Effect of Nitrogen Fertilizer on Nitrogen Accumulation, Translocation, and Use Efficiency in Dryland Oilseed Flax
Bibliographic record
Abstract
Oilseed flax (Linum usitatissimum L.) yields are primarily fertilizer‐limited, especially by N supply in the semiarid regions of North China. This study was conducted to determine whether N accumulation, translocation and N use efficiency (NUE) could be manipulated through N. The effects of N on N translocation, oilseed flax yield, oil content and NUE were studied at Zhangjiakou, China. Plants were grown at 0, 45, 90, and 135 kg N ha−1 (designated as the control, low N, moderate N, and high N, respectively), in 2011 and 2012. We found that N accumulation in leaves and capsule pericarps reached the maximum at anthesis and kernel developmental stage, respectively, then decreased rapidly before maturity. Averaged over 2 yr, N translocation from leaves to the seeds increased by 43, 150, and 150% under low N, moderate N, and high N, respectively, compared to the control; similarly, N translocation in capsule pericarps increased by 43, 243, and 190%, respectively. We discovered that leaves contributed the largest proportion of the seed N (averaging 80% in both years), and secondarily by the capsule pericarp N, which contributed 12% (in 2011) and 9% (in 2012) of the seed N. The highest seed yields were 2270 kg ha−1 (in 2011) and 1903 kg ha−1 (in 2012) which were obtained with the moderate N. Oil content was not affected by N. Nitrogen use efficiency decreased with progressively higher rates of N. The results suggest the moderate‐N supply was adequate for promoting N translocation, and increasing N harvest index, NUE, and the productivity of oilseed flax.
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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) | 0.000 | 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 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".