Aspergilli and Their Aflatoxins Contamination of Poultry and Animal Feedstuff Samples in Western Region of Saudi Arabia
Bibliographic record
Abstract
Aspergillus and their aflatoxins contaminations were studied in sixty poultry and animal feedstuff samples collected from the western region (Jeddah, Makkah and Taif cities) from Saudi Arabia.Fourteen species of Aspergillus were isolated and identified in the present investigation using Potato Dextrose Agar (PDA) at 27ºC.The identification of isolated Aspergillus was confirmed by using internal transcribed spacer (ITS) region sequencing for representative species (194 species) of the collected Aspergillus sp. were sequenced and the obtained sequence results were deposited in Gene Bank under accession numbers.The sequence results indicated to the full correspondence between the molecular identification of the isolated fungi and the morphological identification.Moisture content was considered indicator for the number of Aspergillus isolated, therefore, Aspergillus and their aflatoxins were isolated in high counts from Jeddah and Taif according to the moisture content.Therefore, A. flavus was the most common species (59.78%), followed by A. niger (21.59%).The co-occurrence of Aspergillus species ranged from one species to 6 species per sample.The frequencies of occurrence for most afltoxigenic species isolated from studied samples ranged from 2 to 56%.Aspergillus flavus contaminated the majority of investigated feedstuff samples and the co-occurrence of more than one aflatoxigenic species was reported in many samples.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".