Development of High Levels of Metribuzin Tolerance in Lentil
Bibliographic record
Abstract
Abstract Lentil (Lens culinarisMedik.) is an important and expanding crop in southern Australia and a significant crop in western Canada. Currently, production in both countries is limited by an inability to effectively control weeds, due in part to a lack of registered safe and effective herbicides. Metribuzin is a broad-spectrum herbicide providing an alternative weed control option to the imidazolinones, but it has low crop safety in lentil. Two methods, germplasm screening using a hydroponic sand assay and field screening of a large mutated population of the Australian cultivar ‘PBA Flash’ were initially used to identify lines with putative metribuzin tolerance over current cultivars. Dose–response experiments showed the germplasm line SP1333 had GR50(the rate required to reduce dry weight 50%) values up to four times higher than PBA Flash. However, the mutation selections M043 and M009 had GR50values more than 25 times higher than PBA Flash. A field study in Canada, under conditions of induced shade and no shade 72 h before POST application of metribuzin, confirmed the intermediate level of tolerance in SP1333 and the high level in the two mutant lines compared with 20 Canadian and Australian genotypes. This relative increase in metribuzin tolerance of the two mutant lines over the parent cultivar is higher than all previous reports in a range of crop species. The development of large mutant populations combined with large M2field screens was a successful method for developing high levels of metribuzin tolerance in lentil. The estimated mutation rate of the mutant lines was 9.4×10−8. All three lines are currently being used as parents in lentil breeding programs.
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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 | 0.001 |
| 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".