Allelopathic Potential of Compounds in Selected Crops
Bibliographic record
Abstract
Allelochemicals cause yield differences under various ecosystems worldwide. Studies were conducted at the National Crops Resources Research Institute, Namulonge, Uganda during 2016 to investigate allelopathic properties of bioactive compounds in upland rice (NERICA 1), Desmodium uncinatum, Zea mays (LONGE 6H) and Mucuna pruriens root leachates. Studies involved pot screening, equal compartment agar experiments, germination tests and growth of potted plants. Results under the pot study indicated that maize, rice and mucuna leachates significantly (P ≤ 0.05), reduced root lengths (49%-63%), plant heights (48%-66%) and biomass (63%-75%) for Ageratum conyzoides, Bidens pilosa and Gallinsoga. parviflora weeds. G. parviflora root growth was reduced (20%-41%) and stem growth declined (19%-42%) when maize, rice and mucuna leachates were applied in the equal compartment agar study. Increased leachate concentrations (25%-75%) significantly (P ≤ 0.05), increased the mean germination time (0.4-2.8 days) for mucuna, desmodium, rice and maize as seed germination indices (SGI) were reduced (1.3%-49%). Potted mucuna, maize and desmodium reduced (1.3%-49%) rice root length. Potting mucuna with maize reduced (32%) mucuna leaf width while desmodium growth parameters were reduced (49%-64%) when potted with maize and mucuna. Potting maize with mucuna or desmodium increased the maize leaf length (18%) and SGI (25). Application of higher (25%-75%) rice/maize leachate concentrations similarly increased the maize leaf length (31%) and SGI (119). Allelopathic properties affect seed germination, crop growth and development, and characterise ecosystems age structures. Strategic management of crops under allelopathic ecosystems is critical.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".