The Potential of Baobab (Adansonia digitata L.) Extracts as Biocontrol on the Growth and Aflatoxin Production by Aspergillus flavus and A. parasiticus
Bibliographic record
Abstract
Moulds and associated mycotoxins, especially aflatoxins, are important factors that advesely affect food and feed produced from contaminated plant and animal prodcuts. They are lethal to humans and animals, which emphasizes the great concern in food and feed production. In this study, the effects of baobab (<em>Adansonia digitata</em>) extracts on the vegetative growth and aflatoxin secretion by <em>A. flavus </em>(SQU21) and <em>A. parasiticus</em> (CBS921.7) strains were exzmined. Different concentrations of baobab fruit extract (1.5, 3, 5, and 7% w/v) and essential oil (0.5, 1, 3 and 5% v/v) was used. Fruit extract of baobab apparently inhibited the total aflatoxin secretion up to 20.4-68.5% for <em>A. flavus</em> and 11.9-69.1% for <em>A. parasiticus, </em>whereas the inhibition of aflatoxin B<sub>1 </sub>production ranged between 29.9-79.2% and 13-68% for the two strains, respectively. The highest inhibition levels of total aflatoxin and aflatoxin B<sub>1</sub> secretion by <em>A. flavus</em> (47.2-95.7%; 28.1-89.7%) and <em>A. parasiticus </em>(42.7-93.3%; 25.9-80.2%) were obtained with essential oil extracted from baobab seeds. The two extracts significantly reduced the vegetative growth and the mycelial dry weights of selected fungi. This indicates the antifungal activity and inhibitory effect of baobab on the growth and aflatoxin production by the two toxigenic strains. Thus, fruit extract and essential oil of <em>A. digitata</em> can be suggested as potentially effective biocontrol and biopreservative substrates against food and feed contamination by aflatoxigenic moulds.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".