Biocontrol of Aspergillus flavus on Peanut Kernels Using Streptomyces yanglinensis 3-10
Bibliographic record
Abstract
The bacterium, Streptomyces yanglinensis 3-10, shows promise in the control of many phytopathogenic fungi. In this study, S. yanglinensis and its antifungal substances (AFS), culture filtrate (CF3-10) and crude extracts (CE3-10), were evaluated for their activity in reducing growth and aflatoxin AFB1 production by Aspergillus flavus, both in vitro and in vivo on peanut kernels. The results showed that in dual culture conditions, S. yanglinensis reduced the mycelial growth of A. flavus about 41% as compared to control. The mycelial growth of A. flavus was completely inhibited on PDA amended with CF3-10 at 3% (v/v) or CE3-10 at 2.5 µg/ml. In liquid culture experiments, growth inhibition ranged from 32.3% to 91.9% with reduction in AFB1 production ranging from 46.4% to 93.4% using different concentrations of CF3-10 or CE3-10. For in vivo assays, CF3-10 at 0.133 ml/g (v/w) or CE3-10 at 13.3 µg/g (w/w) reduced the postharvest decay of peanut kernels by inhibiting visible growth of A. flavus leading to a 89.4% or 88.1% reduction in AFB1 detected, respectively. Compared with the controls, CF3-10 and CE3-10 in A. flavus shake culture significantly reduced expression levels of two AFB1 biosynthesis genes, aflR and aflS. Furthermore, electron microscopy observation showed that CF3-10 (2%, v/v) caused hyphae growth to be abnormal and shriveled, cell organelles to degenerate and collapse, large vacuoles to appear. These results suggest that S. yanglinensis 3-10 has potential as an alternative to chemical fungicides in protecting peanut kernels and other agricultural commodities against postharvest decay from A. flavus.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 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".