Pathogenic <i>Streptomyces</i> spp. Abundance Affected by Potato Cultivars
Bibliographic record
Abstract
Potato cultivars vary in their tolerance to common scab; however, how they affect common scab-causing Streptomyces spp. populations over time is poorly understood. This study investigated the effects of potato cultivar on pathogenic Streptomyces spp. abundance, measured using quantitative PCR, in three spatial locations in a common scab-infested field: (i) soil close to the plant (SCP); (ii) rhizosphere soil (RS); and (iii) geocaulosphere soil (GS). Two tolerant (Gold Rush, Hindenburg) and two susceptible cultivars (Green Mountain, Agria) were tested. The abundance of pathogenic Streptomyces spp. significantly increased in late August compared with other dates in RS of susceptible cultivars in both years. Abundance of pathogenic Streptomyces spp., when averaged over locations and time, was significantly greater in susceptible cultivars compared with tolerant cultivars in 2014. Principal coordinates analysis showed that SCP and RS soil properties (pH, organic carbon, and nitrogen concentrations) explained 68 and 76% of total variation in Streptomyces spp. abundance among cultivars in 2013, respectively, suggesting that cultivars influenced common scab pathogen growth conditions. The results suggested that the genetic background of potato cultivars influenced the abundance of pathogenic Streptomyces spp., with five to six times more abundant Streptomyces spp. in RS of susceptible cultivars compared with tolerant cultivars, which would result in substantially more inoculum left in the field after harvest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 0.001 |
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 teacher head, 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".