Evaluation of the Saponin Content in Panax vietnamensis Acclimatized to Lam Dong Province by HPLC–UV/CAD

Panax vietnamensis, or Vietnamese ginseng (VG), an endemic Panax species in Vietnam, possesses a unique saponin profile and interesting biological activities. This plant is presently in danger of extinction due to over-exploitation, resulting in many preservation efforts towards the geographical acclimatization of VG. Yet, no information on the saponin content of the acclimatized VG, an important quality indicator, is available. Here, we analyzed the saponin content in the underground parts of two- to five-year-old VG plants acclimatized to Lam Dong province. Nine characteristic saponins, including notoginsenoside-R1, ginsenoside-Rg1, -Rb1, -Rd, majonoside-R1, -R2 vina-ginsenoside-R2, -R11, and pseudoginsenoside-RT4, were simultaneously determined by HPLC coupled with UV and with a charged aerosol detector (CAD). Analyzing the results illustrated that the detection of characteristic ocotillol-type saponins in VG by CAD presented a superior capacity compared with that of UV, thus implying a preferential choice of CAD for the analysis of VG. The quantitative results indicating the saponin content in the underground parts of VG showed an increasing tendency from two to five years old, with the root and the rhizome exhibiting different saponin accumulation patterns. This is the first study that reveals the preliminary success of VG acclimatization and thereby encourages the continuing efforts to develop this valuable saponin-rich plant.

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The Corona Charged Aerosol Detector – A „Universal“ Detector for the Measurement of Non-volatile Components in Food, Natural Products and Supplements

Planta Medica ◽

10.1055/s-0031-1282197 ◽

2011 ◽

Vol 77 (12) ◽

Author(s):

IN Acworth

Keyword(s):

Natural Products ◽

Volatile Components ◽

Charged Aerosol ◽

Universal Detector ◽

Charged Aerosol Detector

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Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach

Journal of Cheminformatics ◽

10.1186/s13321-021-00532-0 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Ruben Pawellek ◽

Jovana Krmar ◽

Adrian Leistner ◽

Nevena Djajić ◽

Biljana Otašević ◽

...

Keyword(s):

Fatty Acids ◽

Mobile Phase ◽

Molecular Descriptors ◽

Attribute Selection ◽

Selection Strategy ◽

Detector Response ◽

Experimental Conditions ◽

Molecular Features ◽

Charged Aerosol ◽

Charged Aerosol Detector

AbstractThe charged aerosol detector (CAD) is the latest representative of aerosol-based detectors that generate a response independent of the analytes’ chemical structure. This study was aimed at accurately predicting the CAD response of homologous fatty acids under varying experimental conditions. Fatty acids from C12 to C18 were used as model substances due to semivolatile characterics that caused non-uniform CAD behaviour. Considering both experimental conditions and molecular descriptors, a mixed quantitative structure–property relationship (QSPR) modeling was performed using Gradient Boosted Trees (GBT). The ensemble of 10 decisions trees (learning rate set at 0.55, the maximal depth set at 5, and the sample rate set at 1.0) was able to explain approximately 99% (Q2: 0.987, RMSE: 0.051) of the observed variance in CAD responses. Validation using an external test compound confirmed the high predictive ability of the model established (R2: 0.990, RMSEP: 0.050). With respect to the intrinsic attribute selection strategy, GBT used almost all independent variables during model building. Finally, it attributed the highest importance to the power function value, the flow rate of the mobile phase, evaporation temperature, the content of the organic solvent in the mobile phase and the molecular descriptors such as molecular weight (MW), Radial Distribution Function—080/weighted by mass (RDF080m) and average coefficient of the last eigenvector from distance/detour matrix (Ve2_D/Dt). The identification of the factors most relevant to the CAD responsiveness has contributed to a better understanding of the underlying mechanisms of signal generation. An increased CAD response that was obtained for acetone as organic modifier demonstrated its potential to replace the more expensive and environmentally harmful acetonitrile.

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