Chemical Composition and Bioactive Potential of Extracts from Diospyros capricornuta F. White against Aspergillus flavus and Aspergillus parasiticus
Bibliographic record
Abstract
Diospyros capricornuta is an endemic species widely distributed along the coast of Tanzania that is used as food condiments and traditional medicine. The chemical compositions of Diospyros capricornuta leaves, stem-bark, and root-bark extracts; and their bioactive potentials against Aspergillus flavus and Aspergillus parasiticus were investigated. The leaves, stem-bark, and root-bark samples of D. capricornuta were extracted using Soxhlet apparatus and the resultant extracts were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS). A total of 14 compounds were identified from the extracts, whereby 2,4-di-tert-butylphenol was the most abundant compound in all extracts. The growth and aflatoxin production inhibitions against A. flavus and A. parasiticus were determined via antifungal and antiaflatoxigenic bioassays of the extracts at the concentrations of 0.0, 62.5, 125.0, and 250.0 µg/mL using a poisoned-food method. The High-Performance Liquid Chromatography (HPLC) technique was used to quantify the aflatoxins after bioassays to evaluate aflatoxin inhibitions. The stem-bark extracts at the highest dose of 250.0 µg/mL inhibited aflatoxin production by A. flavus for over 99% and A. parasiticus for over 94%. Overall, the results show that the leaves, stem-bark, and root-bark extracts of D. capricornuta are potential inhibitors against A. flavus and A. parasiticus-the producers of aflatoxins. Keywords: Diospyros capricornuta; Growth inhibitions; Aflatoxin inhibitions; Aspergillus flavus; and Aspergillus parasiticus.
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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 | 0.001 | 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) | 0.001 | 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".