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Matrix-Aware LC-MS/MS Quantification of Cyhexatin in Chemically Complex Herbal Matrices Using DOE-Assisted Extraction
Jun Yeop Kim1, Seung Min Lee1, Woo Jae Lee1
1College of Pharmacy, Dankook University, Cheonan, Chungnam 31116, South Korea.
ACS Omega
|August 14, 2026
Summary
This study introduces a matrix-aware LC-MS/MS workflow to accurately quantify hydrophobic pesticides like cyhexatin in complex herbal samples. Design-of-experiments (DOE) optimization significantly improved recovery and reduced variability for reliable pesticide analysis.
Area of Science:
- Analytical Chemistry
- Environmental Science
Background:
- Matrix-dependent analytical interference challenges accurate quantification of hydrophobic pesticides in complex herbal matrices.
- Cyhexatin, a hydrophobic organotin pesticide, shows significant response variability in LC-MS/MS analysis.
- Existing empirical optimization methods are insufficient for complex matrices.
Purpose of the Study:
- To develop and validate a matrix-aware LC-MS/MS workflow for reliable quantification of hydrophobic pesticides in herbal matrices.
- To address matrix-dependent analytical interference using design-of-experiments (DOE) and matrix-matched calibration.
- To improve the accuracy and precision of cyhexatin quantification in challenging herbal samples.
Main Methods:
- A matrix-aware LC-MS/MS workflow was developed, integrating design-of-experiments (DOE) for extraction optimization.
- Fractional factorial and Box-Behnken designs (BBD) were employed to optimize extraction parameters in Angelicae Gigantis Radix.
- Matrix-matched calibration and surrogate internal standard (IS) normalization were utilized to mitigate matrix effects.
Main Results:
- The optimized method demonstrated robust quantitative performance across Angelicae Gigantis Radix and Paeoniae Radix, meeting Codex validation criteria.
- DOE-guided optimization enhanced cyhexatin recovery from 38% to 70-120% in challenging matrices.
- The workflow achieved low-ppb sensitivity (LOD ~3-4 ppb, LOQ = 10 ppb) and reduced matrix-dependent signal variability.
Conclusions:
- The developed matrix-aware LC-MS/MS workflow provides a robust strategy for accurate pesticide quantification in complex herbal matrices.
- DOE-assisted optimization and matrix-matched calibration are effective in overcoming matrix-dependent analytical interference.
- This approach enhances quantitative reliability for hydrophobic pesticides in chemically complex samples.
