Grain protein as a post-harvest index of N sufficiency for hard red spring wheat in the semiarid prairies
Bibliographic record
Abstract
Results from fertilizer trials with hard red spring wheat (Triticum aestivum L.) conducted throughout southwestern Saskatchewan under fallow and cereal stubble cropping conditions were used to determine if grain prote in concentration (GPC) could be used as an index of N sufficiency to the crop. Critical GPC were determined using the Cate-Nelson R2 procedure. Grain yield and protein concentration were negatively correlated under stubble and for fallow cropping when yields were below 2858 kg ha–1 ± 179, with grain protein decreasing by 15 mg g–1 for every 1000kg ha–1 yield increase. In these two groups of observations, water and N availability, N yield and grain produced per unit N available suggested that water availability was the dominant factor limiting grain yield. For the portion of fallow observations in which grain yields were higher than 2858 kg ha–1, water availability was not limiting, and N availability controlled grain yield and protein concentration. In this group, a GPC of 128 mg g–1 (range of 123 to 135 mg g–1) marked the transition between N deficiency and sufficiency. Under stubble cropping and for the lower-yielding portion of the fallow cropping system, where water stress was predominant, the Cate-Nelson analysis identified critical protein concentrations of 160 and 154 mg g–1, respectively. However, these critical concentrations separated populations into moderately and severely water-stressed crops, rather than providing a separation based on N availability. We concluded that GPC as a post-harvest index of N sufficiency must be used with caution in southwestern Saskatchewan. Grain protein concentration below the critical limit of 128 mg g–1 is a reliable indicator of low N sufficiency, but high grain protein does not necessarily imply N sufficiency because, frequently, grain yield and protein concentration are negatively correlated due to water stress. Key words: Yield, protein, N availability, critical levels, water stress
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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 | 0.001 | 0.001 |
| 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".