Determination of Ochratoxin A in Selected Cereal Grains Retailed in Nairobi County, Kenya
Bibliographic record
Abstract
Ochratoxin A (OTA) belongs to a group of mycotoxins which are a key threat to quality of cereals based foodstuff. Mycotoxins are toxic, carcinogenic, nephrotoxic, neurotoxic and immunotoxic secondary metabolites of certain molds occurring in crop produce and their products. OTA occurs naturally in majority of foodstuffs such as coffee, cereal grains and beverages. The aim of the study was to determine the levels of OTA in cereal grains sampled from various market outlets in Nairobi County, Kenya. The levels of OTA were determined from 27 samples of finger millet (Eleusine coracana), wheat (Triticum aestivum) and sorghum (Sorghum bicolor) grains. The levels of OTA in grains was determined by High Performance Liquid Chromatography (HPLC). The results indicated that wheat grains recorded the highest contamination (2.1478±0.3061 ng/g) followed by sorghum (1.0311±0.0635 ng/g), while finger millet recorded the lowest levels (0.6918±0.0315 ng/g). Cereal samples from Gikomba outlet had a higher contamination (1.1750±0.0353 - 3.8147±0.4317 µg kg-1) than those from Githurai outlet (0.1244±0.0795 - 0.4808±0.0321 µg kg-1). OTA levels in samples from Nyamakima outlet were below the detection limit of HPLC (0.03 µg/L). Though levels are lower than maximum allowable limits for OTA in cereals in the European Union (5 µg/kg) and United Kingdom (10 µg/kg), chronic exposure can have serious health risk. The study provides baseline data on the levels of OTA in finger millet, sorghum and wheat grains retailed in Nairobi County, Kenya. The information creates awareness on the potential health risk associated with chronic exposure to OTA from cereals.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".