Application of plastic polymers in remediating wine with elevated alkyl-methoxypyrazine levels
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Bibliographic record
Abstract
3-Alkyl-2-methoxypyrazines (MPs) are odour-active compounds that elicit atypical green aromas and flavours in some wines, and are resilient to removal using traditional wine-making approaches. They originate either as contaminants from Coccinellidae beetles inadvertently introduced during wine processing ("ladybug taint") or as grape-derived constituents that are undesirable at elevated levels. In this study we investigated the capacity of a selection of plastic polymers to reduce concentrations of three MPs: isopropyl methoxypyrazine (IPMP), secbutyl methoxypyrazine (SBMP) and isobutyl methoxypyrazine (IBMP). In Trial 1, red wine was spiked with IPMP (20 ng/l), SBMP (20 ng/l) and IBMP (20 ng/l), then separately treated with 13 plastic polymers (surface area 350 cm(2)/l). Three polymers were then identified for further testing based on the results from Trial 1: silicone, ethylene and vinyl acetate (EVA) and a poly-lactic acid-based biodegradable polymer. In Trial 2, the efficacy of these selected polymers to reduce MP levels in red wine was tested as a function of contact time. Solid-phase micro-extraction multi-dimensional GC-MS was used to measure MP levels before and after treatment with the polymers. Results showed significant reductions in all target odorants after 24 h treatment: silicone reduced IPMP and IBMP by 96% and 100%, respectively, while the biodegradable polymer decreased IPMP and IBMP concentrations by 52% and 36%, respectively. EVA was less effective in lowering MP levels (7% IPMP and 23% IBMP after 24 h). Taken overall, the data suggest the potential for the use of poly-lactic acid and silicone in treating wines contaminated by ladybug taint, as well as in reducing high levels of grape-derived MPs.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 it