Typology and Prospects for the Improvement of Market Gardening Systems in South-Kivu, Eastern DR Congo
Bibliographic record
Abstract
Vegetables play a very important role in rural and urban communities as both food and a business opportunity. They are fast-growing species, with high nutritional values and able to generate income in a relatively short period compared to other crops. A characterization of market gardening systems was carried out with 368 producers from major market gardening sites in South-Kivu, in Easten of the RD Congo.The aim pursued was to assess existing systems and perspectives to enable steady transition to integrated, sustainable and resilient crop systems. The results showed that very few producers in the region practice plant integration. The typology carried out made it possible to identify three classes of market gardening farms based on adopted agronomic practices, production factors and possible outcomes derived from different systems. Most of the surveyed farms practice crop rotation and are market-oriented. However, they majorly differ in terms of farm size, practices of intercropping, permanent agriculture, mulching, production constraints and producer’s perception on the level of production. For instance, producers who are much more into intercropping also cultivate small areas (less than 0.25 ha). Results also showed that variables such as type of labour, cropping system, type of fertilizer used, mulching practice, adoption of permanent agriculture, producer’s perception of the level of soil fertility, and the water source used affect producer’s appreciation of the level of production obtained (p < 0.05). These variables can be mobilized for improvement of the market gardening system towards more sustainable, diversified and resilient 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 | 0.001 | 0.000 |
| 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".