Resistance to bacterial spot (<i>Xanthomonas gardneri</i>) on foliage and fruit of commercial processing tomato cultivars
Bibliographic record
Abstract
Bacterial spot of tomato (Xanthomonas gardneri Šutić) is an economically important disease of processing tomatoes in Ontario, Canada, resulting in premature defoliation and fruit damage. Breeding efforts for host resistance focus on assessments of foliar health as opposed to fruit health but anecdotal reports from industry suggest a poor relationship between fruit and foliar resistance. To investigate this, nine commercial cultivars were inoculated at the vegetative (foliar experiment) or reproductive (fruit experiment) stages in replicated field experiments from 2016 to 2018. In the foliar experiment, the standardized area under the disease progress curve (sAUDPC) for defoliation was 51% to 54% higher for ‘TSH18’ than ‘H9706’, ‘Hypeel 696’, and ‘H3406’, but equivalent to ‘CC337’. Fruit disease incidence was 49% and 47% lower for ‘CC337’ than ‘TSH18’ and ‘H9706’, but equivalent to ‘H3406’ and ‘Hypeel 696’. Fruit disease severity was 63% and 60% lower for ‘CC337’ than ‘H9706’and ‘H3406’, respectively, but equivalent to ‘TSH18’ and ‘Hypeel 696’. However, in the fruit experiment, fruit disease incidence was equivalent among cultivars, while the disease severity index for ‘H9706’ (3.4) was higher than ‘Hypeel 696’ (0.7). Furthermore, rank correlation analysis between sAUDPC and fruit disease variables failed to meet the criteria for a significant and strong relationship (r ≥ 0.8 or ≤ −0.8 and P ≤ 0.05). Additional research is needed to better understand the mechanisms of fruit infection by X. gardneri. In the meantime, scientists should consider the limitations of assessing only foliar damage as an evaluation method for bacterial spot management tools in tomato.
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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) | 0.001 | 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 | 0.001 |
| 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".