Applications of laser ablation inductively coupled plasma mass spectrometry for monitoring impurities in solid foodstuff
Bibliographic record
Abstract
The development of rapid and simple analytical methods that reliably monitor metal impurities in nutraceutical products is beneficial. An alternative solid sampling approach to quantify As, Cd, Hg, and Pb with LA-ICPMS is proposed in this work. This approach employs the incorporation of spiked organic binder standards with powdered raw materials in consistent ratios for the analysis of pressed pellets with LA-ICPMS. To date, LA-ICPMS calibration techniques have been limited by the inability to produce matrix matched standards and samples. This modified standard addition method provides a higher degree of matrix matching. It is hypothesized that LA-ICPMS will produce reliable analytical data for the analysis of elemental impurities in powders for the nutraceutical industry. Also, it is hypothesized that the incorporation of binders into analytical samples will be an effective way to accomplish standard addition. A Cetac LSX 500 266 nm Nd:YAG laser, and a Photon Machines Analyte G2 193 nm excimer laser were coupled to a Thermo XSeries2 ICP-MS to analyze berry, fiber and chondroitin samples in polyvinyl alcohol, microcrystalline and α-cellulose, and vanillic acid matrices under optimized laser conditions. USP 34 regulatory limits were used as guidelines to monitor As, Cd, Hg, and Pb. Quantification limits (LOQ) of 0.56, 0.13, 0.10, 0.10 μg/g were determined for As, Cd, Hg, and Pb respectively with the Nd:YAG laser. Similarly, the excimer laser gave LOQ of 0.063, 0.016, 0.057, 0.006 μg/g. All LOQ were capable of quantifying the impurities below regulatory limits. Accuracy validation with excimer laser gave recoveries ranging from 82 - 99% and 84 - 103% with scandium and yttrium normalizations in PVA respectively; the method precision met validation criteria of less than 20% RSD ranging from 5.4 to 19.8% for Pb and Hg respectively. Linearity validation studies gave R² values above 0.95 meeting acceptance criteria. The accuracy of Pb was maintained with both laser systems, and experimental values were within experimental uncertainty of the certified NIST 1547 and NIST 1486 reference values. The data supports that LA-ICPMS was a viable tool in generating reliable analytical data and that the incorporation of binders into samples effectively accomplished standard addition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".