A fast ethanol assay to detect seed deterioration
Bibliographic record
Abstract
Abstract The most common way to test seed quality is to use a simple and reliable but time- and space-consuming germination test. In this paper we present a fast and simple method to analyse cabbage seed deterioration by measuring ethanol production from partially imbibed seeds. The method uses a modified breath analyser and is simple compared to gas chromatographic or enzymatic procedures. A modified method using elevated temperatures (40°C instead of 20°C) shortened the assay time and improved its sensitivity. The analysis showed an inverse correlation between ethanol production and seed quality (e.g. the final percentages or speed of germination and the number of normal seedlings). The increase in ethanol production was observed when cabbage seeds were deteriorated by storage under ambient conditions or hot water treatments, both of which reduced the number of normal seedlings. Premature seeds produced more ethanol upon imbibition than mature seeds. Ethanol production occurred simultaneously with oxygen consumption, indicating that lack of oxygen is not the major trigger for ethanol production.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".