An evaluation of farmer-selected spring wheat genotypes from Canada's first organic participatory breeding program
Bibliographic record
Abstract
Despite organic spring wheat’s (Triticum aestivum L.) economic and cultural importance to Canadian agriculture, breeding for organic production systems remains a challenge. Organic growing environments are different from conventional farms in terms of weed species and abundance, fertility, and soil biology. More specifically, many organic farms where most of the organic wheat in Canada is grown (Alberta, Saskatchewan, and Manitoba), are deficient in soil test phosphorus (P). To address these complex challenges, the unorthodox breeding model, participatory plant breeding (PPB), has been proposed. An organic PPB wheat program has been practiced across Canada over the past decade, providing an unprecedented opportunity to explore the influence that selection environment diversity has on the agronomic performance under organic management. Field trials testing 25 PPB genotypes against 6 check cultivars across 12 environments demonstrated three PPB genotypes and one check cultivar to be top yield performers. A second experiment compared a modern cultivar and a landrace cultivar used as parental material in the PPB program, as well as the product of two farmer-selected PPB genotypes by farmers in different geographic locations from the same cross. The genotypes were tested under P limited and P-amended organic conditions, to investigate resilience against P limited conditions. There were no significant differences in yield among genotypes. Farmer genotypes were similar to the modern parent cultivar for protein concentration and lodging severity, and similar to the landrace parent in plant height and kernel mass. More detailed measurements pertinent to phosphorus use, physiology, and uptake efficiency demonstrated that two different phosphorus uptake and use efficiency mechanisms may be occurring between the farmer genotypes. Overall, this research provides evidence that early generation farmer selection is an effective breeding strategy to create distinct genotypes with phenotypic characteristics that are beneficial for organic production systems in Canada. More research is needed to determine how PPB initiatives can better serve organic production systems with a focus on specific site selection at the early generation phase in combination with parental material that may enhance pest resistance and greater phosphorus uptake efficiency. A proposed model of future PPB breeding schemes with special attention to selection environment is presented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".