Screening sweet cherry cultivars from the Pacific Agri-Food Research Centre Summerland breeding program for resistance to brown rot (<i>Monilinia fructicola</i>)
Bibliographic record
Abstract
Recently released cultivars and advanced selections of sweet cherries (Prunus avium L.) from the breeding program at the Pacific Agri-Food Research Centre at Summerland, British Columbia, were screened for resistance to brown rot [Monilinia fructicola (Wint.)]. From 2000 to 2003 a range of sweet cherries were inoculated by spraying with a conidial suspension of 1 × 10 4 colony-forming units per mL of Monilinia fructicola, placed in a growth chamber at 13°C and rated for rot at 8 and 11 d after inoculation. The response of cultivars or selections varied from year to year. In 2000, 10 of 14 cultivars had disease incidences of over 50% by day 8, whereas, in 2002, only 2 of 19 cultivars had disease incidences greater than 50%. Staccato™, Stardust and Sweetheart were in the least susceptible category, that is, the percent rot infection was significantly less than the mean of all genotypes in 2 of the 4 yr. Santina, Skeena, and 13N-07-32 were in the least susceptible category in 1 of 4 yr. The level of resistance to brown rot was not very high. For the least susceptible cultivars such as Staccato™, Stardust, or Sweetheart, the level of resistance was not high enough to grow the crop without fungicide applications. Key words: Prunus avium, resistance, inoculation
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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 | 0.001 | 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".