OBJECTIVETo study morphological features of traditional Chinese medicinal herbs in cold property, such as shape, color, odor and taste.

METHODTotally 118 traditional Chinese medicinal herbs in cold property were selected as study objects. EpiData 3.02 software was applied to establish a database, and SPSS 18.0 statistical software was used for data analysis.

RESULTIn terms of shape, traditional Chinese medicinal herbs in cold property were classified into 20 categories. Specifically, there were 33 cylindrical herbs, accounting for 28%; there were 10 flaky, ovate and massive herbs respectively, taking up 8.5%; there were 7 oval and curled herbs, occupying 5.9%; there were 6 sphere herbs, accounting for 5.1%; and other shapes were distributed dispersedly. By color, they were classified into 18 kinds, including 15 cases in yellow-brown color, accounting for 12.7% ; 14 cases in yellow-white color, taking up 11.9%; 13 cases in white color, occupying 11.0%; 9 cases in gray-brown color, accounting for 8.5%; 7 cases in dark brown, taking up 5.9%; and there were 6 cases in green, gray and brown colors respectively, occupying 5. 1%. By odor, they could be classified into 6 categories, including 49 cases with feeble odor, accounting for 41.5%, 31 cases without odor, taking up 26.3%; 15 cases with specific odor, occupying 12.7%; with respect to taste, there were 26 cases in slight bitter taste, accounting for 22.0%; 25 cases in flat taste, taking up 21.2%; 24 cases in bitter taste, occupying 20.3%; and 16 cases in sweet taste, accounting for 13.6%. In terms of texture, there were 34 cases in crisp texture, taking up 28.8%; 26 cases in light weight, occupying 22%; 25 cases in hard texture, accounting for 21.2%; 11 cases in solid and tough textures, respectively, taking up 9.3%; those in heavy weight and loose, hard, smooth and other textures occupied a small proportion.

CONCLUSIONThe morphologic characteristics of traditional Chinese medicines in cold property show certain regularity. They are mostly cylindrical, yellow, slightly bitter and crisp, with feeble odor. They provide reference for further studies.

Color ; Drugs, Chinese Herbal ; chemistry ; Humans ; Odorants ; analysis ; Taste

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.
Electronic Nose ; Odorants/analysis* ; Volatile Organic Compounds/analysis* ; Bayes Theorem ; Drugs, Chinese Herbal/analysis* ; Discriminant Analysis

The quality of honeysuckle has always been an important factor in industrial development. Flowering is one of the elements for the variation of the effective components in honeysuckle. We can conveniently recognize whether the commodity is mixed with blossomed honeysuckle in the form of medicinal material. However,it is hard to identify whether the products are mixed with blossomed honeysuckle in the form of powdersince visual identification traits are missing. Therefore,this study aims to seek an effective method of odor-based distinguish for identifying the quality of honeysuckle powder in different ratios by using Heracles Ⅱ ultra-fast gas phase electronic nose.The powdered samples were prepared with flower buds and fully blooming flowers in different proportion. Gas chromatograms of the powder were obtained by HeraclesⅡ ultra-fast gas phase electronic nose. Through analyzing the data of chromatograms,we have concluded that the qualitative results of the prepared powder were almost the same,and there existed differences in the components content. Meanwhile,the hexanal odor appeared to be the critical factor in identifying honeysuckle powder quality among the flavor of all possible compounds. Also,we have applied PCA,DFA and CQ to identify and classify the variety of the powder based on the chromatogram data. Finally,it is realized that the powder was rapidly identified and classified into three grades based on the proportion of flowering honeysuckle. The predicted concentration value for the first class is less than 3,the value of is not less than 3 and less than 5 for the second class,and more than 5 for the third class. In summary,the results obtained by the study suggest that Heracles Ⅱ ultra-fast gas phase electronic nose analysis can be used as a rapid identification method for the quality of honeysuckle powder. At the same time,it can provide a reference for the quality classification of honeysuckle based on flowering degrees.
Electronic Nose ; Flowers/chemistry* ; Lonicera/chemistry* ; Odorants/analysis* ; Plant Preparations/analysis* ; Powders/analysis* ; Quality Control

OBJECTIVETo digitalize the changes in characters of Magnoliae Officinalis Cortex after perspiration with colorimeter and electronic nose.

METHODWith perspired and non-perspired Magnoliae Officinalis Cortex as objective, colorimeter and electronic nose were used to detect their color characteristic parameter and odor characteristic parameter. Finally, an identification model was established.

RESULTIn terms of drug color, the color characteristic parameter model was established for perspired and non-perspired Magnoliae Officinalis Cortex on the basis of L*, a*, b* color spaces. The range of 90% of reference values of perspired Magnoliae Officinalis Cortex: L* (52.22-59.42), a* (5.36-7.68), b* (22.04-27.05). The range of 90% of reference values of non-perspired Magnoliae Officinalis Cortex: L* (38.42-47.31), a* (9.63-11.85), b* (18.48-25.53). In terms of drug odor, the principal component analysis (PCA) and the partial least squares method (PLS) showed significant difference between perspired and non-perspired Magnoliae Officinalis Cortex.

CONCLUSIONThe difference in drug color and odor of Magnoliae Officinalis Cortex before and after perspiration can be digitalized according to color and odor characteristic parameters tested with colorimeter and electronic nose.

Chemistry, Pharmaceutical ; Color ; Colorimetry ; Drugs, Chinese Herbal ; chemistry ; Magnolia ; chemistry ; Odorants ; analysis ; Quality Control

In order to investigate the mechanism, the correlation between the odor change in Crataegi Fructus stir-fried process and 5-HMF were studied. Required samples were retrieved from Crataegi Fructus stir-fried process. Statistical quality control (SQC) was used to analyze the response values acquired by the electronic nose. At the same time, the content of 5-HMF was detected by high performance liquid chromatography (HPLC). Correlation analysis was used to analyze the relationship between the above two. Experimental results showed that SQC model established by response values of all samples could show the change law of odor in Crataegi Fructus stir-fried process and changes of 5-HMF content was dropped after the first increase. Correlation analysis showed that the odor change in Crataegi Fructus stir-fried process and 5-HMF were significantly correlated (P < 0.05). Sugar degradation reaction and the Maillard reaction may be one of the mechanisms of the odor change in Crataegi Fructus stir-fried process.
Chromatography, High Pressure Liquid ; Crataegus ; chemistry ; Furaldehyde ; analogs & derivatives ; analysis ; Hot Temperature ; Odorants ; analysis ; Plant Extracts ; analysis ; Technology, Pharmaceutical ; methods

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.
Algorithms ; Curcuma/classification* ; Discriminant Analysis ; Drugs, Chinese Herbal/analysis* ; Electronic Nose ; Medicine, Chinese Traditional ; Odorants/analysis* ; Plants, Medicinal/classification*

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.
Electronic Nose ; Gas Chromatography-Mass Spectrometry ; Odorants/analysis* ; Semen/chemistry* ; Solid Phase Microextraction ; Volatile Organic Compounds/analysis*

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,
Chlorogenic Acid ; chemistry ; Chromatography, High Pressure Liquid ; methods ; Electronic Nose ; Lonicera ; chemistry ; Odorants ; analysis ; Polyphenols ; chemistry ; Smell

Different processed products of Coptidis Rhizoma have its unique odor, which is an important assessment index for pro- cessed products identification of Coptidis Rhizoma. Objectify odor as an entry point in this study, an electronic nose technology was used, and a suitable method for Coptidis Rhizoma measurement was built firstly. Then different processed products of Coptidis Rhizoma were detected by the method built. Finally, different processed products were identified by combining with chemometrics based on the objective odor information obtained. Electronic nose detection indicated that a significant difference in odor between different processed products was performed. Coptidis Rhizoma processed or not can be distinguished based on statistical quality control (SQC) and soft independent modeling of class analogy (SIMCA). Principle component analysis (PCA) model showed that Coptidis Rhizoma and its various processed products discriminated obviously. In addition, in order to identify the processed products of Coptidis Rhizoma, a correct recognition rate of 100% was acquired by discriminant factor analysis (DFA) , and the initial identification rate and cross-validation recognition rate of linear discriminant analysis (LDA) is 100%, 94.4% respectively. In conclusion, differentiationin odor of different processed Coptidis Rhizoma was performed by the electronic nose technology used, and different products Coptidis Rhizoma were dis- criminated by combining with chemometrics. This research can be a reference for objective identification in odor of traditional Chinese medicine, and is good for the inheritance and development of traditional experience in odor identification.
Chemistry, Pharmaceutical ; Chromatography, High Pressure Liquid ; Coptis ; chemistry ; Drugs, Chinese Herbal ; analysis ; Electronic Nose ; Odorants ; analysis ; Principal Component Analysis ; Rhizome ; chemistry

The study of neuronal activity with low frequency has shown an increasing interest for its greater stability and reliability recent years. One challenge in analyzing this kind of activity is to find similarities and differences between signals efficiently and effectively. The traditional analysis methods, such as short-time Fourier transform, are easily obscured by background noises and often involve a large number of parameters. Therefore, this paper introduces a novel time-frequency analysis method based on wavelet transformation and half-ellipsoid modeling to extract instantaneous frequency and instantaneous phase information. This method overcomes some shortcomings of conventional time-frequency analysis. In this method, wavelet transformation is used to provide high-level representations of raw signals, and parsimonious half-ellipsoid models are used to extract changes in time domain and frequency domain of neural recordings. The method was validated to local field potentials (LFPs) of olfactory bulb of anesthetized rats during three different odor stimuli. The results suggested that this method could detect odor-relevant features from olfactory signals with large variability. The Odors then were classified with support vector machine (SVM) algorithm and the classification accuracy reached 79.4%.
Algorithms ; Animals ; Evoked Potentials ; Fourier Analysis ; Odorants ; analysis ; Olfactory Bulb ; physiology ; Rats ; Reproducibility of Results ; Smell ; physiology ; Support Vector Machine ; Wavelet Analysis