QTL analysis of quantitative resistance to<i>Phytophthora infestans</i>(late blight) in tomato and comparisons with potato
Bibliographic record
Abstract
Quantitative trait loci (QTLs) for resistance to Phytophthora infestans (late blight) were mapped in tomato. Reciprocal backcross populations derived from cultivated Lycopersicon esculentum x wild Lycopersicon hirsutum (BC-E, backcross to L. esculentum; BC-H, backcross to L. hirsutum) were phenotyped in three types of replicated disease assays (detached-leaflet, whole-plant, and field). Linkage maps were constructed for each BC population with RFLPs. Resistance QTLs were identified on all 12 tomato chromosomes using composite interval mapping. Six QTLs in BC-E (lb1a, lb2a, lb3, lb4, lb5b, and lb11b) and two QTLs in BC-H (lb5ab and lb6ab) were most consistently detected in replicated experiments or across assay methods. Lycopersicon hirsutum alleles conferred resistance at all QTLs except lb2a. Resistance QTLs coincided with QTLs for inoculum droplet dispersal on leaves, a trait in L. hirsutum that may contribute to resistance, and dispersal was mainly associated with leaf resistance. Some P. infestans resistance QTLs detected in tomato coincided with chromosomal locations of previously mapped R genes and QTLs for resistance to P. infestans in potato, suggesting functional conservation of resistance within the Solanaceae.
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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 | 0.000 | 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".