MacMillan Underwood (beamturnip7)

f the influence of different microorganisms on the excellent traits formation of " sweating" Magnolia Officinalis Cortex.The study aimed to investigate the effect of processing on lectin protein in four toxic Chinese medicines tubers of Pinellia ternata,P. pedatisecta,Arisema heterophyllum and Typhonium giganteum. Western blot was used to semi-quantitatively analyze the content of lectin in the four kinds of toxic Chinese medicines and their different processed products. Raw products and lectin were treated by heating or soaking in ginger juice or alum solution. The effects of different excipients and the heating methods on lectin proteins were investigated. The results showed that the content of lectin in raw products of P. pedatisecta,P. ternata,A. heterophyllum,and T. giganteum were 7. 3%,4. 9%,2. 7%,2. 3%,respectively. And the content of lectin in Pinelliae Rhizoma praeparatum cum alumine was 0. 027%. Lectin was not detected in the Pinelliae Rhizoma Praeparatum cum Zingibere et Alumine,Arisaematis Rhizma Praeparatum and Typhonii Rhizoma Praeparatum,which indicated that processing could significantly reduce the content of active lectin in raw products. The results also showed that with the prolongation of soaking and heating time,the content of lectin in raw products decreased gradually,while the content was almost unchanged when soaked in ginger juice alone. The effects of different excipients and heating on lectin were the same as those on raw products. Therefore,the method with alum soaking and heating can reduce the content of active lectin,which is the key to reduce the toxicity of toxic Chinese medicines. In this paper,Western blot was used to study the content of toxic protein in Araceae toxic Chinese medicines as an evaluation method of the processing degree.This paper constructs a prediction model of material attribute-tensile strength based on principal component analysis-radial basis neural network( PCA-RBF),in order to predict the formability of traditional Chinese medicine tablets. Firstly,design Expert8. 0 software was used to design the dosage of different types of extracts,the mixture of traditional Chinese medicine with different physical properties was obtained,the powder properties of each extract and the tensile strength of tablets were determined,the correlation of the original input layer data was eliminated by PCA,the new variables unrelated to each other were trained as the input data of RBF neural network,and the tensile strength of the tablets was predicted. The experimental results showed that the PCA-RBF model had a good predictive effect on the tensile strength of the tablet,the minimum relative error was 0. 25%,the maximum relative error was2. 21%,and the average error was 1. 35%,which had a high fitting degree and better network prediction accuracy. This study initially constructed a prediction model of material properties-tensile strength of Chinese herbal tablets based on PCA-RBF,which provided a reference for the establishment of effective quality control methods for traditional Chinese medicine preparations.A minimal data set( MDS) for soil fertility evaluation of Chrysanthemum plantation areas of Macheng city was established by principal component analysis( PCA) combined with Norm values of soil fertility indices and correlation coefficients among indices. A radar map was used to visually reflect the fertility level of individual indicators. Then,the comprehensive index model was used to calculate the soil fertility quality index( SFQI),and the values of SFQI was used to cluster,and the results showed that MDS was composed of five indicators organic matter( OM),total phosphate( TP),available phosphorus( Av P),available magnesium( Av Mg) and available ferrum( Av Fe). Radar maps showed that the fertility of available phosphorus( Av P) and available copper( Av Cu) was mostly different in the two town,and the fertility of available ferrum( Av Fe) is smallest different. Except for the effect