Postharvest Practices of Maize Farmers in Kaiti District, Kenya and the Impact of Hermetic Storage on Populations of Aspergillus Spp. and Aflatoxin Contamination
Bibliographic record
Abstract
Aflatoxin contamination in maize by Aspergillus spp. is a major problem causing food, income and health concerns. A study was carried out in Kaiti District in Lower Eastern Kenya to evaluate the effect of three months storage of maize in triple-layer hermetic (PICS™) bags on the population of Aspergillus spp. and levels of aflatoxin. Postharvest practices by maize farmers including time of harvesting, drying and storage methods were obtained with a questionnaire. Aspergillus spp. in soil and maize were isolated by serial dilution-plating and aflatoxin content was measured using Vicam method. Maize was mostly stored in woven polypropylene (PP) and sisal bags within granaries and living houses. Aspergillus flavus L-strain was the most predominant isolate from soil (Mean = 8.4 x102 CFU/g),on the harvested grain (4.1 x 102 CFU/g) and grain sampled after three months of storage (1.1 x 103 CFU/g). The type of storage bag significantly (P ≤ 0.05) influenced the population of members of Aspergillus section Flavi, with A. flavus (S and L strains) and A. parasiticus being 71% higher in PP bags than in PICS bags. Total aflatoxin in maize sampled at harvest and after three months storage ranged from <5 to 42.7 ppb with 55% lower aflatoxin content in PICS bags than in PP bags. After storage, the population of Aspergillus section Flavi was positively correlated with aflatoxin levels. The results of this study demonstrate that PICS bags are an effective management option for reducing population of toxigenic Aspergillus spp. and aflatoxin in stored maize.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".