Artificial neural network techniques to predict the moisture ratio content during hot air drying and vacuum drying of Radix isatidis extract

Background:To predict the moisture ratio of Radix isatidis extract during drying.Methods:Artificial neural networks were designed using the MATLAB neural network toolbox to produce a moisture ratio prediction model of Radix isatidis extract during hot air drying and vacuum drying,where regression values and mean squared error were used as evaluation indexes to optimize the number of hidden layer nodes and determine the topological structure of artificial neural networks model.In addition,the drying curves for the different drying parameters were analyzed.Results:The optimal topological structure of the moisture ratio prediction model for hot air drying and vacuum drying of Radix isatidis extract were“4-9-1”and“5-9-1”respectively,and the regression values between the predicted value and the experimental value is close to 1.This indicates that it has a high prediction accuracy.The moisture ratio gradually decreases with an increase in the drying time,reducing the loading,initial moisture content,increasing the temperature,and pressure can shorten the drying time and improve the drying efficiency.Conclusion:Artificial neural networks technology has the advantages of rapid and accurate prediction,and can provide a theoretical basis and technical support for online prediction during the drying process of the extract.

A valid evaluation method for UPLC fingerprint analysis and moisture ratio prediction model:application to microwave vacuum drying of Radix isatidis extract

Background:Drying is a necessary component of traditional Chinese medicine extracts.The heating principle of microwave vacuum drying is different from that of the conventional heat method.However,at present,there is paucity of information on the drying process of traditional Chinese medicine extract by microwave vacuum drying,and the results of such process are unclear.Methods:To study the dynamic changes in the chemical characteristics of microwave vacuum drying under different drying conditions,ultrahigh-performance liquid chromatography fingerprint profiles were established using Radix isatidis extract as a model drug and analyzed using similarity analysis,partial least squares-discriminant analysis,and semi-quantitative analysis.In addition,a backpropagation artificial neural network model was developed to predict the moisture ratio of the drying process.Results:Qualitative results showed that the similarity between different drying conditions was greater than 0.95,and 2 amino acid components(peaks 5 and 6)affected by process fluctuations were screened out.The quantitative results showed that the mass concentration of component 1 fluctuated after drying,while that of component 2 increased.The optimal backpropagation artificial neural network model structure used to predict the moisture ratio was 5-4-1,with regression and mean squared error values of 0.996 and 0.0003,respectively,after training,which were well fitted and had a strong approximation ability.Conclusion:Upon comparison of fingerprints and the evaluation of statistical methods,common components of Radix isatidis extract had little variation under different drying conditions,and the selected components provided a reference for the establishment of process evaluation indexes.The establishment of backpropagation artificial neural network provides a theoretical basis for the application of microwave vacuum drying technology and online monitoring of moisture ratio.

Qualitative and quantitative analysis of glucosinolates and nucleosides in Radix Isatidis by HPLC and liquid chromatography tandem mass spectrometry

Multi-component fingerprinting and quantitation of the glucosinolates and nucleosides in samples of Radix Isatidis have been carried out using high-performance liquid chromatography with diode-array detection and electrospray ionization tandem mass spectrometry(HPLC–DAD–ESI/MS).Five nucleosides together with one glucosinolate were identified by comparing retention times,ultraviolet spectra,mass spectra and/or empirical molecular formulae of reference compounds.Quantitation of these six compounds was carried out simultaneously by HPLC on a Phenomenex Luna C18 column using gradient elution with methanol and water and detection at 254 nm.All calibration curves were linear(r40.9994)within test ranges.Limits of detection and quantitation were 0.33 ng and 2.50 ng on column,respectively.Intra-and inter-day precision(as relative standard deviation)for all analytes was o2.19%with recoveries in the range 99.6%–101.8%at three concentration levels.The validated method was successfully applied to fingerprinting and assay of 25 batches of Radix Isatidis sourced from different geographical regions of China.The method is simple and reliable and has potential value in the quality control of Radix Isatidis.

Enzyme-Linked Immunosorbent Assay and Immunochromatographic Strip for Rapid Detection of Atrazine in Three Medicinal Herbal Roots

Objectives:An enzyme-linked immunosorbent assay(ELISA)and colloidal gold-based immunochromatographic(ICG)strip assay will be developed for the rapid and high-throughput detection of atrazine(ATZ)in medicinal herbs.Methods:A monoclonal antibody against ATZ was obtained after the immunization of mice,cell fusion,and hybridoma screening,and the antibody was used to develop direct competitive ELISA(dcELISA)and the ICG strip assay.Results:Both dcELISA and ICG strip methods were established,optimized,and validated for the detection of ATZ in Salviae miltiorrhizae radix et rhizome,Astragali radix,and Isatidis radix.dcELISA had a half-maximum inhibition concentration of 10.56 ng/m L(Salviae miltiorrhizae radix et rhizome),7.6 ng/m L(Astragali radix),and 8.15 ng/m L(Isatidis radix).The limit of detection(LOD)of the ICG strip assay was 12.5 ng/mL(Salviae miltiorrhizae radix et rhizome),12.5 ng/mL(Astragali radix),and 6.25 ng/mL(Isatidis radix)in different herb matrices.Due to the recognition characteristics of the monoclonal antibody for the pesticides ATZ,propazine,sebuthylazine,and prometryn,the detection results of real samples by the two immunoassays were confirmed by liquid chromatography–tandem mass spectrometry,which proved the accuracy and reliability of the established methods.Conclusion:The proposed dcELISA and ICG strip methods were suitable for the rapid,convenient,and high-throughput detection of ATZ in these medicinal herbs.