Zinc and copper interactions under variable soil phosphorus and moisture conditions in selected Saskatchewan soils
Bibliographic record
Abstract
This study evaluates the influence of phosphorus (P) fertilization (without and with added P fertilizer) and soil moisture (stress and no-stress) on efficacy, fate, and transformation of soil applied micronutrients such as copper (Cu), zinc (Zn), and Cu + Zn in a wheat and pea cropping sequence. Wheat was grown as first crop under controlled environment conditions in which micronutrient fertilizer treatments were applied, whereas pea was grown as following crop with recommended macronutrient fertilizers to understand the residual effects of micronutrient fertilization. The high-P fertilizer application and no-stress moisture condition produced the highest grain and straw yield of wheat. Without P fertilization, there were significant negative effects of a combined application of Cu and Zn on wheat yield in a Dark Gray Chernozem. Yield of the following pea crop did not show response to residual Cu and Zn. Micronutrient fertilization increased the Cu and Zn concentration in wheat and pea grain and straw and resulted in increased after-harvest availability and supply in soils. Apart from the increased concentration in labile fraction, a considerable amount of added Cu and Zn was occluded with organic matter and oxyhydroxide species, respectively. Molecular speciation analyses revealed that carbonate associated was the dominant form of Cu and Zn in the soils. Additional Cu species such as Cu-acetate and methoxide, and Zn species including Zn-sorbed montmorillonite species were identified. Insoluble Cu-phosphate and Zn-phosphate complexes were not identified by speciation analyses and do not appear to be a significant factor controlling Cu and Zn availability in these soils.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".