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March 6, 20260 citationsOpen Access

Evaluation of copper chloride crystallisation as a method for systems-level characterisation of phytopharmaceuticals - a pilot investigation.

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GGGreta GuglielmettiPDPaul DoesburgCSClaudia Scherr

Key Points

  • To evaluate the feasibility of copper chloride crystallisation (CCC) for characterising phytopharmaceuticals across different plant extracts.
  • Analysed Viscum album L. plant extracts with varying subspecies, host trees, and blending procedures.
  • Conducted sensitivity tests to assess CCC's ability to detect differences related to texture and structure.
  • Utilised statistical analysis with variables characterising the CCC fingerprints.
  • CCC was able to distinguish between different subspecies and blending methods with varying sensitivity.
  • Statistical significance was observed (p < 0.01) for the ability of CCC to detect these differences.
  • Four texture-related and two structure-related variables passed further sensitivity tests, although with less significant results.

Abstract

The multifaceted nature of phytotherapeutic products calls for methods able to provide a comprehensive and systems-level characterisation. Agricultural research suggests that copper chloride crystallisation (CCC) fingerprint analysis offers such possibilities. We therefore investigated the applicability of CCC to phytopharmaceutical questions. In this pilot trial, we analysed plant extracts of the same genus (Viscum album L.), featuring three progressively subtler differences: 1) subspecies (subsp. album vs austriacum), 2) deciduous host trees (apple vs oak), and 3) blending procedures (machine vs hand). In three sensitivity tests, we assessed CCC’s ability to detect these differences. CCC fingerprints were analysed using 7 variables characterising texture and structure. Systematic control experiments indicate that the setup is stable. In the Verum experiments, all variables passed the first sensitivity test (p < 0.01, Cohens’d 1.75–0.22). Four, mostly texture-related variables (p < 0.01, Cohens’d 0.56–0.26) and two structure variables (p < 0.01, Cohens’d 0.27, 0.20) passed the second and third sensitivity test, respectively. Our results demonstrated CCC’s ability, in our experimental setup, to detect differences between subspecies, deciduous host trees and blending procedures, although with progressively weaker statistical significance. Further development is needed to establish the relevance of CCC for phytopharmaceuticals and whether it can also detect systems-level properties. Supplementary Information: The online version contains supplementary material available at 10.1038/s41598-026-41081-6.

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Cite This Study

Guglielmetti et al. (2026) studied this question.

synapsesocial.com/papers/69aa701a531e4c4a9ff598e8https://doi.org/10.48620/95949
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