Chemical and molecular scale speciation of copper, zinc, and boron in agricultural soils of the Canadian prairies
Bibliographic record
Abstract
The general incidence of copper (Cu), zinc (Zn), and boron (B) deficiencies in soils of the Canadian prairies may be related to identifiable, highly variable, inherent soil attributes. The objective of this study was to investigate the variability of selected properties and their relationship with the bioavailability, forms, and distribution of Cu, Zn, and B in a range of prairie soils. The nature of these micronutrient distributions were evaluated by measuring extractable concentrations, supply rates, and by separation into various chemical pools through sequential extraction and spectroscopic speciation analyses. Soil pH was found to be the least variable property [coefficient of variation (CV) < 13%], whereas carbonate content was the most variable (CV > 130%). The Cu and B availability showed strong negative correlation with the sand content in all soils. Path coefficient results indicated that organic carbon had the highest positive direct effect on availability and supply of Cu and B in Grey soils. Extractable Zn was positively correlated with organic carbon content of Brown and Dark Brown soils. Overall, high sand content and low organic matter were identified as important soil properties contributing to the deficiency of Cu, Zn, and B. The major proportion of Cu, Zn, and B was found in the recalcitrant residual fraction (59%–88%), with the smallest proportions in labile soluble, exchangeable forms (2%–8%). The X-ray absorption near edge structure revealed that Cu and Zn associated with carbonate minerals were dominant forms of these micronutrients present in all soils. Chemisorption is likely a major process regulating the bioavailability of Cu and Zn in prairie 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 | 0.001 |
| Scholarly communication | 0.001 | 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 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".