Evaluation of Host Resistance and Soil Fumigation for the Management of Black Root Rot of Tobacco in Ontario
Bibliographic record
Abstract
Black root rot of tobacco, caused by the soilborne fungus Thielaviopsis basicola, is a serious problem in many tobacco (Nicotiana tabacum L.)-growing regions of the world. In Ontario, the disease is favored by cool, wet soil conditions and heavy textured or poorly drained soils. Yield loss can be severe under these conditions and fumigants containing chloropicrin are used extensively for controlling the disease. Usually, fumigants control the disease reasonably well, but they are costly and could cause a negative environmental impact. A 2-year study was conducted to evaluate the performance of resistant (AC Gayed) and moderately susceptible (Delgold) tobacco cultivars and soil fumigation to black root rot. T. basicola reduced yield of the susceptible Delgold cultivar. The interaction between genotype and fumigation was significant for most traits examined, indicating that the two genotypes responded differently. Orthogonal comparisons indicate that yield from nonfumigated AC Gayed was higher than that of nonfumigated Delgold. Yield of nonfumigated AC Gayed was also not significantly different from the yield of AC Gayed treated either with Vorlex Plus (1,3-dichloropropene+methyl isothiocyanate) or with Vorlex Plus CP (1,3-dichloropropene+methyl isothiocyanate+chloropicrin). In contrast, the yield of nonfumigated Delgold was lower than Delgold treated with Vorlex Plus CP.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".