Postharvest Management Practices of Grains in the Eastern Region of Kenya
Why this work is in the frame
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Bibliographic record
Abstract
Cereals and legumes play a major role in the production systems and diets of farmers in the semi-arid eastern region of Kenya. Efficient postharvest management can tremendously contribute to food security in these regions. A study was carried out in three counties in eastern Kenya to assess pre and postharvest management practices among farmers. Data was collected using semi-structured questionnaires designed and administered using Kobo Toolbox via android tablets. Results showed that farmers cultivated three main crops: maize (98%), beans 66%), and pigeon peas (28%). The most saved seed crops were beans (80%) and pigeon peas (50%). Majority of the farmers (80%) experienced pre-drying losses due to insects (48%), rodents (40%) and birds (39%). Farmers stored grain for consumption (80%) and for sale (19%). About 48% of farmers stored the grain for more than 9 months. Challenges during grain storage were insects (57%) and rodents (43%). Primary methods of grain preservation included hermetic methods (61%) followed by insecticides (33%). While progress is being made in addressing storage challenges, there still a need to continue building awareness about improved storage technologies and find solutions for pest infestations in the field and drying after harvest.
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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 | 0.001 |
| 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 it