Respiratory Activity as a Fast Method for Vigor Differentiation of Habanero Pepper Seeds
Bibliographic record
Abstract
The objective of this study was to evaluate the efficiency and rapidity of the Pettenkofer and Titulation methods in the determination of respiratory activity and its relation with the vigor of habanero pepper seeds. For this, six lots of habanero pepper seeds were evaluated for respiratory activity, through Pettenkofer and Titulation physicochemical methods, and for physiological quality via tests of germination, first germination count, germination speed index, emergence, initial stand, emergence speed index and electrical conductivity. Biochemical analyzes were also carried out using the electrophoresis of the esterase (EC 3.1.1.1.) and alcohol dehydrogenase (EC 1.1.1.2.), and the quantification of the endo-β-mannanase enzyme (EC 3.2.1.78). The tests of physiological quality and the respiratory activity of the seeds allowed the classification of the habanero pepper seed lots at different vigor levels. There was a correlation between the respiratory activity with the tests used to evaluate the physiological quality of the seeds and with the endo-β-mannanase enzyme. It is concluded that the Pettenkofer and Titulation methods are promising for the evaluation of the deterioration level and the discrimination of lots of habanero pepper seeds with different vigor levels.
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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 | 0.001 |
| 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) | 0.001 | 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".