Nitrous oxide emissions from variable rate application of nitrogen fertilizer to Panicum virgatum L. in Québec, Canada.
Bibliographic record
Abstract
Nitrogen (N) fertilizer is essential to maintain agricultural yields but is susceptible to reactions that produce nitrous oxide (N2O), which acts as a greenhouse gas and contributes to stratospheric ozone depletion. It is difficult to predict where these reactions will produce ‘hot spots’ of high N2O fluxes in a field, as well as the ‘hot moments’ when peak N2O fluxes occur. The objective of this study is to relate the N2O fluxes in a Panicum virgatum L. (switchgrass) field to N fertilizer application rates of 0, 50, 100, and 150 kg N ha-1 while considering the spatial-temporal heterogeneity of the field. In summer 2017, soil samples were collected at 128 locations in an 8.87 ha switchgrass field in the Cookshire-Eaton region (45°20'N, 71°46'W) of Québec, Canada. The sandy loam soil was analysed for standard soil test parameters: macro- and micro-nutrient content, pH and texture. In addition, proximal soil sensing was done to characterize the elevation, electrical conductivity and surface spectral reflectance. This data was used to generate a spatial soil map of the field with R 3.4.1 statistical software and ArcGIS, which revealed three distinct management zones in the field. In spring 2018, four N fertilizer rates were applied to blocks (15 m wide x 100 m long), which created four blocks with variable N fertilizer rates in the high-yielding switchgrass zone and four blocks with variable N fertilizer rates in the low-yielding switchgrass zone. Non-flow-through non-steady-state chambers were installed (n=3 per block) for manual gas sampling and N2O fluxes were calculated during a 1 h period every 7-10 d during the growing season. The experiment was repeated in spring 2019 in the same management zones but in newly-selected blocks that had uniform fertilization in the 2018 growing season. Four N fertilizer rates were applied at random to 4 blocks in the high-yielding zone, plus 4 blocks in the low-yielding zone, and gas sampling chambers (n=3) were placed in new locations in each block. The “hot moments” of N2O flux occurred in the first 30 d after N fertilizer application. Although N2O fluxes differed in the management zones in 2018, there were no distinctive “hot spots” in the switchgrass field in the 2019 growing season. However, the cumulative N2O emission in each growing season tended to increase with greater N fertilizer rates, suggesting that applying more N fertilizer increased the risk of gaseous N loss, probably through denitrification. I conclude that precision agriculture techniques based on geospatial characterization of agricultural fields may help to calibrate site-specific N fertilizer inputs and meet agroenvironmental goals by improving crop production while reducing N2O emissions
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".