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Demonstrates a resource-efficient approach for measuring metals in cannabis, suggesting reduced waste and improved efficiency.
Regulatory testing of cannabis and hemp commonly prioritizes As, Cd, Pb, and Hg, yet inductively coupled plasma mass spectrometry (ICP-MS) workflows often require extensive tuning and method setup that can be difficult to implement in resource-limited laboratories. Although general guidance exists, quantitative ranges for critical settings are still sparsely documented for cannabis matrices, and "one-set" conditions may not transfer well across instruments. To address this gap, we developed a resource-efficient, low-run screening strategy intended to reduce trial-and-error, reagent consumption, and instrument time when only a limited number of runs is feasible, using two linked 12-run, resolution-III Plackett-Burman designs generated in R. First, key ICP-MS parameters were screened under QC conditions to define a stable operating region. Second, digestion factors (acid composition/volumes, temperature program, sample mass, and predigestion) were assessed using spiked inflorescence samples. Apparent effects were identified using standard screening diagnostics and supported by two-factor trend visualizations. The screening highlighted three underreported practical contributors-RF power, peristaltic-pump speed, and operation without inrun dilution-as dominant drivers of robustness, together with element-dependent recovery drivers: As was mainly governed by HCl level; Cd and Hg by coupled HCl volume × sample mass trends; and Pb by combined heating-ramp/HNO₃ and temperature/predigestion patterns. Because resolution-III designs alias main effects with specific two-factor interactions, the numerical effects should be interpreted as first-pass screening estimates rather than definitive optima and require higher resolution confirmation. Overall, the study provides a quantitative map of factor relevance for cannabis metal digestion and narrows the experimental space for subsequent optimization and validation.
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Ramirez et al. (2026) studied this question.
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