Evaluation of the Performance of Different Organic Fertilizers on Maize Yield: A Case Study of Kampala, Uganda
Bibliographic record
Abstract
In Kampala city about 60% of animal manure generated is discarded leading to health and environmental challenges. However about 30% of this manure is used as fertilizer mainly in the form of stored animal manure. The manure could also be vermicomposted or anaerobically digestated and used in crop production. However, it has not yet been clearly established which of these options would be most beneficial in producing better crop yields when applied to soils in Kampala. This study evaluated the performance of different organic fertilizers namely vermicompost, digestate and stored cattle manure and unfertilized control on growth and yield of maize (Zea mays spp). The experiment was carried out at Makerere University Agricultural Research Institute Kabanyolo for two seasons (October 2013 to February 2014 and March to June 2014). No significant difference (P > 0.05) in the different organic fertilizers was noted in both the growth and yield of maize in each season. However a significant difference (P < 0.05) in both crop growth and yield was noted when the organic fertilizers were compared with the control. In addition when the different seasons were compared, the growth and yield of maize in season two was generally found to be better (P > 0.05) than that of season one. The interviews conducted with farmer groups showed they generally preferred using stored manure and vermicompost. It can thus be concluded that these fertilizers are best for Kampala thus should be promoted by the municipal authorities to address the rampant poor disposal of animal manure in Kampala.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".