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Record W2972204767 · doi:10.1088/0026-1394/56/1a/08017

Organochlorine Pesticides in Ginseng Root

2019· article· en· W2972204767 on OpenAlexaboutno aff
W F Wong, W. H. Lam, W H Fung, Boniface M. Muendo, G M Karau, K Hanen, Antonio dos S. Silva, Q Zhang, Nittaya Sudsiri, Dyah Styarini

Bibliographic record

VenueMetrologia · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Residue Analysis and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsGinsengPesticidePesticide residueEndosulfanLindaneToxicologyEnvironmental scienceEuropean unionOrganochlorine pesticideEnvironmental chemistryChemistryBusinessBiologyMedicine

Abstract

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Ginseng is one of the most important traditional herbal medicines for health care and treatment of diseases. Trading of ginseng and related products is a multi-million dollar business. Four major countries including South Korea, China, Canada and the United States are the biggest producers and account for more than 99% of the total ginseng production around the world (i.e. about 80,000 tons). The Commission Regulation of European Union sets up that the maximum residue level (MRL) for hexachlorocyclohexane (sum of alpha, beta and delta isomers, except lindane) is 0.02 mg/kg and that for lindane is 1 mg/kg in ginseng. The use of reliable methods for measurement of these organochlorine pesticides is important in safeguarding the quality of ginseng and related products and public health. The Government Laboratory, Hong Kong (GLHK) previously coordinated and completed CCQM-K95 "Mid-polarity Analytes in Food Matrix: Mid-polarity Pesticides in Tea". Two organochlorine pesticide residues,beta-endosulfan and endosulfan sulfate, were selected for analysis. It is noteworthy that participating institutes in CCQM-K95 found that wetting of test samples prior to extraction was crucial for complete extraction of the incurred analytes in the test material of dried tea. It is apparent that sample extraction is a real technical challenge in the analysis of dried plant material. Ginseng root is collected after years of cultivation. It represents a higher level of analytical challenge for the participating national metrology institutes (NMIs) and designated institutes (DIs) in measuring the incurred organochlorine pesticides in dried ginseng/ginseng root, where the pesticides have been gradually accumulated in the plant material for several years. In this regard, GLHK proposed a new APMP supplementary comparison on determination of organochlorine pesticides in ginseng root at the APMP TCQM meeting in November 2015. The supplementary comparison was further discussed at the CCQM OAWG meeting in April 2016. The Chair of APMP TCQM approved the proposed supplementary comparison for 2016/17 with a study number of APMP.QM-S11 in May 2016. To allow wider participation, a pilot study APMP.QM-P32, was run in parallel with this supplementary comparison. Evidence of successful participation in formal, relevant international comparisons is needed to document calibration and measurement capability claims (CMCs) made by national metrology institutes (NMIs) and designated institutes (DIs). Seven NMIs/DIs participated in this Supplementary Comparison APMP.QM-S11 Organochlorine pesticides in ginseng root. Participants were requested to evaluate the mass fractions, expressed in μg/kg, of alpha-hexachlorocyclohexane (α-BHC, CAS No. 319-84-6) and gamma-hexachlorocyclohexane (Lindane, CAS No. 58-89-9) in a relatively complex food/plant material, termed ginseng root. The purpose of the comparison is to enable participating laboratories to demonstrate their capability in the determination of organochlorine pesticides in a relatively complex food/plant material. All participating laboratories performed wetting before extraction. Different extraction methods such as soxhlet extraction, accelerated solvent extraction, ultrasonic extraction, QuEChERS technique, shaking and vortex were used among the participants. For the instrumental analysis, all laboratories employed GC techniques for chromatographic separation and most laboratories used MS related techniques for detection and quantification. For α-BHC, the consensus mean was 413 μg/kg with standard deviation of 35.3 μg/kg from 4 participating institutes' results. For lindane, the consensus mean was 104 μg/kg with standard deviation of 10.9 μg/kg from 5 participating institutes' results. Successful participation in APMP.QM-S11 demonstrates the following measurement capabilities in determining mass fraction of organic compounds, with molecular mass of 100 g/mol to 500 g/mol, having low polarity pKow < -2, in mass fraction range from 10 μg/kg to 1000 μg/kg in food/plant matrices. KEY WORDS FOR SEARCH Ginseng, Organochlorine Pesticide, alpha-hexachlorocyclohexane, gamma-hexachlorocyclohexane, Lindane, α-BHC Main text To reach the main text of this paper, click on Final Report . Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/ . The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.009
GPT teacher head0.201
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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