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Rapid Identification of American Ginseng Originated from Varied Places Based on Heracles Ultra-fast Gas Phase Electronic Nose

2023· article· en· W6922882417 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsOdorElectronic noseGinsengAmerican ginsengAromaRelative standard deviationAldehydeGas chromatography

Abstract

fetched live from OpenAlex

Objective: Heracles ultra-fast gas phase electronic nose was applied to establish a quick and effective differentiation method for American ginseng originated from varied places on the basis of different smell. Methods: Heracles ultra-fast gas phase electronic nose was used to analyze the smell of American ginseng originated from varied places and acquired chromatographic information of smell of sample American ginseng. The chromatographic peaks with strong separation intensity and discrimination ability were screened. Based on Kovats retention index and Arochembase database, the main odorant compounds of American ginseng from different producing areas were characterized. According to the relative odor activity value (ROAV), the contribution degree of the main difference compounds to the odor of American ginseng was analyzed by the odor threshold and relative content of the main difference compounds. PCA and DFA stoichiometry models were used for analysis. Results: Thirteen major differential compounds including propanaldehyde, n-valyl aldehyde and n-hexanal were screened out from ginseng of different origin by Heracles ultra-fast gas-phase electronic nose. Through the ROAV analysis of the main difference compounds, it was determined that n-hexal, propionic aldehyde, dodecal, n-valyl aldehyde, 2,3,5-trimethylpyrazine, methyl butyrate, 2-heptanol were the odor substances that contributed more to the odor of American ginseng. Among them, n-hexal was the key odor compounds that contributed the most to the odor of American ginseng. The contents of n-hexal, n-valental, 2,3,5-trimethylpyrazine and 2-heptanol were the highest in American ginseng from American . The contents of propionic aldehyde and methyl butyrate were the highest in American ginseng from Canadian. The content of dodecal was the highest in American ginseng from Jilin . PCA and DFA stoichiometric models were established. The recognition index of PCA model was 88. The cumulative discrimination index of DFA model was 100%. It was indicated that both PCA and DFA models could distinguish the odors of American ginseng from different producing areas, which could identify and analyze the odors of American ginseng samples. Conclusion: Heracles ultra-fast gas-phase electronic nose can quickly and effectively distinguish ginseng from different origin. This provides a new scientific basis for tracing the origin of ginseng.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.095
GPT teacher head0.476
Teacher spread0.381 · 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 designBench or experimental
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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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