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Solid‐phase extraction for clean‐up of sugar‐rich plant material for improving
identification by normal phase HPTLC
Grigorios THEOCHARIS
CAMAG Laboratory, Muttenz, Switzerland
Debora FROMMENWILER
CAMAG Laboratory
Berries constitute a significant dietary source of a multitude of phytochemicals such as
flavonoids and coumarins, which exert beneficial effects on human health. However, they
also have a high sugar content, hence disturbing identification by HPTLC fingerprints
obtained on normal phases. Therefore, the preparation of such samples requires an
efficient clean‐up step to avoid matrix‐derived interferences that may adversely influence
the analysis sensitivity, specificity, and reproducibility.
In two individual studies, existing HPTLC methods for the identification of Cranberry
(Vaccinium macrocarpon) and Goji berry (Lycium barbarum) fruits were evaluated. The
thereby encountered poor reproducibility has been greatly improved by the removal of
matrix compounds employing a C18 SPE clean‐up. Moreover, the yield of substances of
interest has been increased whereas the overall solvent consumption decreased.
From the experiments, a generalized approach has been derived, which is applicable for
future projects targeting other sugar‐rich sample matrices.

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Solid‐phase extraction for clean‐up of sugar‐rich plant material for improving identification by normal phase HPTLC

  • 1. Solid‐phase extraction for clean‐up of sugar‐rich plant material for improving identification by normal phase HPTLC Grigorios THEOCHARIS CAMAG Laboratory, Muttenz, Switzerland Debora FROMMENWILER CAMAG Laboratory Berries constitute a significant dietary source of a multitude of phytochemicals such as flavonoids and coumarins, which exert beneficial effects on human health. However, they also have a high sugar content, hence disturbing identification by HPTLC fingerprints obtained on normal phases. Therefore, the preparation of such samples requires an efficient clean‐up step to avoid matrix‐derived interferences that may adversely influence the analysis sensitivity, specificity, and reproducibility. In two individual studies, existing HPTLC methods for the identification of Cranberry (Vaccinium macrocarpon) and Goji berry (Lycium barbarum) fruits were evaluated. The thereby encountered poor reproducibility has been greatly improved by the removal of matrix compounds employing a C18 SPE clean‐up. Moreover, the yield of substances of interest has been increased whereas the overall solvent consumption decreased. From the experiments, a generalized approach has been derived, which is applicable for future projects targeting other sugar‐rich sample matrices.