Allelopathic Activity of Cymbopogon nardus (Poaceae): A Preliminary Study
Bibliographic record
Abstract
The inhibitory effects of aqueous methanol extract of Cymbopogon nardus (L.) Rendle were determined on seedling growth of eight test plant species: alfalfa (Medicago sativa L.), cress (Lepidum sativum L.), lettuce (Lactuca sativa L.), rapeseed (Brassica napus L.), barnyard grass (Echinochloa crus-galli L.), Italian ryegrass (Lolium moltiflorum Lam.), jungle rice (Echinochloa colonum (L.) P. Beauv.) and timothy (Phleum pratense L.). The bioassay was conducted with four extract concentrations (0.01, 0.03, 0.1 and 0.3 g dry weight equivalent extract/mL). The extracts inhibited significantly shoot and root growth of four test plants such as cress, lettuce, rapeseed and Italian ryegrass at the concentration ? 0.03 g dry weight equivalent extract/mL. The inhibitions of shoots and roots increased with increasing extract concentrations. The concentrations required for 50% growth inhibition of all test plants ranged 0.007-0.090 g dry weight equivalent extract/mL. Roots of all test plants were more sensitive to the extract than their shoots. Lettuce was most sensitive, follows by cress and timothy. The results suggest that C. nardus may have allelopathic compounds and may be a candidate for isolation and identification of allelopathic compounds to develop an alternative weed management option.
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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".