How Do the Extracts From the Invasive Plant <i>Acmella radicans</i> Inhibit Germination and Growth of <i>Brassica rapa</i> (Field Mustard) and <i>Chrysanthemum coronarium</i> (Garland Daisy)?
Bibliographic record
Abstract
The allelopathic effects have not previously been studied for Acmella radicans (Jacquin) R. K. Jansen, a new invasive species recorded for Yunnan Province, China. In the current study, the allelopathic potential of root, stem, leaf, flower, and fruit head aqueous extracts from A. radicans on two important vegetable crops, Brassica rapa (field mustard) and Chrysanthemum coronarium (garland daisy), was explored in the laboratory. All four plant part aqueous extracts had some inhibitory effects on B. rapa and C. coronarium in terms of seed germination and seedling growth. Increasing concentrations of aqueous extracts of A. radicans reduced many indicators significantly, including germination rate, the seed germination index, root length, stem length, and biomass of B. rapa and C. coronarium . Generally, the most inhibited parameter was root length, followed by shoot length and biomass, with the lowest being seed germination. In terms of allelopathic response index, flowers and fruit heads yielded the strongest inhibition, followed by leaves and stems, with the lowest impact from root extracts. Root extracts had positive effects at 0.0125–0.025 g·mL −1 . The inhibition rates for A. radicans extracts on B. rapa were generally higher than those of C . coronarium . It is concluded that A. radicans has allelopathic potential on vegetable crops with the overall inhibition rates ranked in the order flower and fruit head > leaf > stem > root. This was the first study to show that the allelopathic potential of A. radicans against crops may be strongly linked to its invasion and expansion.
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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".