Evaluation, genetic control and QTL analysis of Sclerotinia stem rot resistance in soybean
Bibliographic record
Abstract
Sclerotinia stem rot, caused by 'Sclerotinia sclerotiorum' (Lib.) de Bary, is a major disease of soybean ('Glycine max' (L.) Merr.). Morphological and agronomic factors have been associated with resistance to Sclerotinia stem rot but the underlying genetic resistance has proven challenging to identify. The objectives of this research were to develop molecular markers associated with resistance to Sclerotinia stem rot and develop tools to achieve this objective. The barley kernel inoculation, was developed to assess field physiological disease resistance. The barley kernel inoculation severity index (ISI) was compared to controlled environment and natural infection-based resistance evaluation techniques. Significant positive correlations between DSI and ISI were obtained, indicating the potential of this technique for pre-screening breeding material. This may be of value to soybean breeders trying to develop soybean lines resistant to sclerotinia stem rot because of the difficulty in obtaining consistent and reliable natural infection across environments. Different markers were shown to be associated with natural infection resistance and barley kernel inoculation suggesting that responses to inoculation are controlled by different genetic pathways. Genetic interactions for disease response between cultivars of ' Glycine max' and isolates of 'Sclerotinia sclerotiorum' were evaluated in controlled environment inoculations of five soybean cultivars and four genetically-unique isolates of 'S. sclerotiorum'. No differences (P > 0.05) in disease severity were observed among pathogen isolates and no interactions (P > 0.05) were detected either. These results validate the practice of assuming different isolates from agricultural sources of 'S. sclerotiorum' to be equivalent for the purpose of evaluating cultivars for resistance. Recombinant inbred lines derived from a cross between two cultivars a partially resistant, OAC Salem, and a susceptible, Nattosan, were developped and then evaluated at two locations in Ontario in 2000. Several markers were positively associated with greater resistance to Sclerotinia stem rot as measured by ISI and DSI. The variability explained by the markers ranged from 1.9% to 4.3% for ISI and from 3.2% to 10.5% for DSI. Several markers were also associated with maturity. Analysis of co-variance and biplot analysis showed that the QTL for ISI were influenced by maturity but not QTL for DSI.
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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".