Alelopatic Effects of Tectona grandis L.F. in the Germination and Initial Development of Lettuce (Lactuca sativa L.)
Bibliographic record
Abstract
This study aimed to evaluate the allelopathic effects of aqueous extracts of Tectona grandis L.F. in various concentrations produced from leaves and flowers. Seeds of lettuce (Lactuca sativa L.) and germitest paper as substrate were used, the germitest paper was moistened with distilled water, and aqueous extract in concentrations of 100%, 75%, 50%, 25% and 0% (distilled water). The extracts were homogeneously deposited on twenty-five seeds evenly distributed in gerbox-type boxes. The materials used in the experiment were previously sterilized with alcohol (70%). A completely randomized experimental design with four replicates was used and the experiment was conducted under natural conditions of temperature and humidity. The tests were carried out in the laboratory, the experiment was watched for 10 days always at the same hour and the variables analyzed were Germination Percentage (%G), Speed of Germination Index (SGI), Mean germination time (MGT) and Mean speed of germination (MSG). The data were submitted to Analysis of Variance and compared by Tukey test considering 95% of probability. It was observed that there were no significant differences in leaf and flower extracts for the variables %G, MGT and MSG, however, in SGI aqueous leaf extract differed significantly at the highest concentrations (75% and 100%). It was concluded that aqueous extracts of leaves and flowers of T. grandis had no inhibitory potential in relation to the percentage and average germination time of lettuce seeds at any of the concentrations.
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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) | 0.001 | 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 | 0.000 |
| 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".