Biological control of <i>Pythium</i> damping-off of pea and sugar beet by <i>Rhizobium leguminosarum</i> bv. <i>viceae</i>
Bibliographic record
Abstract
Rhizobium leguminosarum Jordan bv. viceae strains from pea and lentil root nodules were tested for control of damping-off of pea (Pisum sativum L., host) and sugar beet (Beta vulgaris L., nonhost) crops caused by Pythium sp. "group G". Of the 18 Rhizobium isolates tested, only strain R5 inhibited mycelial growth of Pythium sp. "group G". None of the strains showed any protease activity. Results of indoor experiments in soil artificially infested with Pythium sp. "group G" showed that 10 strains of R. leguminosarum bv. viceae were effective in increasing sugar beet emergence compared with the untreated control, when bacteria were coated onto seeds. Three of the most promising strains, R12, R20, and R21, were further tested for control of damping-off of field pea and sugar beet in a field naturally infested with Pythium spp. R12 and R20 significantly increased seedling emergence of field pea in the two field tests, compared with the untreated control. The efficacy of strains R12 and R20 was similar to that of Pseudomonas fluorescens Migula 708, a biological control agent of Pythium sp. "group G". Rhizobium leguminosarum bv. viceae strains R12 and R21 were the most effective biological control agents for control of sugar beet damping-off in the field experiments. They were as effective as seed treatment with the fungicide ThiramTM in one field experiment. The present study reveals that some R. leguminosarum bv. viceae strains, in addition to their use as biofertilizer, also have the potential to be used for biological control of Pythium damping-off of field pea and sugar beet.Key words: Rhizobium leguminosarum bv. viceae, Pythium sp. "group G", damping-off, biological control, sugar beet, pea.
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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".