Widening the genetic base of cultivated lentil through hybridization of Lens culinaris ‘Eston’ and L. ervoides accession IG 72815
Bibliographic record
Abstract
Tullu, A., Bett, K., Banniza, S., Vail, S. and Vandenberg, A. 2013. Widening the genetic base of cultivated lentil through hybridization of Lens culinaris ‘Eston’ and L . ervoides accession IG 72815. Can. J. Plant Sci. 93: 1037-1047. Lentil (Lens culinaris Medik.) is affected by many stresses and the genetic variation for resistance to some of these stresses is limited in the cultivated germplasm. Introgression of genes from diverse sources for the improvement of disease resistance and agronomic performance is urgently needed. An interspecific recombinant inbred line (RIL) population designated LR-26 was developed from a cross of L. culinaris ‘Eston’ and L. ervoides (Brign.) Grande accession IG 72815. RILs were phenotyped (1) to examine the inheritance of resistance to the more aggressive race 0 of Colletotrichum truncatum (Schwein.) Andus & W.D. Moore, causal agent of anthracnose, for which resistance is lacking in the cultivated species and (2) to study the genetic variation in agronomic traits and their relationships to each other. Greenhouse studies were conducted to screen for resistance to race 0 of C. truncatum and evaluate RILs for variations of agronomic characters. Two recessive genes conferred resistance in L. ervoides accession IG 72815. Traits varied significantly and showed transgressive segregations. Seed yield had a significant and positive relationship with biomass, straw yield, seed weight and harvest index. About 20 lines that performed better than Eston in terms of podding ability, lodging, and stand at maturity can be used in a breeding program. LR-26-180 had an 8% greater seed weight than Eston, suggesting that IG 72815 has alleles contributing positively to seed size. Overall, results show that IG 72815 can be used in breeding programs to improve disease resistance and quantitative traits of lentil.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".