Identification of allelopathic compounds from rice (<i>Oryza sativa</i> L.) straw and their biological activity
Bibliographic record
Abstract
Experiments were conducted to identify allelochemicals from rice (Oryza sativa L.) straw extracts of four rice cultivars (Gin shun, Kasawala mundara, Philippine 2 and Juma 10), and to test their biological activity on barnyard grass (Echinochloa crus-galli P. Beauv. var. oryzicola Ohwi). High performance liquid chromatography (HPLC) analysis showed that the concentration and composition of allelopathic compounds depended on the cultivar. Among the compounds identified were p-hydroxybenzoic acid at 6.87 mg g–1 in Gin shun, p-coumaric acid at 0.34 mg g–1 in Kasawala mundara, ferulic acid at 0.05 mg g–1 in Philippine 2, and p-hydroxybenzoic acid at 6.34 mg g–1 in Juma 10. Preliminary identification by HPLC analysis resulted in peaks with retention times near those of standards, including p-hydroxybenzoic acid m/z = 138). This was confirmed with electron impact/mass spectra. In a bioassay with nine known allelochemicals and their mixtures, p-hydroxybenzoic acid (10–3 M) showed the greatest inhibitory effect on barnyard grass seed germination, seedling length, and dry weight. This suggests that this compound may be a key factor in rice allelopathy on barnyard grass. Key words: Allelopathic compound, rice, barnyard grass, bioassay
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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".