Characterization of Field Pea Production and Options for Improved Productivity in Mt. Elgon, Uganda
Bibliographic record
Abstract
Field pea is a key source of household income, food and nutrition in Uganda mainly produced in the high land areas of country including south western and Mt. Elgon. The crop fetches a high stable price across markets compared to other grain pulses and yet it has remained outside the mainstream of the research process. The status of this commodity is largely unknown yet such information would support its research agenda to improve productivity and marketing. A study was conducted in the Mt. Elgon sub-zone to determine the status of field pea production, understand its constraints and map out its production cycle. This was done through a survey covering 5 districts namely; Bulambuli, Kapchorwa, Kween, Namisindwa and Mbale. In each district two major field pea growing sub counties were purposively selected, in each sub-county 25 respondents were randomly sampled from a list of field pea producers. A structured questionnaire was then administered; data collated, and analyzed using descriptive statistics and chi-square test. The results revealed that the crop is grown by all gender categories with 60% grown for home consumption and 40% for income. In the districts of Kween and Mbale it is mostly grown for income since the Kween farmers have relatively larger pieces of land whereas Mbale being a commercial hub of the region there is relatively higher price throughout the year which attracts farmers to sell. Field pea is grown alongside other crops which varied by district but was largely grown as sole crop, along boundaries and intercrops depending on availability of land. It is also important to note that it forms a very important part of the rotation system because it plays a significant role in soil fertility restoration as well as serving as a break crop suitable for rotation to minimize the negative impact of cereal based mono-cropping.
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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 | 0.000 |
| 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 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".