Simultaneous qualitative identification of all medicinal herbs in Zaoren Anshen capsule by thin-layer chromatography

The holistic characterization and quality control of all the medicinal herbs of proprietary Chinese medicines(PCMs)are of great significance to ensure their safety,efficacy,and consistency.Thin-layer chromatography(TLC),a simple and classic approach for qualitatively characterizing and examining quality markers of natural products,has been widely used in the characterization and quality control of traditional Chinese medicines.Zaoren Anshen(ZRAS)capsule,prepared from three medicinal herbs of fried Ziziphi Spinosae Semen,Salvia Miltiorrhiza Radix et Rhizoma,and vinegar-processed Schisandrae Chinensis Fructus,is a famous PCM in China for the treatment of insomnia,amnesia,and dizziness in clinical practice.However,no effective method is available so far for simultaneous identification and examination of all the three medicinal herbs of ZRAS capsule.In the present study,we developed a TLC method via twice-development and visualization by UV light or chromogenic agent,which could be used for simultaneous qualitative identification of all the three medicinal herbs of ZRAS capsule in one plate.Moreover,the sample preparation method was optimized.The developed TLC method was rapid,simple,low-cost,and effective,and thus it could be used for quality control of ZRAS capsule.

Research on Detection of Food additives Based on Terahertz Spectroscopy and Analytic Hierarchy Process

Terahertz time-domain spectroscopy is a kind of far-infrared spectroscopy technology,and its spectrum reflects the internal properties of substances with rich physical and chemical information,so the use of terahertz waves can be used to qualitatively identify food additives containing nitrogen elements.Analytic hierarchy process(AHP)was originally used to solve evaluation-type problems,and this paper introduces it into the field of terahertz spectral qualitative analysis,proposes a terahertz time-domain spectral qualitative identification method combined with analytic hierarchy process,and verifies the feasibility of the method by taking four common food additives(xylitol,L-alanine,sorbic acid,and benzoic acid)and two illegal additives(melamine,and Sudan Red No.I)as the objects of study.Firstly,the collected terahertz time-domain spectral data were pre-processed and transformed into a data set consisting of peaks,peak positions,peak numbers and overall trends;then,the data were divided into comparison and test sets,and a qualitative additive identification model incorporating analytic hierarchy process was constructed and parameter optimisation was performed.The results showed that the qualitative identification accuracies of additives based on single factors,i.e.,overall trend,peak value,peak position,and peak number,were 80.23%,70.93%,67.44%,and 40.70%,respectively,whereas the identification accuracy of the analytic hierarchy process qualitative identification method based on multi-factors could be improved to 92.44%.In addition,the fuzzy characterisation of the absorption spectrum data was binarised in the data pre-processing stage and used as the base data for the overall trend,and the recognition accuracy was improved to 94.19%by combining the fuzzy characterisation method of such data with the hierarchical analysis qualitative recognition model.The results show that it is feasible to use terahertz technology to identify different varieties of additives,and this paper constructs a hierarchical analytical qualitative model with better effect,which provides a new means for food additives detection,and the method is simple in steps,with a small demand for samples,which is suitable for the rapid detection of small samples.

Logging-based assessment of low-resistivity oil zones:A case study from Sudan

The reservoirs in the N oilfield in Sudan feature a complex sedimentary environment,which has led to a widespread development of low-resistivity oil zones,accounting for as high as 37%of the total oil zones.In this case,a large number of oil zones will be misinterpreted using conventional methods.Based on the analysis of the core data and logging curves of the study area,this study concludes that the lowresistivity oil zones are formed mainly due to the high irreducible water saturation caused by the high content of illite and smectite and complex pore structure,the additional electrical conductivity induced by clay minerals,and the difference in formation water salinity between the oil zones and water zones.Furthermore,four methods are proposed to qualitatively identify these oil zones and water zones,namely the relationship analysis of five reservoir properties,cross-plotting of sensitive parameters,analysis of pressure testing data,and multi-well correlation.Furthermore,the study quantitatively calculates the initial oil saturation using the capillary pressure data,thus avoiding the conventional empirical saturation formulas depending on electrical resistivity and solving the difficulty in calculating oil saturation of low-resistivity oil zones.Finally,precise logging processing and interpretation of 95 wells in the study area are conducted using the above-mentioned comprehensive assessment system for low-resistivity oil zones.As a result,59 oil zones are newly discovered in 43 wells.Moreover,it is recommended that 17 oil zones in 12 wells should be tested,of which 11 oil zones have been tested as recommended,all proven to be high production oil zones after perforation.The coincidence rate of logging interpretation increases from 75%to 94.3%,and the original oil in place(OOIP)increases by 57.42 million barrels.All these indicate that the assessment system proposed is suitable for low-resistivity zones.