Yield and Bread‐Making Potential of Spring Wheat Under Mineral and Organic Fertilization
Bibliographic record
Abstract
ABSTRACT The food industry is increasingly interested in bread wheat ( Triticum aestivum L.) produced under low‐input farming. However, the influence of soil management practices and N source type on wheat is unclear. Spring wheat (‘AC Brio’) was grown in 2009 and 2010 near Quebec City, QC, Canada, on a silty clay (SC) and a sandy loam (SL) soil under cool and wet climatic conditions. Nitrogen treatments comprised a control (mineral fertilizer containing P and K only [PK]), a complete mineral fertilizer (NPK), and three organic N sources (liquid swine manure [LSM], liquid dairy cattle manure [LCM], and solid poultry manure [SPM]) applied in the spring to moldboard plowed and minimum till plots. Even though some differences were found in crop N uptake between soil types and production years, the average amount of grains produced at harvest per unit of N applied was greater with NPK (8.5 kg grain kg −1 N applied) than with animal manures but was similar among LSM (6.4), SPM (5.8), and LCM (5.0). The use of LSM and SPM resulted in grain yields similar to those obtained with NPK. The grain protein and gluten content were generally greater with NPK (150 g protein kg −1 and 105 g gluten kg −1 ) than with the organic N sources (142 to 144 g protein kg −1 and 94 to 100 g gluten kg −1 ). However, these disparities had no effect on bread loaf volumes (average of 790 mL). The use of animal manures appears as an interesting alternative to mineral N fertilizers to produce good quality bread‐making wheat.
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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".