A review of copper fertilizer management for optimum yield and quality of crops in the Canadian Prairie provinces
Bibliographic record
Abstract
Deficiency of copper (Cu) in Canadian prairie soils is not widespread, but whenever it occurs it can cause a drastic reduction in seed yield and quality of most cereals, especially wheat. Field experiments conducted in western Canada indicated that broadcast-incorporation of granular Cu fertilizers prior to seeding at 3-5.6 kg Cu ha -1 was usually sufficient to prevent Cu deficiency in wheat, and improve seed yield and quality. At lower rates (< 2.0 kg Cu ha -1 ), broadcast-incorporation of granular Cu fertilizers was not effective, while surface spray-broadcast followed by incorporation of liquid Cu fertilizers was much more effective in increasing seed yield of wheat in the first year of application. Surface broadcast without incorporation and seedrow-placed granular Cu fertilizers were much less effective in improving seed yield of wheat than their foliar or soil-incorporated applications. In the growing season, foliar applications of Cu at 0.20 to 0.28 kg Cu ha -1 to wheat at the Feekes 6 (first node of stem visible at base of shoot or stem elongation), Feekes 10 (sheath of last leaf completely grown or flag-leaf) and early boot growth stages were very effective in restoring seed yield, while Cu applications at the Feekes 2 (four-leaf) or Feekes 10.5 (complete heading) growth stage did not have a consistent effect to correct damage caused by Cu deficiency. Some Cu fertilizers (e.g., Cu oxide) were less effective than others in preventing/correcting Cu deficiency. Soil application at relatively high rates produced residual benefits in increasing seed yield for a number of years. The sensitivity of crops to Cu deficiency is usually in the order (wheat, flax, canary seed) > (barley, alfalfa) > (timothy seed, oats, corn) > (peas, clovers) > (canola, rye, forage grasses). Stem melanosis in wheat was associated with deficiency of Cu in soil, and the disease was reduced substantially with Cu application. A high level of available P in soil was observed to induce/increase severity of Cu deficiency in wheat. Soil analysis for diethylene triamine pentacetic acid- (DTPA) extractable Cu in soil can be used as a good diagnostic tool to predict Cu deficiency, but there was a poor relationship between total Cu concentration in shoots and the degree of Cu deficiency in crops. Application of Cu fertilizers to wheat on Cu-deficient soils also generally improved seed quality. Key words: Application time, Cu source, foliar application, granular Cu, growth stage, placement method, rate of Cu, seedrow-placed Cu, soil incorporation, 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".