Sedentary Agriculture and Its Implications on Soil Quality in Agro-pastoral Semi-arid Karamoja, Uganda
Bibliographic record
Abstract
Uganda Government embarked on promoting sedentary agriculture in Karamoja agro-pastoral semi-arid livelihood zone, which experience rapid environmental and high soil quality (SQ) decline. However, studies on sedentary agriculture’s impact on soil quality using farmer’s knowledge is limited. Consequently, a survey was carried out in Karamoja (Iriiri, Matany Sub-counties of Napak of districts and Rengen sub-county of Kotido) to determine the soil quality indicator parameters based on the farmers knowledge in order to build a local soil knowledge data base to better inform sustainable land use strategies. Using a semi-structured questionnaire, forty indigenous farmers per sub-county, were interviewed between August and September, 2015. The study took into account the social demographic characteristics of the people, farming enterprises, methods of crops production, crops yields trends, causes of the perceived yields trends and soil quality indicators. Prospects of developing Karamoja indigenous knowledge data base lies in visible feature that predict soil quality. Farmers used 36 parameters to determine SQ. The parameters were clustered into five categories; soil, crop, biological, environmental and management each category contributing to 42, 19,14,8 and 17% of the total indicators, respectively. The relationship between age group and the perceived indicators of soil fertility was statistically significant (p-value = 0.045) with the majority stating that they use either soil colour, soil depth or soil texture to express the fertility of soil. The farmer’s soil quality indicators assessed in this study, is important in establishing indigenous-scientific hybrid knowledge data base to enhance soil fertility maintenance and better inform policy makers and other stakeholders on development of sustainable land use strategies.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".