Irrigated soft white spring wheat is largely unresponsive to conservation management in rotations with dry bean, potato and sugar beet
Bibliographic record
Abstract
Historically, soft white spring (SWS) wheat (Triticum aestivum L.) has been a crop choice in southern Alberta’s irrigation districts. A 12-yr (2000–2011) study compared conservation (CONS) and conventional (CONV) management for SWS wheat in 3–5-yr rotations with dry bean (Phaseolus vulgaris L.), potato (Solanum tuberosum L.), and sugar beet (Beta vulgaris L.). Conservation management incorporated reduced tillage, compost, cover crops, and narrow-row dry bean. Wheat was largely unresponsive to CONS management, with only 2 of 13 parameters showing significant positive effects: greater grain Ca (605 vs. 576 μg g−1 on CONV) and S concentrations (1137 vs. 1105 μg g−1 on CONV). Two parameters showed significant negative responses to CONS management: shorter plant height (82.8 vs. 84.8 cm on CONV) and higher take-all [Gaeumannomyces graminis (Sacc.) Arx & Olivier var. tritici Walker] severity (1.34 vs. 1.27 rating on CONV). The remaining nine parameters were unresponsive: plant density, days to maturity, grain yield, grain protein concentration, test weight, kernel hardness, wheat stem sawfly [Cephus cinctus Norton (Hymenoptera: Cephidae)] damage, and grain P and K concentrations. With a backdrop of continued decline in irrigated SWS wheat hectarage, we feel our data is relevant to other wheat classes grown under irrigation in southern Alberta.
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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 | 0.000 |
| 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".