Performance and stability of performance of spring wheat variety mixtures in organic and conventional management systems in western Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| 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 it