Resistance to <i>Turnip mosaic virus</i> in <i>Brassica rapa</i> and <i>B. napus</i> and the analysis of genetic inheritance in selected lines
Bibliographic record
Abstract
Forty‐two Brassica rapa and Brassica napus lines were tested for resistance to Turnip mosaic virus (TuMV) isolates representing the three major pathotypes in Europe. Of these lines, 11 were susceptible to all pathotypes; nine were resistant to one pathotype; eight were resistant to two pathotypes; and 14 were resistant to all three pathotypes. Of the lines tested, 23 were either able to, or had the potential to, discriminate between two different pathotype‐3 isolates. Genetic models for inheritance of resistance were proposed for four B. rapa lines: Jong Bai No. 2 had dominant resistance to pathotype 1 conferred by a single allele; PI418957C and Jin G 55 had recessive resistance to pathotype 4 where a single allele was required; PI418957C also had recessive resistance to pathotype 3 where a model with one of two epistatic, unlinked loci was proposed. Jong Bai No. 1 also had recessive resistance to pathotype 3, apparently conferred by alleles at three loci, where any two of the three loci were epistatic and required for resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".