Rapid Determination of Chlorogenic Acid, Luteoloside and 3,5-O-dicaffeoylquinic Acid in Chrysanthemum Using Near-Infrared Spectroscopy.

The feasibility of near-infrared spectroscopy (NIR) to detect chlorogenic acid, luteoloside and 3,5-O-dicaffeoylquinic acid in Chrysanthemum was investigated. An NIR spectroradiometer was applied for data acquisition. The reference values of chlorogenic acid, luteoloside, and 3,5-O-dicaffeoylquinic acid of the samples were determined by high-performance liquid chromatography (HPLC) and were used for model calibration. The results of six preprocessing methods were compared. To reduce input variables and collinearity problems, three methods for variable selection were compared, including successive projections algorithm (SPA), genetic algorithm-partial least squares regression (GA-PLS), and competitive adaptive reweighted sampling (CARS). The selected variables were employed as the inputs of partial least square (PLS), back propagation-artificial neural networks (BP-ANN), and extreme learning machine (ELM) models. The best performance was achieved by BP-ANN models based on variables selected by CARS for all three chemical constituents. The values of rp2 (correlation coefficient of prediction) were 0.924, 0.927, 0.933, the values of RMSEP were 0.033, 0.018, 0.064 and the values of RPD were 3.667, 3.667, 2.891 for chlorogenic acid, luteoloside, and 3,5-O-dicaffeoylquinic acid, respectively. The results indicated that NIR spectroscopy combined with variables selection and multivariate calibration methods could be considered as a useful tool for rapid determination of chlorogenic acid, luteoloside, and 3,5-O-dicaffeoylquinic acid in Chrysanthemum.

Distinguishing Vaccinium species by chemical fingerprinting based on NMR spectra, validated with spectra collected in different laboratories.

A method was developed to distinguish Vaccinium species based on leaf extracts using nuclear magnetic resonance spectroscopy. Reference spectra were measured on leaf extracts from several species, including lowbush blueberry (Vaccinium angustifolium), oval leaf huckleberry (Vaccinium ovalifolium), and cranberry (Vaccinium macrocarpon). Using principal component analysis, these leaf extracts were resolved in the scores plot. Analysis of variance statistical tests demonstrated that the three groups differ significantly on PC2, establishing that the three species can be distinguished by nuclear magnetic resonance. Soft independent modeling of class analogies models for each species also showed discrimination between species. To demonstrate the robustness of nuclear magnetic resonance spectroscopy for botanical identification, spectra of a sample of lowbush blueberry leaf extract were measured at five different sites, with different field strengths (600 versus 700 MHz), different probe types (cryogenic versus room temperature probes), different sample diameters (1.7 mm versus 5 mm), and different consoles (Avance I versus Avance III). Each laboratory independently demonstrated the linearity of their NMR measurements by acquiring a standard curve for chlorogenic acid (R(2) = 0.9782 to 0.9998). Spectra acquired on different spectrometers at different sites classifed into the expected group for the Vaccinium spp., confirming the utility of the method to distinguish Vaccinium species and demonstrating nuclear magnetic resonance fingerprinting for material validation of a natural health product.

[Determination of eleven major components and fingerprint chromatography for Reduning injection by UPLC].

A reliable method for simultaneous determinition of eleven representative components (neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, isochlorogenic acid B, isochlorogenic acid A, isochlorogenic acid C, shanzhiside, geniposidic acid, genipin-1-ß-D-gentiobioside, geniposide and secoxyloganin) in combination of chromatographic fingerpint analysis for Reduning injection was developed by ultra high-performance liquid chromatography (UPLC). The method was performed on an Agilent ZORBAX SB-C18 anlytical column (3. 0 mm x 100 mm, 1. 8 µm) with a guard column of Agilent UPLC Guard ZORBAX SB-C18 (3.0 mm x 5 mm) at the column temperature of 30 °C. The gradient mobile phase consisted of acetonitrile (A)-0. 1% phosphoric acid (B) with a flow rate of 0. 4 mL . min-1. The injection volumn was 2 µL. The detection wavelengths were set at 324 nm and 238 nm for quantit tive analysis and 225 nm for fingerpint chromatography. Neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, isochlorogenic acid B, isochlorogenic acid A, isochlorogenic acid C, shanzhiside, geniposidic acid, genipin-1-ß-D-gentiobioside, geniposide and secoxyloganin were baseline seperated with good linearity relationships (r >0. 999) between concentration and peak areas over the linear ranges. The average recoverys of the investigated compounds were 103.5%, 100. 2%, 103. 3%, 102. 8%, 101. 3%, 102. 8%, 97. 36%, 99. 62%, 98. 16%, 102. 8%, 99. 27%, respectively. Reduning injection of forty-five batches was analyzed by UPLC finge print chromatography. Thirty batches were selected to generate the reference fringerprint chromatography with fourteen common peaks. The similarity values between the reference fringerprint chromatography and the remaining fifteen batches were higher than 0. 99. The developed method was fast, accurate and sensitive. It could be used as a reference for the quality control of multiple components determination and fingerprint chromatography for Reduning injection in future.

Qualitative and quantitative high performance thin layer chromatography analysis of Calendula officinalis using high resolution plate imaging and artificial neural network data modelling.

Calendula officinalis, commonly known Marigold, has been traditionally used for its anti-inflammatory effects. The aim of this study was to investigate the capacity of an artificial neural network (ANN) to analyse thin layer chromatography (TLC) chromatograms as fingerprint patterns for quantitative estimation of chlorogenic acid, caffeic acid and rutin in Calendula plant extracts. By applying samples with different weight ratios of marker compounds to the system, a database of chromatograms was constructed. A hundred and one signal intensities in each of the HPTLC chromatograms were correlated to the amounts of applied chlorogenic acid, caffeic acid, and rutin using an ANN. The developed ANN correlation was used to quantify the amounts of 3 marker compounds in calendula plant extracts. The minimum quantifiable level (MQL) of 610, 190 and 940 ng and the limit of detection (LD) of 183, 57 and 282 ng were established for chlorogenic, caffeic acid and rutin, respectively. A novel method for quality control of herbal products, based on HPTLC separation, high resolution digital plate imaging and ANN data analysis has been developed. The proposed method can be adopted for routine evaluation of the phytochemical variability in calendula extracts.

HPLC-DAD method for comprehensive quality control of Semen Strychni.

CONTEXT: Semen Strychni is the seed of Strychnos nux-vomica L. (Loganiaceae). Its quality control procedure remains an issue since previous reports only focused on Strychnos alkaloids. To the best of our knowledge, chlorogenic acid (a phenolic acid) and loganin (an iridoid glycoside) are selected for the first time as marker constituents of quality control for Semen Strychni because of their bioactive activity correlating with therapeutic effects. OBJECTIVE: This study aimed to develop a simple and comprehensive quantity control method for Semen Strychni. MATERIALS AND METHODS: The optimal ultrasonic extraction procedure was carried out for 45 min using 50% aqueous methanol with 1% formic acid. The satisfactory chromatographic separation was achieved on an Ultimate LP-C18 column with gradient elution using acetonitrile and water containing 30 mmol/L ammonium acetate and 1% formic acid. The high performance liquid chromatography method with diode array detector was validated for linearity, limit of detection and quantification (LOQ), precision, repeatability, accuracy and stability. RESULTS: All the calibration curves showed good linearity (r(2) ≥ 0.999). The LOQ values for chlorogenic acid, loganin, strychnine, brucine, strychnine N-oxide and brucine N-oxide were 0.54, 0.83, 0.48, 0.50, 0.52 and 0.54 µg/mL, respectively. The method was reproducible with good accuracy in the range 95.6-104.4% and relative standard deviation (RSD) values less than 4.55%. The method was then applied to determine the components of the seed coat, seed leaf, endosperm and whole seed of Semen Strychni. CONCLUSION: This newly established method is validated as a simple and practical tool for authentication and quality control of Semen Strychni.

NIR analysis for batch process of ethanol precipitation coupled with a new calibration model updating strategy.

Ethanol precipitation plays a major role in the pretreatment of Flos Lonicerae Japonicae of Qingkailing injection, and is also one of the most popular purification techniques in Chinese herbal medicines. In order to monitor and have a better understanding of the ethanol precipitation process, a PLS model was built based on NIR spectroscopy and HPLC analysis of chlorogenic acid content within the framework of FDA's PAT initiative. Nevertheless, due to the complex mechanism of and the raw materials' natural variability introduced into the ethanol precipitation process, it was unable to foresee the variations in new batches which may jeopardize the robustness of the established model. Therefore, based on the simple interval calculation (SIC) theory, a new model expansion updating strategy which could continuously expand the variation coverage of the calibration model along with the batch proceeding of ethanol precipitation process was proposed. Effects of model updating were validated by an individual batch with 60 samples. After two times of updating, the root mean squared error of prediction (RMSEP) decreased from 0.268 mg mL(-1) to 0.199 mg mL(-1), while the insiders in the object status plot (OSP) increased from 44 to 58, demonstrating the good performance of the proposed approach.

Hydrophilic interaction liquid chromatography method for the determination of ascorbic acid.

Hydrophilic interaction liquid chromatography (HILIC) method using internal standard for the determination and stability study of ascorbic acid was developed. HILIC method was very fast and simple using the following analytical conditions: ZIC HILIC (150 x 2.1 mm, 3.5 microm) chromatographic column and mobile phase composed of ACN and 50 mM ammonium acetate buffer pH 6.8 (78:22 v/v). Diode array detection was performed and chromatograms were processed at 268 nm, the maximum wavelength of absorbance of ascorbic acid. An extensive stability study of ascorbic acid as a function of various factors including temperature, stabilizing agents, oxygen presence and its concentration in solution was performed in order to gain information about the quantitative influence of individual stability factors. Low temperature and stabilizing agents (o-phosphoric acid and oxalic acid) were found to be key factors enabling substantial enhancement of the stability of ascorbic acid.