the contents of chlorogenic acid and polyphenols. The regression equations have been established. However, the relationship between the comprehensive index value and the content of galuteolin is not obvious. This is proof that the odor of L. japonica has close connection with the chemical compounds. Therefore, this research offered a new method for initially determine or predict the content of the chemical composition in L. japonica,
Subject(s)
Chlorogenic Acid , Chemistry , Chromatography, High Pressure Liquid , Methods , Electronic Nose , Lonicera , Chemistry , Odorants , Polyphenols , Chemistry , SmellABSTRACT
Optimization of sensor array is a significant topic in the application of electronic nose (EN). Stepwise discriminant analysis and cluster analysis combining with screening of typical index were employed to optimize the original array in the classification of 100 samples from 10 kinds of traditional Chinese medicine based on alpha-FOX3000 EN. And the identification ability was evaluated by three algorithm including principle component analysis, Fisher discriminant analysis and random forest. The results showed that the identification ability of EN was improved since not only the effective information was maintained but also the redundant one was eliminated by the optimized array. The optimized method was eventually established, it was accurate and efficient. And the optimized array was built up, that is, S1, S2, S5, S6, S8, S12.
Subject(s)
Algorithms , Biosensing Techniques , Methods , Cluster Analysis , Discriminant Analysis , Drugs, Chinese Herbal , Classification , Electronic Nose , Medicine, Chinese Traditional , Principal Component Analysis , Reproducibility of Results , SmellABSTRACT
<p><b>OBJECTIVE</b>To ascertain the relationship between glycyrrhizinic acid content and the underground part growth character of Glycyrrhiza uralensis and provide the theoretical evidence for wild resources protection and artificial cultivation method of G. uralensis.</p><p><b>METHOD</b>Through the analytical investigation on the underground part of G. uralensis and analysis of glycyrrhizinic acid content in different organs, parts, ages, and diameter medicinal materials, the systematic study on the relationship between glycyrrhizinic acid content and the underground part growth character of glycyrrhiza uralensis was carried out.</p><p><b>RESULT</b>The underground part of a G. uralensis seedling consisted of seed root, random root, horizontal underground stem, vertical underground stem and assimilating root. The glycyrrhizinic acid content in horizontal underground stem with the age below two years old or in random root with the diameter below 0.5 cm was low. The difference of glycyrrhizinic acid content among horizontal underground stem, random root and vertical underground stem was obvious, but the difference between horizontal underground stem and random root was not obvious.</p><p><b>CONCLUSION</b>The horizontal underground stem was of G. uralnesis acts as a link that can connect random root, vertical underground and stem assimilating root, so that the whole underground part constructs one huge underground net system. The glycyrrhizinic acid accumulation is a effected by organ type, growth age, root diameter and grow position, and the distribution pattern of random root and vertical underground stem has influence on glycyrrhizinic acid distribution in horizontal underground stem.</p>