EFFECT OF SOIL AMENDMENT WITH THIN STILLAGE AND GLYCEROL ON PLANT GROWTH AND SOIL PROPERTIES
Bibliographic record
Abstract
Controlled environment experiments were set up in 2007 and 2008 to evaluate the potential of using by-products of the biofuel industry as soil amendments to improve fertility and plant growth in Saskatchewan soils. Trials were run with thin stillage (a by-product of ethanol production) and glycerol (by-product of biodiesel production). Canola (B. napus L.) and wheat (T. aestivum) were grown as the test crop in amended pots. Plant yield, composition, and soil properties were measured after five weeks. The stillage was found to be an effective soil amendment for increasing plant biomass yield. Per unit of nitrogen (N) added, canola yields were less than that of urea when nitrogen was the only limitation, due to only a portion of the nitrogen in the thin stillage becoming available over the five week period. However, when nutrients other than nitrogen were limiting, canola dry matter yields with thin stillage amendment approached or exceeded that of urea, due to the ability of the amendments to supply other nutrients such as phosphorus in addition to nitrogen. Glycerol, an amendment that only contains carbon, hydrogen and oxygen, was effective in increasing soil organic carbon content, but required supplemental fertilizer to account for nutrient tie-up by microorganisms during decomposition in the soil. The amendments did not have any biologically significant effects on other soil chemical parameters measured, including soluble metals, pH or salinity.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".