Smallholder Maize Farmers Need Better Storage for Food Security: An Exploratory Study over the Storage Types Used in Uganda
Bibliographic record
Abstract
Storage is a crucial link in the food supply chain. It helps to even-out fluctuations in food demand and supply. This ensures food availability during the lean periods. Despite the immense contribution of storage, a knowledge gap exists on the storage types used by smallholder maize farmers, how they are acquired, used, and their cost in Uganda. Storage affects the social and economic well-being of smallholder maize farmers. In this study, smallholder maize farmers in three districts of eastern Uganda (Iganga, Manafwa, and Katakwi) were interviewed during the maize storage season of 2014/2015. The aim was to: describe the different storage types; find out how they were acquired and used; the length of storage and the cost. The findings show that sacks were the most used storage type. Storage types were acquired through purchase; however, some were constructed by the smallholder maize farmers. Affordability and accessibility determined the storage type used. Some storage types were not used across all the districts; for example, the granary was used in two out of the three sampled districts. Thus, the findings show that maize storage is a challenge. We recommend that maize storage facilities should be improved with affordable to the farmers.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".