Performance and stability of performance of spring wheat variety mixtures in organic and conventional management systems in western Canada
Bibliographic record
Abstract
SUMMARY Wheat (Triticum aestivum L.) variety mixtures represent a relatively unexplored avenue for maintaining and stabilizing yield for both organic and conventional producers. The present study examined the responses of three Canadian western red spring wheat varieties in sole crop and in variety mixtures to varying levels of simulated and natural competition, as well as environmental stress at one conventionally and two organically managed locations in central Alberta, Canada, between 2003 and 2005. Three modern hard red spring wheat varieties (Superb, semi-dwarf; AC Intrepid, early maturing and 5600HR, tall), along with 13 two- and three-way variety mixtures, were planted under two levels of simulated weed (Brassica juncea L.) competition at each of the eight location-years. The B. juncea weed competition treatment decreased yields at all locations. Overall yield was lowest at the certified organic farm and highest under conventional management. Sole-crop semi-dwarf Superb and all three Superb–Intrepid mixture entries consistently yielded among the highest, regardless of management system, testing location or competition treatment. The 1:1 and 1:2 Superb–Intrepid mixture entries were the most stable of all entries tested. Early season vigour was strongly associated with yield, with the strongest correlation occurring under low-moisture, low-nutrient, high-competition conditions at the certified organic farm. Spring wheat variety mixtures may provide greater stability with little or no reduction in yield, while providing greater competitive ability.
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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 | 0.001 |
| 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".