The Impact of Cover Cropping on Soil Nitrogen Availability, Crop Nitrogen Use, and Nitrous Oxide Emissions in a Prairie Potato—Grain Crop Rotation
Bibliographic record
Abstract
In prairie regions of Canada, growers are beginning to adopt cover cropping. Yet several questions remain unanswered on the viability, impact, and benefits associated with cover cropping in a short growing season region like the prairies. To address this gap, a four-year fully phased crop rotation trial consisting of wheat (Triticum aestivum)- canola (Brassica napus)- potato (Solanum tuberosum)- pea (Pisum sativum) grown with vs. without shoulder-season cover crops, red clover (Trifolium pratense), berseem clover/oat (Trifolium alexandrinum/Avena sativa), rye (Secale cereale), and mustard/tillage radish (Brassica juncea/Raphanus sativus) respectively, was set up in Saskatoon to determine cover crop influence on N availability, crop nitrogen use efficiency (NUE), and N2O emissions. A short rotation (wheat-canola) and a perennial alfalfa were included as treatment checks. Results showed that cover crops are viable, but success depends on species, management, and weather conditions. It was evident that cover crops influenced N cycling during the non-growing season (in the fall or spring). Cover crops had potential to reduce post-season N losses through plant N uptake and subsequent N release through mineralization. However, there was no cover crop effect on main crop yields and NUEs. When cover crop impact on N2O emissions were evaluated, several trends pointed towards higher N2O emissions with vs. without cover crops especially if a legume appeared in the phase studied. However, there were exceptions where cover crops significantly increased emissions. Emission events were observed post-fertilization and at spring thaw for all crop rotations. The growing season, post-harvest and spring thaw contributed 51, 7 and 42%, respectively to the cumulative annual emissions. Overall, it can be concluded that N dynamics were not markedly influenced by cover crops in the crop rotations studied. Longer-term studies are recommended to detect any possible impacts on N cycling, as cover crop effects may gradually build overtime. Future research should investigate methods of supporting rapid cover crop establishment and biomass accumulation (i.e., cold hardy varieties, early-seeding or under-seeding techniques). To sufficiently benefit main crop NUEs and reduce the risk of N losses, cover crop management may need to be bundled with other practices such as N fertilizer rate adjustments.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".