A Validated Stability-Indicating HPTLC Assay for Determination of 10-Hydroxy-2-Decenoic Acid Content in Royal Jelly Products Using Robust Regression Methods
| Autor: | Mohamed A. Korany, Marwa S. Moneeb, Nadia A. El-Sebakhy, Alaa A. El-Banna, Aya M. Asaad |
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| Rok vydání: | 2020 |
| Předmět: |
food.ingredient
02 engineering and technology Derivative 01 natural sciences Analytical Chemistry Robust regression Fatty Acids Monounsaturated food Drug Stability Limit of Detection Royal jelly Chromatography High Pressure Liquid Chromatography Chemistry 010401 analytical chemistry Fatty Acids Nonparametric statistics Reproducibility of Results Regression analysis General Medicine 021001 nanoscience & nanotechnology 0104 chemical sciences Nonparametric regression Forced degradation Linear Models Regression Analysis Chromatography Thin Layer 0210 nano-technology Unit-weighted regression |
| Zdroj: | Journal of chromatographic science. 58(6) |
| ISSN: | 1945-239X |
| Popis: | A new, simple, stability-indicating high-performance thin-layer chromatography method was developed for the quantification of 10-hydroxy-2-decenoic acid (10-HDA) in some royal jelly products marketed in Egypt. The used solvent system was chloroform:acetic acid (10:1, v/v) and the bands were measured densitometrically at 210 nm. First- and second-derivative treatments of the data were performed. The present study shows a comparison between three statistical regression methods for handling data: parametric, nonparametric and weighted regression (WR) methods. The developed methods were validated as per International Conference on Harmonization guidelines. To validate the stability-indicating power of the developed analytical method, the royal jelly standard was subjected to forced degradation studies including the effect of hydrolysis, oxidation, photolysis and dry heat. It was found that derivative treatment of the chromatographic response data gives improved quantitation and sensitivity of the chromatographic signals. Weighted regression of the response data is found to be advantageous over the use of both parametric and nonparametric regression models. This was shown by a great enhancement in the accuracy and precision in the analysis of 10-HDA in royal jelly products. The % recovery in case of WR was 99.92 ± 0.16, while % recovery in case of nonparametric and parametric regressions were 99.56 ± 0.25 and 98.63 ± 0.65, respectively. |
| Databáze: | OpenAIRE |
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