Combining reduced tillage and green manures minimized N2O emissions from organic cropping systems in a cool humid climate
Bibliographic record
Abstract
Developing and implementing improved management practices are necessary to enhance the sustainability of organic cropping systems. This study examined the effects of various organic cropping systems on soil greenhouse gas (GHG) emissions and crop yields in Québec, Canada. Organic cropping systems combining different: (i) crop sequences (barley [Hordeum vulgare L.]-grain corn [Zea mays L.], soybean [Glycine max (L.) Merr.]-spring wheat [Triticum aestivum L.], and grain corn-soybean), (ii) nitrogen (N) sources (poultry manure [PM] and/or a fall-seeded green manure [GM] or no applied N), and (iii) primary tillage intensities (moldboard plough [MP] or chisel plough [CP]) were compared to a perennial forage (PF) and a bare fallow (BF) control. During the 2019 and 2020 snow-free seasons, nitrous oxide (N2O) and methane (CH4) emissions, soil water content, soil temperature, and mineral N concentrations were monitored periodically on a sandy loam soil. The lowest cumulative N2O emissions were found in CP-GM (0.52 ± 0.11 kg N ha-1 in 2019 and 0.47 ± 0.06 kg N ha-1 in 2020), whereas the highest N2O emissions were found in MP-PM in 2019 (3.55 ± 0.72 kg N ha-1) and BF in 2020 (1.44 ± 0.20 kg N ha-1). For the barley-grain corn sequence, the CP-GM treatment generated N2O emissions that were 40–70 % lower and yields that were 33–51 % lower than the MP-PMGM and CP-PMGM systems, which showed equivalent N2O emissions and yields. Yield-scaled N2O emissions were equivalent for all cropping systems. Peak N2O daily fluxes in the PF occurred shortly after cutting in 2020. During both years, CH4 emissions varied from − 0.65 to + 0.18 kg C ha-1 with no detectable differences among cropping systems. The CP-GM cropping system minimized area-scaled N2O emissions without increasing yield-scaled emissions. However, this was a two-year study on a site that was recently converted from conventional agriculture, so a long-term assessment is still necessary to determine whether the benefits associated with these cropping systems change over time.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".