Heavy metal content and microbiological quality of <I>Yaji<I> (complex spice mixture) sold within Kano metropolis
Bibliographic record
Abstract
In recent years, food biosafety has been a priority, as such a study was carried out on the microbiological and heavy metal contents of yaji; a complex spice mixture sold within Kano metropolis. A total of nine yaji samples were purchased randomly in several retail stores within Kano metropolis and compared with 3 samples prepared in the laboratory. The result of the analysis showed that the total aerobic mesophilic count, fungal count and coliform count ranged from 3.35×106 - >3.00×107cfu/g, <1.00×103 – 9.60×106cfu/g, and 3.6 - >1100MPN/g respectively. Staphylococcus aureus, Escherichia coli, Salmonella, Enterobacter and Klebsiella species were the bacteria isolated while Fusarium, Rhizopus and Aspergillus species were the fungi isolated from the samples. The counts obtained were higher than the maximum acceptable levels provided by the ISO and FAO. The ranges of the concentration of heavy metals in dry weight were; lead 0.001 – 0.003, nickel 0.001 - 0.005, copper 0.002 - 0.020, zinc 0.105 – 0.223, iron 0.004 – 0.009 g/Kg. The levels of metals found in the samples were within the standard limits approved by WHO. This study showed that the samples were not contaminated with the studied heavy metals but were found to harbor microorganisms, which can pose serious health hazard to consumers. It is therefore recommended that strict hygienic measures should be taken during yaji preparation since the laboratory prepared yaji were less contaminated. Public enlightenment on the dangers of heavy metals consumption should be provided as continuous/routine consumption may result to the bioaccumulation of harmful metals in the body. Key words: Microbiological, heavy metal, spice, yaji, Kano.
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 | 0.000 |
| 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 | 0.001 |
| 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".