Soil responses to inclusion of corn, soybean, and cover crops under rainfed conditions in the northern Great Plains
Bibliographic record
Abstract
Crop rotations in the northern Great Plains of North America increasingly include corn ( Zea mays L.) and soybean ( Glycine max (L.) Merr.). Use of cover crops, while less extensive, is also increasing given their purported agronomic and environmental benefits. To date, soil responses to the inclusion of corn, soybean, and cover crops in rainfed cropping systems have not been well documented in the region. Therefore, soil properties were evaluated 6 years after establishment of three crop rotations (spring wheat ( Triticum aestivum L.)–soybean (SW–S), spring wheat–corn–soybean (SW–C–S), and spring wheat–corn–cover crop (SW–C–cc)) each split by no and minimum tillage on a Dark Brown Chernozem near Mandan, ND, USA. Soil responses to treatments were subtle and exclusive to the 0–7.6 cm depth. Soil pH was lower in SW–S than SW–C–cc (5.28 vs. 5.48; P = 0.05), SO4-S was greater under SW–C–cc than SW–C–S (13.4 vs. 11.6 g S kg−1; P = 0.03), exchangeable K was greater under SW–C–S and SW–C–cc than SW–S (0.83 cmol kg−1 vs. 0.52 cmol kg−1; P = 0.05), and water-stable aggregates were greater in SW–S than SW–C–S (26% vs. 19%; P = 0.08). Soil organic carbon (SOC) and total N did not differ among crop rotations or between tillage treatments, while particulate organic matter N was greater under no tillage compared to minimum tillage ( P = 0.08). Between 2012 and 2018, soil pH decreased and SOC increased under SW–C–S. Frequent monitoring of near-surface soil conditions in rotations with soybean every other year is recommended. Furthermore, innovative management practices are needed to enhance soil C and N fractions in rotations with full-season cover crops.
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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 | 0.000 |
| 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) | 0.001 | 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".