Fertilizer response of barley grain in south and central Alberta
Bibliographic record
Abstract
The rate of N fertilizer application is among the most critical decisions for barley (Hordeum vulgare L.) grain production because of its large impact on grain yield, protein content and input cost. A field study was conducted to determine the optimum rate of N fertilizer for a range of barley cultivars in south and central Alberta. Experiments were conducted at 20 sites over 3 yr (1997 to 1999). Nitrogen fertilizer was applied at 0, 40, 80, 120, and 160 kg N ha -1 to 10 cultivars. Grain yields were highest for the two semi-dwarf cultivars (CDC Earl and Kasota) and three of the five general-purpose cultivars (AC Harper, AC Lacombe, Leduc) (high-yielding cultivars) and least for the hulless cultivars (Falcon and Phoenix). Grain yields of the two remaining general-purpose cultivars (CDC Fleet and Seebe) and the malt cultivar (Harrington) were intermediate (medium-yielding cultivars). The economic optimum rate of N fertilizer (NF opt ) for high-yielding cultivars was 14 kg N ha -1 higher than for medium-yielding cultivars and 24 kg N ha -1 higher than for hulless cultivars. Maximum grain yields for all cultivars were obtained when the ratio of available N (fertilizer + soil-derived N) to maximum grain yield exceeded ~28 kg N Mg -1 . Soil-derived N was highly correlated with both pre-seeding soil NO 3 -N and growing season precipitation. Protein concentrations were highest for hulless cultivars and least for high-yielding cultivars, and increased linearly with increasing N availability. Barley responses to P, K, S and micronutrients were also tested in this study and showed similar responses to earlier studies. The optimum rate of N fertilizer for barley in this study was obtained when the ratio of available N (fertilizer + soil-derived N) to maximum grain yield was 25 to 30 kg N Mg -1 . Key words: Hordeum vulgare, nitrogen fertilizer use efficiency, malting barley, protein
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".