Allelopathic Potentials of Eight Barley Cultivars on Brassica jucea (L) Czern. and Setaria viridis (L) p. Beauv.
Bibliographic record
Abstract
The allelopathic potential of the foliage tissues of eight barley cultivars was investigated using seedlings bioassays of Indian brown mustard (Brassica juncea) and green foxtail (Setaria viridis) as typical broadleaf and grass weeds of the croplands. The correlations of allelochemical compounds with seed germination of weeds were determined. The barley cultivars used were Jackson, Bronco, CDC Dolly, B1602, Harrington, UNA80, Stander, and TR251. Three dilutions of the extracts of each barley cultivar (20, 10 and 5 g/L) plus deionized distilled water, as a control, were assayed on the target weeds. The effects of barley cultivars and extract concentrations on seed germination and radicle and shoot lengths of the target weed seeds were highly significant (P<0.001). By increasing the concentration of the allelopathic extracts, the percent germination, radicle and shoot lengths of both target plants seedlings decreased. Seed germination and seedling growth of B. juncea were more sensitive than those of S. viridis. Relative to the germination inhibition of target weed seeds in comparison to the untreated control, the selected barley cultivars were categorized as being highly allelopathic, moderately allelopathic and of low allelopathic potential. Among the phenolic compounds detected, the cumulative effect of four small-quantity-compounds (vanillic, chlorogenic, p-coumaric, and ferulic acids) on average weed germination was very high (R 2 = 0.83), with B. juncea it was high (R 2 = 0.70) and with S. viridis it was very low (R 2 = 0.15). The two high concentration phenolic compounds of protocatechuic and p-hydroxybenzoic acid, when accumulated with the small-quantity phenolic compounds of barley cultivars, reduced the weed seeds germination correlation to r=- 0.11.
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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".