Influence of genotypic mixtures on field pea yield and competitive ability
Bibliographic record
Abstract
Darras, S., McKenzie, R. H., Olson, M. A. and Willenborg, C. J. 2015. Influence of genotypic mixtures on field pea yield and competitive ability. Can. J. Plant Sci. 95: 315–324. Field pea breeding programs have been very successful at improving plant and disease resistance; however, limited success has been achieved in improving the competitive ability of field pea. A study was conducted to determine whether growing field pea in two-way genotypic mixtures could improve the crop's yield and competitive ability. A second objective was to determine if genetic relatedness had any effect on the mixing ability of genotypes. Genotypes were chosen on the basis of pedigree and included two sister lines (CDC1987-3 and CDC1897-14), their common parent (Eclipse), and a distantly related genotype (Midas). The four genotypes were grown as pure stands and as all possible two-way mixtures in field experiments conducted at Lethbridge and St. Albert, Alberta, from 2010 to 2011. The results revealed that CDC1897-3×Eclipse suppressed the model weed (barley); it reduced seed production by 47% (442 kg ha −1 ) and 61% (391 kg ha −1 ) compared with the same components within pure stands at Lethbridge 2010 and Lethbridge 2011, respectively. The same mixture also reduced model weed (barley) biomass production by 61% (831 kg ha −1 ) at St. Albert in 2010, and by 41% (1372 kg ha −1 ) at Lethbridge in 2010. Although mixtures demonstrated the potential to improve field pea competitive ability, results were not consistent across site-years. However, some mixtures did improve yield and competitive ability over the most poorly competitive genotypes in pure stand.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".