Identification of allelopathic compounds from rice (<i>Oryza sativa</i> L.) straw and their biological activity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it