Seeds of Calotropis procera Treated With Essential Oils of Copaifera langsdorffii Desf. and Syzygium aromaticum L.
Bibliographic record
Abstract
The Silk Flower (Calotropis procera) is widely used by farmers in the Northeast region, due to the adaptation of the climatic and soil conditions of the semi-arid region, but the incidence of pathogens has reduced the physiological and sanitary quality standards acceptable for sexual propagation of these plants in the field. Thus, the objective of this research was to verify the effects of the Copaíba (C. langsdorffii) and Cravo (S. aromaticum) oils on the health and physiological quality of silk flower seeds (C. procera) harvested in the city of Tacima, PB. The treatments were constituted by Copaíba (C. langsdorffii) and Cravo (S. aromaticum) essential oils at concentrations of 0.5; 1; 1.5; 2% and the fungicide Captan® (240 g, i.a. 100 kg-1 seed). The control 0 (zero) corresponded only to the immersion of the seeds in distilled and sterilized water (ADE). In the evaluation of sanity, the method of incubation on filter paper (Blotter test) was performed, using twenty replicates of 10 seeds for each treatment. The physiological quality was evaluated by the germination test (G%), first germination count (FGC), germination speed index (GSI) and seedling dry mass (SDM). A microflora composed mainly of Alternaria sp. (52%), Fusarium sp. (70%), Helminthosporium sp. (40%), Cladosporium sp. (50%), Curvularia sp. (20%) and Nigrospora sp. (5%). The essential oils considerably reduced the percentage of fungi associated with silk flower seeds, but there was moderate phytotoxic effect under the germination and vigor of C. procera seeds.
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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 | 0.001 |
| 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".