Evaluation of manure-derived struvite as a phosphorus source for canola
Bibliographic record
Abstract
Ackerman, J. N., Zvomuya, F., Cicek, N. and Flaten, D. 2013. Evaluation of manure-derived struvite as a phosphorus source for canola. Can. J. Plant Sci. 93: 419–424. There is growing interest in the treatment of swine manure to mitigate water quality issues related to phosphorus (P) from livestock operations. Precipitation of P as struvite (MgNH4PO4·6H2O) is a potential strategy to achieve this. The overall objective of this growth room study was to evaluate the effect of manure-derived struvite (MDS) on canola growth and P recovery efficiency. Pure struvite (PS), monoammonium phosphate (MAP), and polymer-coated monoammonium phosphate (PCMAP) were applied to canola plants in plastic pots containing 2 kg of a sandy loam soil. Biomass yields for MDS and PS were similar at all P rates (mean = 7.6 g pot−1) and significantly smaller than those for MAP and PCMAP (mean = 9.3 g pot−1). Differences in P uptake among P sources were detected at the highest P rate where P uptake was significantly greater for MAP and PCMAP (mean = 22.7 mg P pot−1) than for the struvite forms (mean = 16.4 mg P pot−1). Our results show that although P uptake was similar for the struvites and commercial fertilizers at P2O5 rates of 38 mg pot−1 or lower, biomass yield per unit of P taken up was smaller for the struvites. This may be due to lower initial solubility of the struvites in the alkaline (pH 7.7) soil used in this experiment, which gave an early stage growth advantage to canola fertilized with MAP and PCMAP. These results suggest that it may be necessary to supplement struvite with soluble P fertilizers, such as MAP, if applied on soils such as that tested in this study.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".