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Seeds are the source for the production of Chinese medicinal materials. The seed authenticity and quality of directly affect the effectiveness and safety of Chinese medicinal materials. The seed quality is faced with the problems such as mixed sources, existence of adulterants and seeds stocked for years, low maturity, and low purity. To ensure the high-quality and sustainable development of the Chinese medicinal material industry, it is urgent to standardize the seed market and identify and evaluate the quality of the seeds circulating in the market. Seed identification methods include visual inspection, microscopic observation, micro-character identification, chemical fingerprinting, molecular identification, electronic nose, X-ray diffraction, electrochemical fingerprinting, spectral imaging, and artificial intelligence. These methods have different application scopes and unique advantages and disadvantages. According to the different species of Chinese herbal medicines and different requirements of testing sites, suitable methods can be selected to achieve rapid and accurate identification with low costs. In the future, the seed identification methods should be developed based on emerging technologies with interdisciplinary knowledge, and intelligent, nondestructive, and single-grain detection methods are needed for the modern Chinese medicinal material industry. This paper introduces the seed identification technologies currently applied in research and production, compares the principles, applicability, advantages, and disadvantages of different technologies, and provides an outlook on the future development of seed identification technologies, aiming to provide a reference for the identification and quality evaluation of seeds of Chinese medicinal material.
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Bronchial asthma is a heterogeneous disease characterized by chronic airway inflammation. In recent years, the diagnosis and treatment of asthma tend to be precision medicine, and the individualized treatment of asthma is mainly based on individualized diagnosis. However, the pathogenesis of asthma is complex and the clinical phenotype is different, and its high heterogeneity also brings great challenges to realize individualized diagnosis and treatment, Diagnosis and evaluation based on multi-dimensional and multi-means is an important practical development direction.
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In this study, CM-5 spectrophotometer and Heracles NEO ultra-fast gas-phase electronic nose were used to analyze the changes in color and odor of vinegar-processed Cyperi Rhizoma(VPCR) pieces. Various analysis methods such as DFA and partial least squares discriminant analysis(PLS-DA) were combined to identify different processing degrees and quantify the end point of processing. The results showed that with the increase in vinegar processing, the brightness parameter L~* of VPCR pieces decreased gradua-lly, while the red-green value a~* and yellow-blue value b~* initially increased and reached their maximum at 8 min of processing, followed by a gradual decrease. A discriminant model based on the color parameters L~*, a~*, and b~* was established(with a discrimination accuracy of 98.5%), which effectively differentiated different degrees of VPCR pieces. Using the electronic nose, 26 odor components were identified from VPCR samples at different degrees of vinegar processing. DFA and PLS-DA models were established for different degrees of VPCR pieces. The results showed that the 8-min processed samples were significantly distinct from other samples. Based on variable importance in projection(VIP) value greater than 1, 10 odor components, including 3-methylfuran, 2-methylbuty-raldehyde, 2-methylpropionic acid, furfural, and α-pinene, were selected as odor markers for differentiating the degrees of vinegar processing in VPCR. By combining the changes in color and the characteristic odor components, the optimal processing time for VPCR was determined to be 8 min. This study provided a scientific basis for the standardization of vinegar processing techniques for VPCR and the improvement of its quality standards and also offered new methods and ideas for the rapid identification and quality control of the end point of processing for other traditional Chinese medicine.
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Ácido Acético , Medicamentos de Ervas Chinesas/análise , Rizoma/química , Controle de Qualidade , EletrônicaRESUMO
ObjectiveTo investigate the feasibility of applying electronic nose technology to rapidly identify Bletillae Rhizoma and its approximate decoction pieces. MethodA total of 134 batches of Bletillae Rhizoma and its approximate decoction pieces, including 45 batches of Bletillae Rhizoma, 30 batches of Gastrodiae Rhizoma, 30 batches of Polygonati Odorati Rhizoma and 29 batches of Bletillae Ochraceae Rhizoma, were collected as test samples. The olfactory sensory data of the samples were collected by PEN3 electronic nose as the independent variable(X). Based on the identification results of the 2020 edition of Chinese Pharmacopoeia and local standards, as well as the high performance liquid chromatography(HPLC) fingerprint and original purchase information of 134 batches of the decoction pieces, the benchmark data Y of the identification model were obtained, and four chemometric methods of principal component analysis-discriminant analysis(PCA-DA), partial least squares-discriminant analysis(PLS-DA), least square-support vector machine(LS-SVM) and K-nearest neighbor(KNN) were used to establish the binary identification model for 45 batches of Bletillae Rhizoma and 89 batches of non-Bletillae Rhizoma and the quadratic identification model of the four kinds of decoction pieces, that is, Y=F(X). ResultAfter leave-one-out cross validation, the positive discrimination rates of the above four models were 97.01%, 97.01%, 98.51% and 97.01% in the binary identification, and 97.76%, 89.55%, 98.51% and 97.01% in the quadratic identification, respectively. The highest positive discrimination rate could reach 98.51% for the binary and quadratic identification models, and LS-SVM algorithm is both the optimal one, the most suitable kernel functions were chosen as radial basis function and linear kernel function, respectively. The optimal models discriminated well with no unclassified samples. ConclusionElectronic nose technology can accurately and rapidly identify Bletillae Rhizoma and its approximate decoction pieces, which can provide new ideas and methods for rapid quality evaluation of other decoction pieces.
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OBJECTIVE To analyze the odor composition changes of two kinds of traditional Chinese medicine sachet (children type and adults type) with different placement time by using ultra-fast gasphase electronic nose technology. METHODS The change rule of sachet components at different storage times was analyzed by gas chromatography. At the same time, the qualitative results were obtained by combining electronic nose with Arochembase database. Discriminant factor analysis was used to analyze the overall odor composition differences of the two sachet samples. RESULTS A total of 10 odor compositions were identified in children-type sachet, including α-pinene and β-pinene as the functional index compositions; five odor compositions of children-type sachet disappeared after 0.25 days, and most of them disappeared after 7 days; the cumulative contribution rate of discriminant factor analysis was 99.225%. A total of 8 odor compositions were identified in adult-type sachets, including α-pinene and α-phellandrene as the functional index compositions; four odor components disappeared after the adult-type sachet was placed for 0.25 days; after 15 days of placement, the peak 6-8 disappeared, and the intensity of peak 5 decreased by 34.3% compared with 0 day of placement; the cumulative contribution rate of discriminant factor analysis was 91.965%. CONCLUSIONS With the extension of storage time, the smell and composition of the two traditional Chinese medicine sachets are decreasing. It is recommended that the use time of children-type sachet is 7 days, and that of adult-type sachet is 15 days.
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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.
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Nariz Eletrônico , Odorantes/análise , Compostos Orgânicos Voláteis/análise , Teorema de Bayes , Medicamentos de Ervas Chinesas/análise , Análise DiscriminanteRESUMO
Since Curcumae Radix decoction pieces have multiple sources, it is difficult to distinguish depending on traditional cha-racters, and the mixed use of multi-source Curcumae Radix will affect its clinical efficacy. Heracles Neo ultra-fast gas phase electronic nose was used in this study to quickly identify and analyze the odor components of 40 batches of Curcumae Radix samples from Sichuan, Zhejiang, and Guangxi. Based on the odor fingerprints established for Curcumae Radix decoction pieces of multiple sources, the odor components was identified and analyzed, and the chromatographic peaks were processed and analyzed to establish a rapid identification method. Principal component analysis(PCA), discriminant factor analysis(DFA), and soft independent modeling cluster analysis(SIMCA) were constructed for verification. At the same time, one-way analysis of variance(ANOVA) combined with variable importance in projection(VIP) was employed to screen out the odor components with P<0.05 and VIP>1, and 13 odor components such as β-caryophyllene and limonene were hypothesized as the odor differential markers of Curcumae Radix decoction pieces of diffe-rent sources. The results showed that Heracles Neo ultra-fast gas phase electronic nose can well analyze the odor characteristics and rapidly and accurately discriminate Curcumae Radix decoction pieces of different sources. It can be applied to the quality control(e.g., online detection) in the production of Curcumae Radix decoction pieces. This study provides a new method and idea for the rapid identification and quality control of Curcumae Radix decoction pieces.
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Medicamentos de Ervas Chinesas/análise , Nariz Eletrônico , China , Raízes de Plantas/química , Limoneno/análise , Cromatografia Líquida de Alta PressãoRESUMO
ObjectiveIn order to find a fast odor-based method for the identification of sulfur fumigated Gastrodiae Rhizoma, an ultra-fast gas phase electronic nose technology was used to identify the odors of different degrees of sulfur fumigated Gastrodiae Rhizoma decoction pieces. MethodHeracles NEO ultra-fast gas phase electronic nose was employed to collect gas chromatograms of unsulfured and sulfured with different degrees of Gastrodiae Rhizoma decoction pieces, gas chromatograms were performed under programmed temperature (initial temperature of 40 ℃, 0.2 ℃·s-1 to 60 ℃, and then 4 ℃·s-1 to 250 ℃), the sample volume was 5 mL, the incubation temperature was 65 ℃ and incubation time was 35 min. Kovats retention index and the AroChemBase database were used for qualitative analysis, and stoichiometric analysis was performed on this basis. Principal component analysis (PCA), discriminant factor analysis (DFA) and partial least squares-discriminant analysis (PLS-DA) models were established to identify the Gastrodiae Rhizoma decoction pieces with different degrees of sulfur fumigation. ResultAccording to the comparative analysis of AroChemBase database, there were significant differences in the odor characteristics of sulfur fumigated and non-sulfur fumigated Gastrodiae Rhizoma, cyclopentane, acetone and heptane might be the odor components to distinguish the degree of sulfur fumigation in Gastrodiae Rhizoma decoction pieces. The identification index of PCA model was 81, the accumulative discriminant index of the discriminating factors was 92.09% in DFA model, the supervisory model interpretation rate of PLS-DA model was 0.963 and the predictive ability parameter was 0.956, indicating that PCA, DFA and PLS-DA models could well distinguish Gastrodiae Rhizoma decoction pieces with different sulfur fumigation degrees. ConclusionHeracles NEO ultra-fast gas phase electronic nose can be used as a rapid method to identify and distinguish Gastrodiae Rhizoma decoction pieces with different levels of sulfur fumigation. Meanwhile, it can provide a rapid, simple and green method and technology for identification of traditional Chinese medicine decoction pieces by sulfur fumigation.
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ObjectiveTo analyze the flavor substances and change rules of Rhei Radix et Rhizoma during the process of nine-time repeating steaming and sun-drying. MethodThe flavor response values of Rhei Radix et Rhizoma samples were obtained by using PEN3 electronic nose system. The data were processed and analyzed by principal component analysis (PCA), linear discriminant analysis (LDA) and Loadings analysis. ResultRhei Radix et Rhizoma processed with nine-time repeating steaming and sun-drying could be effectively distinguished into two categories as the sixth sample was the turning point. The samples steamed and dried for one to five times could be grouped into one category, the other four samples were obviously distinguished from them. The main flavor components reached the maximum response in the sample processed with six-time repeating steaming and sun-drying, and its response value of inorganic sulfur compounds was about 2.7 times that of the sample processed with one-time repeating steaming and sun-drying. In addition, compared with the raw products, the flavors of Rhei Radix et Rhizoma processed with nine-time repeating steaming and sun-drying and wine stewing changed significantly, and the response value of inorganic sulfur compounds in sample processed with nine-time repeating steaming and sun-drying was about 2.2 times that of raw products. From the perspective of flavor analysis, the response values of inorganic sulfur compounds and nitrogen-oxygen compounds in sample processed with nine-time repeating steaming and sun-drying were higher than those of wine-stewed products, and the two were not completely equivalent. ConclusionElectronic nose technology preliminarily clarifies the dynamic change rules of the flavor of Rhei Radix et Rhizoma during the process of nine-time repeating steaming and sun-drying from the flavor characteristics, and clarifies the difference between products processed with nine-time repeating steaming and sun-drying and wine-stewed products from the odor characteristics, which lays a foundation for revealing the processing principle of Rhei Radix et Rhizoma processed with nine-time repeating steaming and sun-drying.
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OBJECTIVE To establish the method for monitoring the dynamic changes of odor components in Cornus officinalis during processing . METHODS The decoction pieces of C. officinalis with different processing time were prepared by the wine steaming method . The dynamic changes of odor components were obtained by using ultra -fast gas electronic nose ;odor components were identified by comparing with AroChemBase database ;the dynamic changes of odor compounds were analyzed in combination with peak area ,and the chemical pattern recognition analysis were carried out . RESULTS A total of 12 common peaks of odor components were identified in the fingerprints of raw C. officinalis,and 21 in the fingerprints of decoction pieces of C. officinalis. Eight odor components with the high proportion of peak area during processing were ethanol , isopropyl alcohol , 2- methylpropylaldehyde,ethyl acetate ,2-methylbutanal,isoamyl alcohol ,2-hexanol and furfural ,among which ,the peak areas of ethanol,isoamyl alcohol and 2-hexanol showed a trend of first increasing and then decreasing ;at 24 h of processing ,their peak areas were still higher than those of raw products . The peak areas of ethyl acetate ,2-methylbutanal and furfural nearly increased with the increase of processing time . Variable importance in projection of above eight odor components were all greater than 1. CONCLUSIONS The method is established for monitoring the dynamic changes of odor components of C. officinalis during processing. Eight odor components such as ethanol can be used as monitoring indicators of C. officinalis dring processing .
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ObjectiveTo analyze the quality changes of Platycladi Semen before and after the deterioration of moth-eaten and rancidity during storage. MethodFour types samples of Platycladi Semen, including normal, moth-eaten, oxidative rancidity and hydrolytic rancidity, were determined for volatile components, odor, and taste based on headspace solid phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) and electronic sensory techniques such as electronic nose and electronic tongue. Volatile components were identified by searching the database and manual comparison, the odor and taste were determined by the response values of the electronic nose and electronic tongue sensors, and the difference between samples before and after deterioration was studied by multivariate statistical analysis. ResultA total of 85 compounds were identified in Platycladi Semen samples. Compared with the normal samples, the number of volatile compounds in samples after hydrolytic rancidity decreased by 5, the number of volatile compounds in samples after moth-eaten and oxidative rancidity increased by 1 and 21, respectively. Aldehydes and acids accounted for majority of types. Among them, the contents of N-hexanoic acid, hexanal and propionic acid in the samples of oxidative rancidity reached 11.49%, 10.21% and 7.52%, which became the key indicators of rancidity. There was significant variance among the odor components corresponding to W1W, W2W and W1S sensors by electronic nose analysis. It was indicated that the value of sourness in deteriorated samples generally increased by mean of electronic tongue analysis. Compared with normal samples, the moth-eaten samples had changed slightly and rancidity samples had changed significantly especially oxidative rancidity samples of volatile components, odor and taste by multivariate statistical analysis. ConclusionIn terms of Platycladi Semen, the oxidative rancidity caused by nature storage for 12 months has the greatest impact on the quality. Therefore, it should be mainly to prevent oxidative rancidity to ensure the quality of Platycladi Semen.
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Objective:To detect the common pathogenic bacteria in rat wounds using electronic nose so as to explore the feasibility of electronic nose for rapid screening of pathogenic bacteria in clinic.Methods:The wound was cutted from the left and right side of the psoas muscle of 45 SD rats. The type of standard bacterial fluids applied to the wound was divided into Staphylococcus aureus group, Escherichia coli group, Pseudomonas aeruginosa group, Acinetobacter baumannii group and Klebsiella pneumoniae group according to the random number table, with 9 mice per group. Three days later, the wound pus was sent to culture. Five standard bacterial fluids were detected by electronic nose, and the overall recognition rate and individual recognition rate of standard bacterial fluids were calculated by neural network (BP). The wound pus in each group was detected by electronic nose to visually compare the overlap degree of the radar map of the wound pus with the standard bacterial fluid characteristic radar map. The detection rate of wound pus in each group by electronic nose was compared. The wound pus in each group was submitted for examination, and the clinical detection rate of wound pus in each group was compared. The consistency was compared between electronic nose test and clinical test.Results:The overall BP identification rate of five standard bacteria liquid was 93.2%. The BP single identification rate of the Staphylococcus aureus, Escherichia coli and Klebsiella pneumoniae reached over 99.0%, and was more than 88.0% for Pseudomonas aeruginosa and Acinetobacter baumannii. The radar pattern of wound pus was highly overlapped with the characteristics of radar pattern of standard bacterial fluid. The detection rate of wound pus by electronic nose was the highest (100.0%) in Pseudomonas aeruginosa group and Escherichia coli group, followed by 88.9% in Klebsiella pneumoniae group and 72.2% in Pseudomonas aeruginosa group and Acinetobacter baumannii group. Using electronic nose, the detection rate in Pseudomonas aeruginosa group and Acinetobacter baumannii group was significantly different from that in Staphylococcus aureus group and Escherichia coli group ( P<0.05). The clinical detection rate of wound pus was 100.0% in Staphylococcus aureus group, Escherichia coli group and Klebsiella pneumoniae group, 94.4% in Pseudomonas aeruginosa group and 66.7% in Acinetobacter baumannii group. The clinical detection rate in Acinetobacter baumannii group differed significantly compared to that in Staphylococcus aureus group, Escherichia coli group and Klebsiella pneumoniae group ( P<0.05), while there was no significant difference between Acinetobacter baumannii group and Pseudomonas aeruginosa group ( P>0.05). Comparison of detection rate of wound pus between electronic nose and clinic examination showed a Kappa coefficient of 0.475. Conclusions:The animal wound pus detected by electronic nose can obtain a feature map with high repeatability compared to the standard bacterial fluid. The electronic nose detection has a medium degree of consistency with clinical detection, providing an experimental basis for the feasibility of using electronic nose to rapidly screen types of pathogenic bacteria.
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Objective:To establish a new fast and accurate method for identifying the authenticity and specifications of Fritillariae Cirrhosae Bulbus based on electronic nose technology, and to discuss the feasibility of this technology in the identification of decoction pieces. Method:Fritillariae Cirrhosae Bulbus was used as the research object, 80 batches of samples to be tested were collected, and the olfactory sensory data of the electronic nose were taken as independent variables (<italic>X</italic>), the results of the method contained in the 2020 edition of <italic>Chinese Pharmacopoeia</italic> were taken as the focus, and the traditional empirical identification results were used as benchmarking information (<italic>Y</italic>). Four chemometric methods, including discriminant analysis (DA), least square support vector machine (LS-SVM), principal component analysis-DA (PCA-DA) and partial least squares-DA (PLS-DA), were used to establish the identification model [<italic>Y</italic>=<italic>F</italic>(<italic>X</italic>)] of authenticity and commodity specifications of Fritillariae Cirrhosae Bulbus, respectively. Wherein, the identification accuracy and time-consuming was taken as indicators to discuss the results. Result:After cross-verification by leave-one-out method, the correct rates of the above four models were 93.75%, 91.25%, 95.00% and 95.00%, respectively, and the PCA-DA and PLS-DA identification models were the best in terms of authenticity identification. In specification identification, the correct rates of these four models were 86.67%, 88.00%, 89.33% and 68.00%, respectively, and the PCA-DA identification model was the best. The electronic nose had a high accuracy in the identification of authenticity and specification model, and the time consuming was relatively short. Conclusion:Electronic nose technology can identify Fritillariae Cirrhosae Bulbus accurately and quickly, and has significant advantages in terms of timeliness and correct judgment rate.
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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.
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Nariz Eletrônico , Cromatografia Gasosa-Espectrometria de Massas , Odorantes/análise , Sêmen/química , Microextração em Fase Sólida , Compostos Orgânicos Voláteis/análiseRESUMO
This study was designed to investigate the flavor and taste change rules of Sophora Flavescentis Radix processed using the ancient classical method documented in Master Lei's Discourse on Medicinal Processing(Lei Gong Pao Zhi Lun). The Sophora Flavescentis Radix pieces and the corresponding test samples in each processing stage were first prepared based on the processing method for Sophora Flavescentis Radix recorded in Master Lei's Discourse on Medicinal Processing(Lei Gong Pao Zhi Lun). Then the flavors and tastes of Sophora Flavescentis Radix test samples undergoing the soaking in rice-washed water, washing with clean water, and steaming for different time were compared with the electronic nose and tongue. The results showed that in the preparation of Sophora Flavescentis Radix with the ancient method, such processes as soaking in rice-washed water and washing with clean water had no significant influences on the flavor, which, however, was weakened by steaming. In terms of the taste, soaking with rice-washed water enhanced the bitter taste of Sophora Flavescentis Radix, which remained unchanged after being washed with the clean water. The steaming would also diminish the bitter taste, making it taste similar to the original Sophora Flavescentis Radix medicinal materials. During the steaming for six to eight hours, the flavor did not vary significantly over time, while the bitter taste was first weakened and then intensified. The bitter taste of Sophora Flavescentis Radix steamed for six hours was similar to that steamed for eight hours. In addition, the differences in flavor and taste between Sophora Flavescentis Radix pieces processed by the ancient method in Master Lei's Discourse on Medicinal Processing(Lei Gong Pao Zhi Lun)and those by the modern method in the 2020 edition of Chinese Pharmacopoeia were analyzed. The findings demonstrated that the flavor of Sophora Flavescentis Radix pieces prepared by the ancient method was weaker than that by the modern method, whereas the bitter taste showed the opposite trend. The exploration on the flavor and taste change rules of Sophora Flavescentis Radix in its preparation by the ancient classical method and the differences in flavor and taste between Sophora Flavescentis Radix decoction pieces prepared by ancient and modern methods will lay a foundation for further elucidation of the scientific connotation of the ancient processing method and the medication principles of Sophora Flavescentis Radix in both ancient and modern times.
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Medicamentos de Ervas Chinesas , Nariz Eletrônico , Raízes de Plantas , Sophora , PaladarRESUMO
OBJECTIVE:To esta blish the m ethod for identifying Schizonepeta tenusfolia from different habitats based on odor information. METHODS :The odor of S. tenusfolia from different habitats were identified by Heracles Ⅱ ultra-fast gas phase electronic nose. Qualitative analysis was conducted according to obtained chromatographic information combined with AroChemBase database and Kovats retention index qualitative database. Principle component analysis (PCA)and discriminant factor analysis (DFA)were conducted by using Alpha Soft V 14.2 software,and cluster analysis (CA)was performed with SPSS 22.2 software. RESULTS :There were 16 common peaks in 15 batches of S. tenusfolia from different habitats. After comparison with AroChemBase database and Kovates retention index qualitative database ,a total of 13 possible components were obtained. The possible components and sensory description information of S. tenusfolia from different habitats were basically the same ,but only the content was different. The chromatographic peak intensities of common peak No. 2 were in descending order as Anhui > Gansu>Henan>Hebei>Jiangsu,the chromatographic peak intensities of common peak No. 6 were in descending order as Anhui > Hebei>Gansu≈Henan>Jiangsu,the chromatographic peak intensities of common peak No. 9 were in descending order as Anhui > Gansu>Henan>Jiangsu>Hebei,the chromatographic peak intensity of common peak No. 13 were in descending order as Anhui ≈ Gansu>Hebei>Jiangsu>Henan,which represented the chromatographic peak intensity of methyl formate (peak No. 2),α-pinene (peak No. 6),3-nonone(peak No. 9)and α-terpineol(peak No. 13)were significantly different due to the change of habitats. PCA results showed that the cumulative contribution rate of the first two principal components was 96.807%. Results of DFA showed that contribution rates of discriminant factor 1 and discriminant factor 2 were 92.089% and 3.982%. CA results showed that when the distance was 10,15 batches of samples could be clustered into 3 categories,B1-B5 and J 1-J3 into one category ,A1-A3 into one category ,G1,G2,N1 and N 2 into one category. The results were basically consistent with those of PCA and DFA. CONCLUSIONS:Ultra-fast gas phase electronic nose technology can be used to identify S. tenusfolia from different habitats rapidly. Methyl formate ,α-pinene,3-nonone and α-terpineol may be the key factors to distinguish S. tenusfolia from different habitats.
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OBJECTIVE: Pseudostellaria Radix, due to its sketchy description and individual difference during the odor evaluation, fails to come to researchers' attention. To analyze the odor of the Pseudostellaria Radix samples from different habitat processing methods and areas, and apply electronic nose technology to creating a new method for the determination of Pseudostellaria Radix. METHODS: According to the response values obtained by using electronic nose technology, two multivariate statistical methods to the data to distinguish the samples collected from different areas and habitat processing methods were applied. From the aspect of response values, the sunned Pseudostellaria Radix after boiling get lower values than the sunned ones, while the values of the samples from different producing origins vary very slightly. RESULTS: The results of the multivariate statistical methods show that principal component analysis (PCA) can differ the sunned samples from the sunned ones after boiling. With regard to the sunned ones after boiling, there is no significant difference among the three boiling time groups from 30 s to 120 s. While the two discrimination models constructed during the discriminant factor analysis (DFA) have respectively favorable identification ability in habitat processing methods and producing areas. CONCLUSION: The electronic nose technology can be used to express the odor of Pseudostellaria Radix, and in combination with multivariate statistical methods, it can differentiate Pseudostellaria Radix from different areas and habitat processing methods.
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Objective:To analyze and compare the fishy components in raw, stir-fried, liquorice-processed, vinegar-processed and wine-processed products of Pheretima aspergillum, and explore the material basis and processing principle of fishy smell of P. aspergillum. Method:Heracles Ⅱ ultra-fasted gas chromatography electronic nose technology combined with chemometrics was used for the overall analysis of volatile components in raw P. aspergillum and its processed products. Headspace gas chromatography-mass spectrometry (HS-GC-MS) was used to analyze and identify the volatile compositions in the raw products and processed products. Gas chromatographic conditions were as following:temperature program (initial temperature at 60 ℃, kept for 5 min, up to 120 ℃ with the heating rate of 3 ℃·min-1, and then up to 230 ℃ with the heating rate of 10 ℃·min-1 and finished), the inlet temperature at 280 ℃, high purity helium as the carrier gas, the flow rate of 1.0 mL·min-1, the split ratio of 20∶1. Mass spectrum conditions were as following:electron impact ionization (EI), electron collision energy of 70 eV, ion source temperature of 230 ℃, quadrupole temperature at 150 ℃, scanning range of m/z 50-550. The relative content of each component was calculated by peak area normalization. Result:Principal component analysis (PCA) and discriminant factor analysis (DFA) of the electronic nose showed that the raw products and its processed products could be clearly distinguished from each other. Among them, the difference between raw products and stir-fried, liquorice-processed products was small, but the difference between raw products and vinegar-processed, wine-processed products was large. A total of 25, 27, 22, 26 and 33 components were respectively identified from raw, stir-fried, liquorice-processed, vinegar-processed and wine-processed products of P. aspergillum, there were 13 common components in these products, including 4 aldehydes (isovaleraldehyde, 2-methylbutyraldehyde, hexanal, benzaldehyde), 2 ketones (2-heptanone, 2-tridecanone), 1 carboxylic acid (lauric acid), 4 heterocyclic compounds (2-methylpyrazine, 2,5-dimethyl pyrazine, 2-pentylfuran, 2-ethyl-6-methyl pyrazine), 1 amine (trimethylamine) and 1 alcohol (1-octen-3-ol). Conclusion:The odorous components in the raw products are mainly derived from aldehydes (isovaleraldehyde, 2-methylbutyraldehyde, isobutyraldehyde, 2-ethylhexanal, hexanal) and amines (trimethylamine). Odorous components of P. aspergillum can be reduced effectively by stir-fried and liquorice, vinegar, wine processing, while flavoring substances can be increased by wine processing to cover its ugly odor. This paper can provide scientific basis for the deodorization of P. aspergillum by processing, and also provide reference for the analysis and correction of ugly odor of other animal medicines.
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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.
Assuntos
Medicamentos de Ervas Chinesas , Nariz Eletrônico , Medicina Tradicional Chinesa , Sêmen , Máquina de Vetores de SuporteRESUMO
This study aimed to establish a rapid and accurate method for identification of raw and vinegar-processed rhizomes of Curcuma kwangsiensis, in order to predict the content of curcumin compounds for scientific evaluation. A complete set of bionics recognition mode was adopted. The digital odor signal of raw and vinegar-processed rhizomes of Curcuma kwangsiensis were obtained by e-nose, and analyzed by back propagation(BP) neural network algorithm, with the accuracy, the sensitivity and specificity in discriminant model, correlation coefficient as well as the mean square error in regression model as the evaluation indexes. The experimental results showed that the three indexes of the e-nose signal discrimination model established by the neural network algorithm were 100% in training set, correction set and prediction set, which were obviously better than the traditional decision tree, naive bayes, support vector machine, K nearest neighbor and boost classification, and could accurately differentiate the raw and vinegar products. Correlation coefficient and mean square error of the regression model in prediction set were 0.974 8 and 0.117 5 respectively, and could well predict curcumin compounds content in Curcuma kwangsiensis, and demonstrate the superiority of the simulation biometrics model in the analysis of traditional Chinese medicine. By BP neural network algorithm, e-nose odor fingerprint could quickly, conveniently and accurately realize the discrimination and regression, which suggested that more bionics information acquisition and identification patterns could be combined in the field of traditional Chinese medicine, so as to provide ideas and methods for the rapid evaluation and stan-dardization of the quality of traditional Chinese medicine.