Rotational Effects of Legumes and Non‐Legumes on Hybrid Canola and Malting Barley
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
High costs of fertilizer in western Canada have generated interest in alternative N sources. Legumes produce N through fixation, and may increase soil residual and mineralizable N, thus reducing the need for fertilizer N in subsequent crops. Hybrid canola ( Brassica napus L.) has a high N requirement for optimum yield, but knowledge of rotational effects of legumes on canola is limited. The objective was to determine the effects of legume and non‐legume preceding crops on yield and quality of canola grown the following year and malting barley ( Hordeum vulgare L.) grown after canola. Field pea ( Pisum sativum L.), lentil ( Lens culinaris Medik.), faba bean ( Vicia faba L.), canola, and wheat ( Triticum aestivum L.) harvested for grain, and faba bean grown as a green manure were direct‐seeded at seven locations in 2009. Canola was seeded in 2010 and barley in 2011, with fertilizer N applied at 0, 30, 60, 90, and 120 kg ha −1 . On average, all legumes, except faba bean for seed, produced higher canola and barley yields than when wheat was the preceding crop. Faba bean green manure produced the highest yields, while canola on canola produced the lowest canola yield. The legumes had little negative effect on canola oil or barley protein concentration. Yields of both crops increased with increasing N rate, but canola oil concentration decreased, and barley protein increased. The results indicate that growing legumes for seed before hybrid canola can improve canola and subsequent barley yield without negatively affecting canola oil or malting barley protein.
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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 | 0.000 | 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) | 0.000 | 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