Diversity of antifungal actinomycetes in various vegetative soils of Korea
Bibliographic record
Abstract
Diversity of actinomycetes and their antifungal activities against some plant pathogenic fungi were examined in various vegetative soils from 14 different sites in the western part of Korea. Actinomycete counts ranged from 1.17 x 10(6) to 4.20 x 10(6) cfu x g(-1) dried soil. A total of 1510 actinomycetes were isolated from the soil samples. Streptomyces was predominant in soils with a pH range of 5.1-6.5, 9.1-13.0% moisture, and 9.1-11.0% organic matter. Most Micromonospora, Dactylosporangium, and Streptosporangium were distributed in soils with pH 4.0-5.0, 2.0-9.0% moisture, and 4.0-7.0% organic matter. Actinomadura and nocardioform actinomycetes were abundant in soils with pH 4.0-5.0 and 13.1-20.0% moisture and with 9.1-11.0 and 4.0-7.0% organic matter, respectively. Populations of Streptomyces were predominant in all the soils, but were highest in grassland and lowest in mountain-forest soils. Micromonospora was most abundant in pepper-field soil and nocardioform actinomycetes were highest in rice paddy field soil. Dactylosporangium was predominant in lake-mud sediments and pepper-field soil, Streptosporangium in lake-mud sediments, and Actinomadura in mountain-forest soil. Antifungal actinomycetes were abundant in orchard soil and lake mud. More than 50% of antifungal isolates from most soils were classified as genus Streptomyces. Actinomycete isolates that showed strong antifungal activity against Alternaria mali, Colletotrichum gloeosporioides, Fusarium oxysporum f.sp. cucumerinum, and Rhizoctonia solani were predominant in pepper-field soils, whereas those against Magnaporthe grisea and Phytophthora capsici were abundant in radish-field soils.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".