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.

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.

For solving the problem that common similarity algorithms are insensitive to the relative differences of different chromatographic fingerprints data, this paper improved the algorithms of improved extent similarity), which named new improved extent similarity. It was confirmed that new improved extent similarity could distinguish) the samples with the same total difference and different distribution of relative differences. by applying) the similarity algorithm to simulated data and the chromatographic fingerprints of nine batches Rukuaixiao tablets. New improved extent similarity could reflect the relative differences of peak areas more sensitively when the relative differences of common peak areas was less than 100%. The result indicates that new improved extent similarity can reflect the large deviation from the established proportion of components, which can be applied to the control of the fluctuation of the established proportion of effective components and the process quality control of Traditional Chinese Medicine .

The literature study and survey revealed existed problems and factors such as the difficulties to maintain quality of traditional Chinese medicine (TCM), sustainable development, homogenization and indeterminacy of clinical orientation diagnosis, lack of favorable evidence-based medicine and pharmacoeconomics data to support, lack of ev-idence of safety evaluation, which restrict the development of TCM enterprises. Based on problems and factors men-tioned above, recommendations were made on the healthy development of TCM enterprises, which include guarantee of the quality of TCM herbs and the sustainable development of its resource; conduct systematic evidence-based pharmacoeconomic research, identify the clinical orientation; carry out safety assessment systematically, improve the specification; improve clinical effectiveness-oriented quality standards.

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.