Effects of Nitrogen Fertilizer on Protein Quantity and Gluten Strength Parameters in Durum Wheat (<i>Triticum turgidum</i> L. var. <i>durum</i>) Cultivars of Variable Gluten Strength
Bibliographic record
Abstract
ABSTRACT Field studies were conducted over three years at two locations in Saskatchewan, Canada, to determine the effect of nitrogen fertilizer on protein quantity and protein strength in 10 cultivars of durum wheat ( Triticum turgidum L. var. durum ) representing a range of gluten strength. Increasing nitrogen fertilizer resulted in increased protein content in all cultivars across environments. Cultivars were clearly differentiated on the basis of gluten strength using a gluten index (GI), SDS sedimentation (SDSS), alveograph indices of overpressure ( P ) and deformation energy ( W ), mixograph energy to peak (ETP), and mixograph bandwidth energy (BWE) at all fertilizer levels. Variable cultivar response to nitrogen fertilizer was observed only for protein content, GI, and alveograph W . The nature of the cultivar‐by‐fertilizer interaction for GI suggested that the conventional strength cultivars would benefit more from nitrogen fertilizer than the extra‐strong types, which showed no change or slight decreases in GI with nitrogen fertilizer despite an increase in total gluten. SDSS increased with nitrogen fertilizer, following similar trends as protein. Gluten strength rankings of the cultivars by SDSS were maintained with increased fertilizer. Fertilizer had little effect on alveograph P , mixograph ETP, and mixograph BWE. Overall, GI values were more stable across increasing levels of nitrogen fertilizer and resultant increased protein content compared with SDSS, mixograph development time, and alveograph W and L , suggesting it is a good test for estimating intrinsic gluten strength for cultivars with a wide range of protein content.
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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".