Field efficacy of nonpathogenic <i>Streptomyces</i> species against potato common scab
Bibliographic record
Abstract
AIMS: The primary objective of these experiments was to reduce pathogenicity and virulence of endemic soil pathogenic Streptomyces strains that cause potato common scab (CS) using nonpathogenic Streptomyces strains to suppress CS in a field situation. METHODS AND RESULTS: Nonpathogenic Streptomyces strains that had shown potential for mitigating CS in greenhouse assays were used in Michigan and Pennsylvania fields known to have high CS disease pressure. Five biocontrol (BC) strains and three potato cultivars were used in 2009, and three BC strains and three cultivars were used in 2010 in each location. The effects of BC strains on CS disease incidence and severity differed between locations, years and potato cultivars. When overall means of individual BC treatments were compared with nontreated controls, CS incidence and severity were decreased by all BC strains in PA2009, PA2010 and MI2010, particularly in cultivar 'Yukon Gold' in MI. Biocontrol treatments also significantly shifted the proportions of superficial, raised and pitted lesion types in some cultivar/biocontrol treatment combinations. CONCLUSIONS: All BC strains significantly reduced CS incidence and severity on 'Yukon Gold' in three of four trials, and one BC strain significantly improved the lesion severity profile in cultivar 'Atlantic'. No BC strain significantly reduced CS incidence and severity on all potato cultivars in the different years and locations. SIGNIFICANCE AND IMPACT OF THE STUDY: Several nonpathogenic Streptomyces strains showed potential to reduce CS incidence and severity on two important potato-chipping cultivars in the field. These results can be further applied to reduce CS disease severity in potatoes.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".