Allelopathic Effects of Purple Nutsedge Extract on the Physiological Quality of Cabbage and Tomato Seeds
Bibliographic record
Abstract
Invasive plants may present allelopathic substances that interfere with the germination and initial development of seedlings of various species. The objective of this study is to evaluate the physiological quality of cabbage and tomato seeds in the presence of different concentrations of purple nutsedge extract. The seeds were left to germinate in different substrates. Individual experiments were performed for both species. Five concentrations (0, 25, 50, 75 and 100%) of aqueous extract obtained from tubers of Cyperus rotundus were used. The seeds of each species were placed to germinate in three types of substrates (sand, commercial, and paper). Germination, normal seedlings, abnormal seedlings, non-germinated seeds, germination speed index, and accelerated aging were evaluated. A completely randomized experiment with a 3 × 5 factorial design (three substrates and five concentrations of purple nutsedge extract) was conducted with four replications. For the substrates, the means were compared by Tukey test at 5% probability. Polynomial regression analyses were carried out for concentrations of purple nutsedge extract. Cyperus rotundus exerts allelopathic effects on the germination of tomato and cabbage seeds. As the concentration of the tuber extract increases, the inhibitory effect increases, thus reducing germination and seed vigor in the different substrates. The commercial substrate for tomato and the paper substrate for cabbage may minimize the allelopathic effects of Cyperus rotundus extract during germination of 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 | 0.000 |
| 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".