Antagonistic effect of symbiotic bacteria from entomopathogenic nematodes and <i>Bacillus</i> spp. against <i>Panax ginseng</i> root rot pathogens
Bibliographic record
Abstract
Ginseng root rot is a destructive disease of Panax ginseng that seriously affects the yield and quality of P. ginseng. Based on the broad-spectrum suppression properties of entomopathogenic nematode (EPN) symbiotic bacteria, four symbiotic bacteria were selected: Xenorhabdus bovienii (Xbf), Xenorhabdus nematophila (Xna), Xenorhabdus nematophila Cxrd (Xnc) and Xenorhabdus budapestensis (Xbc). Meanwhile, six beneficial Bacillus strains (Bacillus velezensis S1A; Bacillus amyloliquefaciens H4C; Bacillus subtilis N5D; and Bacillus albus HYS, K8, and N2A) were tested. Their individual and combined effects (both in vitro and in P. ginseng slices) on fungi pathogenic to P. ginseng, Fusarium solani, Fusarium proliferatum and Fusarium oxysporum were evaluated. Xenorhabdus budapestensis had the highest suppression effects (up to 82%) on F. solani and F. oxysporum, and a 60% inhibition rate on F. proliferatum, significantly higher than Xnc, Xbf and Xna. Bacillus velezensis and B. subtilis had the strongest suppression rates on F. solani (40%). The combined effects of Xbc and B. subtilis K8 on F. solani and F. oxysporum were stronger than their individual effects. The P. ginseng slice experiment further confirmed the enhanced inhibition of Fusarium by mixing Xbc with B. subtilis K8. In conclusion, we used EPN symbiotic bacteria to suppress P. ginseng root rot and screened two EPN symbiotic bacteria that were highly effective against Fusarium spp. The combination of Bacillus strains with EPN symbiotic bacteria enhanced the suppression effect. Our results provide new biological materials and directions for biological control of P. ginseng root rot.
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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".