The eighteen incompatible medicaments is the incompatibilities in traditional Chinese medicine (TCM). However, in some special occasion, the incompatible medicaments can also be used in one prescription in the clinical applications. In order to reveal the theoretical basis for applications of incompatible medicaments in prescriptions, we analyzed ancient prescriptions and found that there are contrary Chinese herbal nature combina-tions (CHNCs) which have the same meridian tropism as well as the opposite nature and taste in prescriptions. In clinical applications, one of the non-contrary CHNCs was selected as the main response to syndrome differentia-tion. The contrary CHNCs in the same meridian tropism were used to restrict each other and therefore have the protective effects. The features found in this paper will be beneficial to further research on the rational applica-tion of incompatible medicaments.

Chinese herbal nature combination (CHNC) is the particular combination of nature, taste and channel tropism, which can be used to express the effect of Chinese herbal medicine in the clinical application concisely. The complex system model for the relationship between CHNC and viscera was constructed in this paper based on the thinking model of viscera theory. The model is able to reveal the functional features of CHNC. The model will promote research on the relationship between CHNC and viscera and provide new ideas for clinical applications of CHNC.

This study was aimed to explain the relationship between chemical component and therapy objective and to identify effective component group (ECG). The objective of this study is to build a new method to identify the ECG. Traditional Chinese medicine (TCM) formula and one of its treated diseases were selected as the re-search object. The entity grammar systems (EGS) were used as the theoretical framework. A grammatical method for ECG identification was constructed. The component-disease relationship was inferred and the ECG was identi-fied with these inference results. In this paper, 16 compounds which act to 12 proteins in Type 1 diabetes melli-tus (T1D) disease network were identified from Bai-Hu Tang plus Xiao-Ke Fang and 9 chemical compounds were determined as the candidate effective components group. The results indicated that this method can be used to identify ECG and provide a new way to elucidate the molecular mechanism of TCM formula.

Gastrodia elatais graded as top medication in theShen Nong’s Herbal Classic. It was mainly distributed in southwest China. Its quality varied with geographical location. And the quality difference between wild and cultivated sample was extreme. Identifications using traditional methods were unable to accurately distinguish the quality ofG. elata. Therefore, near-infrared (NIR) spectroscopy combined with pattern recognition method was used to distinguish the quality ofG. elata from different geographical locations as well as cultivated or wild. The results demonstrated that using NIR spectroscopy combined with multiclass classification algorithm, the geographical location ofG. elata can be accurately distinguished. The prediction accuracy can reach as high as 94.3% and 96.4% for both applications. Besides, the classification model was built without preprocessing; hence, it can be extended to be applied on-site.

Near infrared chemical imaging (NIR-CI) is an emerging technology for rapidly analyzing the critical quality attribute of Chinese materia medica (CMM). It integrates NIR spectroscopy with chemical imaging. In this paper, it provided a systematic introduction to NIR-CI, such as the core part of instrument, the reliability, transformation, analysis and application of high-dimensional data acquisition. In addition, current studies of NIR-CI application in pharmaceutical field were analyzed. Finally, future opportunities and challenges of NIR -CI applications in the quality control of CMM preparation were prospected.

This study was aimed to establish the classification method of Chinese herbal medicine based on feature parameters extracted from images of herbal transverse section, in order to explore the feasibility of automatic identi-fication method of herbal medicine. The extracted 26 parameters of 18 herbal medicine images by gray-level co-oc-currence matrix and grayscale gradient matrix were used as the basic data set. And the minimum covariance determi-nant (MCD) was used to delete the outliers. A total of 18 identification models were established using the native Bayes method and BP neural network methods. The results showed that the average correct rates of models were 90%. It was concluded the feasibility of using these models in the establishment of the automatic identification method of herbal medicines. It provided new technologies for the quantitative, scientific and objective identification of Chinese herbal medicine.

This study was aimed to compare the difference of parameters of texture feature in the transverse section images of the same and different Chinese herbal medicine. A total of 26 parameters of herbal medicines were ex-tracted by gray-level co-occurrence matrix and grayscale gradient matrix. The graph of mutative curve was drawn. And differences of 26 parameters of texture feature in the same and different Chinese herbal medicine were com-pared. The results showed that parameters of texture feature extracted by gray-level co-occurrence matrix and grayscale gradient matrix had similarities and differences in the same and different Chinese herbal medicine. It was concluded that the method can show the texture feature scientifically and quantitatively. It also laid a foundation for the establishment of an automatic identification model, but the parameters still had instability. All these remind us to find some parameters which can show the details of texture feature preferably, thus perfect the extracted method of texture features in Chinese herbal medicine.

This study was aimed to explore the impact of integrality of Chinese herbal medicine on parameters of tex-ture feature in transverse section images. Three Chinese herbal medicine of Semen Arecae, Radix et Rhizoma Rhei and Radix A tractylodis Macrocephalae with different texture features were taken as research materials. Parts of Chi-nese herbal medicine were cut off from the whole by equal proportions. The 26 parameters were extracted by gray-level co-occurrence matrix and grayscale gradient matrix. The similarities and differences of 26 parameters of texture feature in the parts and whole, rectangular and fan-shaped Chinese herbal medicine were compared. The results showed that parameters of Semen A recae and Radix et Rhizoma Rhei with radial or annular texture had better con-sistency in whole and fan-shaped parts. Parameters of Radix A tractylodis Macrocephalae with irregular texture fea-ture were approximately the same in the whole and rectangular parts. It was concluded that whether parameters of texture features in parts Chinese herbal medicine can present the whole were related to its texture feature and the shape of the parts. This study provided the basis for collection of Chinese herbal medicine when sampling images. It also laid a foundation for the extraction of accurate parameter of texture feature.

This study was aimed to investigate the impact of rotation sampling on feature parameters of texture im-ages of Chinese herbal medicine. Four Chinese herb medicine with various shape and texture feature were taken as research materials. Images of complete and incomplete herbal medicine were collected respectively after different ro-tation angles. The 26 parameters were extracted by gray-level co-occurrence matrix and grayscale gradient matrix. The impact of rotation sampling on feature parameters was investigated through analysis of variation tendency and range of 26 parameters. The results showed that if the Chinese herbal medicine was complete, the 26 parameters were not impacted by the rotation angle, whereas the 26 parameters were impacted by the rotation angle and the im-pact will be more obvious when the shape of Chinese herb medicine was irregular. It was concluded that in order to get a high quality of images and construct a well identification model based on the parameter of texture features, we must consider the impact of rotation angle on the parameters to Chinese herbal medicine with various shapes and tex-ture features.

Digitalization is an important method for the objectification and quantification of quality control on Chi-nese herbal medicine. To solve the problem of texture online visualization of Chinese herbal medicine and the estab-lishment of automatic identification method based on the texture, 12 Chinese herbal medicines were selected to cap-ture the images of their transverse sections. A total of 11 features were extracted from images using Gray-level Co-occurrence Matrix (GLCM) method. Through analyzing the influence of distances and angles between pixels on identi-fication results, it was concluded that when the distance was d = 3 and the angle was ? = 0o, the features extracted were suitable for expressing the texture of the transverse sections. The results indicated the feasibility of establishing the automatic identification method on Chinese herbal medicine based on image of transverse section. It will provide new technologies for the objectification and quantification of identification on Chinese herbal medicine.