Effect of Selected Metal Ions on the Mycelial Growth of Sclerotinia Sclerotiorum Isolated From Soybean Field in Rongai, Kenya
Bibliographic record
Abstract
White mold caused by Sclerotinia sclerotiorum attacks a wide host range of broad-leafed plants which includes soybeans. The effect of twelve metal ions (Hg+2, Co+3, Ag+1, La+3, Cd+2, Cr+3, Cu+2, Zn+2, Mo+5, Sr+2, Sn+4 and Ba+2) on the growth of pathogenic fungus S. sclerotiorum was studied. The fungus was isolated from infected soybean plant collected at Rongai, Kenya. The isolate was tested for the tolerance to metal ions at concentrations of 50.0, 100.0, 250.0 and 500.0 ppm amended into the C: N (35:1) glucose peptone prepared using 1.5% (3.75g) agar culture medium. All the investigated metal ions exhibited concentration dependent mycelial growth using disc diffusion test. Of 12 metal cations tested, only copper and zinc stimulated mycelial growth of S. sclerotiorum mycelial in relatively higher concentrations. Higher concentrations of Hg+2, Ag+1, La+3 and Cd+2 inhibited growth of fungi causing an opaque halo in the medium. FT-IR spectral analysis of culture filtrate reviewed oxalic acid secreted precipitated primarily as oxalate at the periphery of the fungal colony. This work suggests that strong pollution of soil by some heavy metals could be a restrictive factor of development and pathogenicty of S. sclerotiorum fungi in the environment.
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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".