In Vitro Activity of Balanites aegyptiaca and Tamarindus indica Fruit Extracts on Growth and Aflatoxigenicity of Aspergillus flavus and A. parasiticus
Bibliographic record
Abstract
Aflatoxin and especially aflatoxin B1 (AFB1) is a carcinogenic secondary metabolite synthesized by certain Aspergillus species. They contaminate natural and processed agricultural and animal products which render them unfit for consumption. The aim of this study was to evaluate the in vitro effects of Balanites aegyptiaca and Tamarindus indica fruit extracts on the growth and aflatoxin secretion of Aspergillus flavus (SQU21) and A. parasiticus (CBS921.7) strains. The two fruit extracts significantly (P < 0.05) reduced aflatoxin and did not inhibit mycelial dry weights of the two Aspergillus strains. At different concentrations of balanites (2.5-10%), the inhibition of total aflatoxin was 49.9-84.8% for A. flavus (SQU21) and 32.1-84.4% for A. parasiticus (CBS921.7), whereas the inhibition of aflatoxin Bwas 38.2-81.4% and 32.8-80.6% for the two strains. Tamarind fruit extract (2.5-7.5%) caused 28.8-84.2% and 40.7-85.5% reductions in total aflatoxin and 37.1-83.5% and 33.9-85.9% in aflatoxin B for the two strains, respectively. None of these extracts inhibited the fungal growth or detoxified synthetic aflatoxin B1. We have concluded that these fruits contain various inhibitors to aflatoxin biosynthesis and secretion. Therefore, they can be used in combination as safe green biopreservatives to combat aflatoxin contamination of food.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".