Formation of heterocyclic amines during cooking of duck meat
Bibliographic record
Abstract
Heterocyclic amines (HAs) are an important class of food mutagens and carcinogens produced in meat cooked at high temperature. In the present study, the effects of various cooking methods: boiling, microwave cooking, charcoal-grilling, roasting, deep-frying and pan-frying on the formation of HAs in duck breast were studied. The various HAs formed during cooking were isolated by solid-phase extraction and analysed by HPLC. Results showed that both the varieties and contents of HAs and the cooking loss of duck breast increase along with increasing cooking temperature and time. Pan-fried duck breasts contained the highest amount of total HAs, followed by charcoal-grilling, deep-frying, roasting, microwave cooking and boiling. 9H-pyrido[3,4-b]indole (norharman) and 1-methyl-9H-pyrido[3,4-b]indole (harman) were detected in all of the cooked duck meat, with levels in the range of 0.1-33 ng g⁻¹. 2-Amino-1-methyl-6-phenylimidazo[4,5-f]pyridine (PhIP) was formed easily in duck meat cooked by pan-frying and charcoal-grilling in the range of 0.9-17.8 ng g⁻¹. 2-Amino-3-methylimidazo[4,5-f]quinoline (IQ) was identified in duck meat cooked by charcoal-grilling and pan-frying, in the range of 0.4-4.2 ng g⁻¹. 2-Amino-3,8-dimethyl-imidazo[4,5-f]quinoxaline (MeIQx) was detected in amounts below 4.5 ng g⁻¹ in duck meat cooked by charcoal-grilling, roasting, deep-frying and pan-frying. The other HAs were detected in amounts below 10 ng g⁻¹. Colour development increased with cooking temperature, but no correlation with HAs' content was observed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".