Influence of compost source on corn grain yields, nitrous oxide and carbon dioxide emissions in southwestern Ontario
Bibliographic record
Abstract
Drury, C. F., Reynolds, W. D., Yang, X. M., Tan, C. S., Guo, X., McKenney, D. J., Fleming, R. and Denholme, K. 2014. Influence of compost source on corn grain yields, nitrous oxide and carbon dioxide emissions in southwestern Ontario. Can. J. Soil Sci. 94: 347-355. The impacts of compost type on corn grain yields over 10 yr and N2O and CO2 emissions in the first 3 yr after compost application were evaluated on a Brookston clay loam soil in Woodslee, ON. The treatments included yard waste compost (YWC), kitchen food waste compost (FWC), and pig manure compost (PMC), which were applied once in the fall of 1998 to field plots at a rate of 75 Mg ha-1 (dry weight basis) and no further applications occurred thereafter as well as a fertilized control treatment. Large application rates were examined to see if the various compost sources could have a lasting effect on soil C storage, N2O and CO2 emissions and corn yields. Compost application significantly increased corn grain yields by 12.9 to 19.4% over 3 yr. However, after 10 yr, FWC was the only compost source which significantly increased yields by 11.3% compared with the fertilized control. Emissions of N2O and CO2 varied with compost type, soil water content and time. Greater N2O emissions occurred in 1999 from PMC (5.4 kg N ha-1) than YWC (2.7 kg N ha-1) and FWC (1.3 kg N ha-1); however, the N2O emissions from the PMC were less than from YWC and FWC in 2001. The 3-yr average N2O emissions were significantly greater with PMC (2.7 kg N ha-1) and YWC (2.5 kg N ha-1) compared with the control (1.5 kg N ha-1). Hence, the timing of N2O emissions varied by compost type, but the overall losses were similar as the higher N2O losses in the first year with PMC were offset by the reduced losses with PMC in the third year. Significantly more CO2 was produced from the FWC in 2000 and from PMC in 2001 than the control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".