Application research of entropy weight-based grey systematic theory in quality evaluation of Angelicae Sinensis Radix slices / 中国中药杂志

In order to discuss the "entropy weight method" for weighting various indicators in the comprehensive evaluation of Angelicae Sinensis Radix slices(ASR), the quality of ASR was comprehensively evaluated by entropy weight-based gray systematic theory and cluster analysis. In this study, the contents of ferulic acid, volatile oil, polysaccharide, alcohol extract, water extract, moisture, total ash and acid-insoluble ash in 44 batches of ASR from different sources were determined. The entropy weight method was used for objective weighting. With relative correlation(r_i) as a measure, a multi-index comprehensive evaluation model was constructed for the quality of ASR. The results showed that the relative correlation value of 44 batches of ASR ranged from 0.301 9 to 0.662 9. There were certain differences in the quality of ASR from different sources. The ASR S1-S8, traceable and standardized in processing techno-logy, showed a high relative correlation degree and high quality ranking, indicating that the implementation of systemic management of the production chain of Chinese herbal pieces was beneficial to the quality control of ASR. The quality evaluation results of 44 batches of ASR were consistent with those of traditional geo-authentic habitats for ASR and the mainstream varieties of ASR on market, and basically consistent with the results of cluster analysis. This study suggests that the gray systematic theory based on the entropy weighting method can be used for the quality evaluation of ASR. The objective weighting of the entropy weight method improves the reliability of the gray correlation method and the scientificity of ASR quality evaluation.

Far infrared drying characteristics and kinetics of Angelicae Sinensis Radix slices / 中草药

Objective: Taking Angelicae Sinensis Radix (ASR) slices as the research object, the far infrared drying characteristics and kinetic model of ASR slice were explored, which provided a theoretical basis for improving the quality of dry products and establishing a suitable processing method. Methods: The far-infrared drying technique was applied to the drying of ASR. The far-infrared drying characteristics and dry product quality of ASR were studied under different drying temperature, slice thickness and irradiation height, and the Weibull function was used to fit the drying curve. The quantitative relationship between test factors and model parameters were established. Results: With the increase of drying temperature and the decrease of the slice thickness and the irradiation height, the water ratio was decreased significantly, and the drying rate was increased significantly. The far-infrared drying process of the ASR slice obeyed the Weibull distribution function (R2 = 0.983 34-0.999 34, χ2 = 0.001 3-0.006 5), both the size parameter and the shape parameter were related to the drying temperature, slice thickness and irradiation height; The interval for estimating the water diffusion coefficient (Dcal) was 4.698 × 10-11-2.084 × 10-10 m2/s. The effective moisture diffusion coefficient (Deff) was in the range of 3.891 × 10-9-2.179 2 × 10-8 m2/s, both of which tended to increase with the increase of drying temperature, slice thickness and irradiation height. Compared with dry products from hot-hair drying, the color difference and water activity of far infrared drying were smaller, and it was easier to retain ferulic acid and volatile oil in ASR. Scanning electron microscopy analysis of the microstructure of dry products under different drying conditions showed that far infrared increased the interior of ASR slices. The number of micropores was increased, the cells were arranged more neatly, so as to increase the rate of thermal mass migration during the drying process and reduce the drying time. Conclusion: The Weibull distribution function can predict the water migration law of the drying process of ASR. It is of great significance for the prediction of the drying process of ASR and the process optimization.