Screening Cover Crops for Weed Suppression in Conservation Agriculture
Bibliographic record
Abstract
The use of herbicides amongst smallholder farmers is minimal because herbicides are expensive and they require specialized application equipments. Weeds are problematic in conservation agriculture where herbicides are expensive for smallholder farmers. The use of cover crops can help to suppress weed growth and development by creating an environment which is not suitable for weeds survival. Cowpea (Vigna unguiculata (L.) Walp) dolichos lablab (Lablab purpureus L.) and velvet bean (Mucuna pruriens (L.) DC) were evaluated for biomass accumulation and weed suppression under conservation agriculture system in two contrasting experimental sites: Ukulinga and Bergville in KwaZulu-Natal. Bare plot and herbicide treatments served as controls. Treatments were laid in a randomized complete block design, replicated three times. Mucuna pruriens (L.) DC had the highest biomass accumulation in both sites Bergville (0.72 t/ha) and Ukulinga (1.59 t/ha). Cowpea had the lowest biomass accumulation in Bergville (0.59 t/ha) and lablab was the lowest in Ukulinga (0.88 t/ha). Lablab was effective in suppressing weed biomass in Bergville (P < 0.05). Cowpea performed best in suppressing weed biomass in Ukulinga (P < 0.05). The results suggest that cowpea and lablab can be effective for weed suppression and therefore can be recommended for use in conservation agricultural systems.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".