Effect of nitrogen fertilizer application on seed yield, N uptake, and seed quality of Camelina sativa
Bibliographic record
Abstract
Abstract. Malhi, S. S., Johnson, E. N., Hall, L. M., May, W. E., Phelps, S. and Nybo, B. 2014. Effect of nitrogen fertilizer application on seed yield, N uptake, and seed quality ofCamelina sativa. Can. J. Soil Sci. 94: 35-47. Camelina [Camelina sativa (L.) Crantz] is a new crop to western Canada, and research information on its response to nitrogen fertilizer is lacking. Two field experiments were conducted from 2008 to 2010 in Saskatchewan and Alberta, Canada, to determine the effect of N fertilizer application on camelina plant establishment, seed and straw yield, total N uptake in seed and straw, seed oil and protein concentration, N fertilizer use efficiency (NFUE) and percent recovery of applied N (%NR) in seed. Nitrogen fertilizer rates ranged from 0 to 160 kg N ha-1 in exp. 1 and from 0 to 200 kg N ha-1 in exp. 2. There was generally no detrimental effect of high N rates on plant establishment, with the exception of 1 site-year in which there was a slight linear decline in plant density as N rate increased. Seed yield, total N uptake in seed, NFUE and %NR responded to applied N rates at most site-years. Seed yield and total N uptake in seed usually increased while seed NFUE and %NR decreased with increasing N rate. Response trends of yield and total N uptake of straw to applied N were similar to that of seed at the corresponding site-years. Seed oil concentration decreased while protein concentration increased with increasing N rate. In exp. 1, fertilizer rates were not high enough to attain a maximum seed yield; however, maximum seed yields of 2013 kg ha-1 were achieved at an N rate of 170 kg N ha-1 in exp. 2. In conclusion, camelina responded to fairly high rates of applied N similar to responses reported for Brassica juncea on the Canadian prairies.
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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".