Sanity and Physiology of Ceiba speciosa Seeds Treated With Essential Oils
Bibliographic record
Abstract
Since the propagation of forest species is by seeds, the success of population establishment depends on the use of good quality seeds. And the use of alternative controls with essential oils for fungal control is ecologically important. The present work aimed to evaluate the influence of essential oils of Citronella (Cymbopogon winterianus), Palmarosa (Cymbopogon martini), Lemongrass (Cymbopogon citratus), Thyme (Thymus vulgaris), Eucalyptus globulus and Rosemary (Salvia rosmarinus) in reducing the incidence of fungus and physiological quality of painera—Ceiba speciosa seeds. The seeds were treated with the essential oils of Citronella, Palmarosa, Lemongrass, thyme, eucalyptus, and rosemary at a concentration of 2%. Captan fungicide (240 g/100 kg-1) was used as a control treatment. After the treatments, the seeds were evaluated by the sanity test, using the “Blotter test” filter paper method. For physiological quality, germination, first count, germination speed index, and seedling length were evaluated. The following genera of phytopathogenic fungi have been identified on Paineira seeds: Cladosporium sp., Fusarium spp., Penicillium sp., Colletotrichum sp. and Pestalotipsis sp. Treating the seeds with essential oils of Citronella, Palmarosa, Lemongrass, and Thyme controlled the fungi on the Paineira seeds. However, changes in the physiological quality of the seeds were associated with the use of the essential oils, compromising seedling vigor.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".