Farmer participatory assessment of soil health from Conservation Agriculture adoption in three regions of East Africa
Bibliographic record
Abstract
Abstract The challenges of soil degradation and low crop yield are being addressed in East Africa using a number of soil health-promoting farming systems including Conservation Agriculture (CA). CA is based on principles of minimal soil disturbance, continuous soil cover, and crop diversity, though implementation on farms may vary due to local circumstances. This study evaluated the effect of CA, as practiced by farmers, and compared farmer descriptions of soil health with scientific measures. CA and non-CA fields were compared in regions of Ethiopia (23 farms), Kenya (23 farms), and Tanzania (13 farms) with most fields repeatedly sampled for 2 to 3 years. CA and non-CA fields were located within meters, on soils with the same texture, growing similar crops. CA systems used precision planting, mostly with basins. Soil parameters were assessed using a participatory approach where farmers and field technicians collected data. CA practices improved qualitative soil characteristics as sensed by farmers (e.g., hoe-ability, crusting, smell, water infiltration), and this positive response was consistent across most fields. For qualitative data, the logarithm of the odds ratio estimates method was used to test the probability that CA would provide soil improvement. Fields under the CA treatment had a higher probability of rating better than non-CA fields. Quantitative measurements of pH and microbial respiration validated farmer assessments. CA-managed soils were weakly associated with darker colour, indicating higher soil organic matter. Sandy soils did not appear to improve with CA as dramatically as clay and loam soils, suggesting different CA strategies may be required. We discuss both benefits and drawbacks of this type of participatory, on-farm research. We conclude that farmer participation as citizen scientists will advance soil restoration in East Africa and increase the potential for farmer-to-farmer knowledge exchange of soil-improving practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".