Back to Search
Start Over
Statistical evaluation of the influence of soil properties on recoveries and matrix effects during the analysis of pharmaceutical compounds and steroids by quick, easy, cheap, effective, rugged and safe extraction followed by liquid chromatography–tandem mass spectrometry
- Source :
- Journal of Chromatography A, Journal of Chromatography A, Elsevier, 2013, 1315, pp.53-60. ⟨10.1016/j.chroma.2013.09.056⟩
- Publication Year :
- 2013
- Publisher :
- Elsevier BV, 2013.
-
Abstract
- International audience; Numerous chemical products are dispersed in our environment. Many of them are recognized as harmful to humans and the ecosystem. Among these harmful substances are antibiotics and steroid hormones. Currently, very few data are available on the presence and fate of these substances in the environment, in particular for solid matrices, mainly due to a lack of analytical methodologies. Indeed, soil is a very complex matrix, and the nature and composition of the soil has a significant impact on the extraction efficiency and the sensitivity of the method. For this reason a statistical approach was performed to study the influence of soil parameters (clay, silt, sand and organic carbon percentages and cation exchange capacity (CEC)) on recoveries and matrix effects of various pharmaceuticals and steroids. Thus, an analysis of covariance (ANCOVA) was performed when several substances were analyzed simultaneously, whereas a Pearson correlation was used to study the compounds individually. To the best of our knowledge, this study is the first time such an experiment was performed. The results showed that clay and organic carbon percentages as well as the CEC have an impact on the recoveries of most of the target substances, the variables being anti-correlated. This result suggests that the compounds are trapped in soils with high levels of clay and organic carbon and a high CEC. For the matrix effects, it was shown that the organic carbon content has a significant effect on steroid hormones and penicillin G matrix effects (positive correlation). Finally, interaction effects (first order) were evaluated. This latter point corresponds to the crossed effects that occur between explanatory variables (soil parameters). Indeed, the value taken by an explanatory variable can have an influence on the effect that another explanatory variable has on a dependent variable. For instance, it was shown that some parameters (silt, sand) have an impact on the effect that clay content has on recoveries. Besides, CEC and silt affect the influence that organic carbon percentage has on matrix effect. This original approach provides a better understanding of the complex interactions that occur in soil and could be useful to understand and predict the performance of an analytical method.
- Subjects :
- Matrix effects
QuEChERS
010501 environmental sciences
Silt
Quechers
Interaction
complex mixtures
01 natural sciences
Biochemistry
Analytical Chemistry
Soil
Tandem Mass Spectrometry
[CHIM.ANAL]Chemical Sciences/Analytical chemistry
Liquid chromatography–mass spectrometry
Recoveries
Cation-exchange capacity
LC-MS/MS
0105 earth and related environmental sciences
Total organic carbon
Models, Statistical
Chromatography
Chemistry
010401 analytical chemistry
Organic Chemistry
Extraction (chemistry)
General Medicine
15. Life on land
6. Clean water
0104 chemical sciences
Pharmaceutical Preparations
Statistical analysis
13. Climate action
Environmental chemistry
Soil water
Steroids
Soil properties
Chromatography, Liquid
Subjects
Details
- ISSN :
- 00219673 and 18733778
- Volume :
- 1315
- Database :
- OpenAIRE
- Journal :
- Journal of Chromatography A
- Accession number :
- edsair.doi.dedup.....20190b3bcd647e8210bb6a0a9c301b78