Seeding Rate, Nitrogen Rate, and Cultivar Effects on Malting Barley Production
Bibliographic record
Abstract
The malting barley ( Hordeum vulgare L.) industry is often challenged by the availability of sufficient volume and quality to meet demand. Our objective was to evaluate the effects of agronomic practices on grain uniformity, protein concentration, yield, and yield components. Field experiments were conducted from 2005 to 2008 at eight rain‐fed locations in western Canada. The effects of two seeding rates (200 and 400 seeds m −2 ) and five N (0, 30, 60, 90, and 120 kg ha −1 ) rates on two two‐row barley cultivars (‘AC Metcalfe’ and ‘CDC Copeland’) were determined. Each experiment was conducted for 3 yr at each location (24 environments). CDC Copeland displayed some advantages over AC Metcalfe including higher grain yield, lower protein and more uniform kernels. For both cultivars, kernel weight, and plumpness were lower at the higher seeding rate; protein was also lower, maturity was earlier and kernels were more uniform. With increasing N rate, barley yield, kernel weight, and tillers plant −1 increased, but days to seed maturity and protein concentration also increased, and kernel plumpness and seed uniformity decreased. The increase in protein was less pronounced with CDC Copeland suggesting that there may be less risk with this cultivar of unacceptable protein levels at relatively high N rates. At many environments barley plant stand decreased while lodging increased with increasing N rates. To improve the likelihood that barley will be acceptable for malting growers should select low‐protein varieties, seed at relatively high rates and limit N application.
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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 | 0.001 | 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 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".