Soybean production and soil health response to crop rotation sequences in Manitoba
Bibliographic record
Abstract
This study was conducted to evaluate the effect of growing soybean continuously vs in rotation with canola, corn, and wheat on soybean performance, biological nitrogen fixation, and biological soil health in the soils of Manitoba. The experiment was established in 2014 at two locations (Carman and Kelburn) in Manitoba. Crop sequence treatments were continuous soybean (S-S-S-S), canola-soybean-canola-soybean (Ca-S-Ca-S), corn-soybean-corn-soybean (C-S-C-S), and wheat-canola-corn-soybean (W-Ca-C-S). All four treatments had a common soybean test crop in the 4th year (2017) of the study. Soybean production and biological N fixation (BNF) parameters were observed in the soybean test crop in 2017. Soil health analysis were conducted for the surface soils (0-8 cm depth) collected at multiple sampling stages in the 4th and 6th (2019) years of the experiment. After four years, the preceding crop in the sequence had no effect on soybean seed yield. Crop sequence treatments were significant for soybean seed quality, dry matter yield, above ground N uptake, and biological nitrogen fixation. However, the continuous soybean sequence was not consistently different form sequences where soybean was grown in rotation with canola, corn, and wheat. Penalties of continuous cropping when first introducing soybean into the rotations were minimal. Future research is needed to identify long-term impacts of continuous soybean in the soils of Manitoba. There were inconsistent trends in the activities of β-glucosidase, β-glucosaminidase, and acid phosphatase among sampling stages, crop sequence treatments, locations, and years. However, enzyme activity was frequently greater in the C-S-C-S sequence compared to the S-S-S-S sequence across sampling stages in both years. Active C was also greater in the C-S-C-S in relative to the S-S-S-S sequence. Greater levels of soil enzymes were observed at the beginning and end of the growing season. Bacterial families formed separate clusters at before planting (BP) and full maturity (R8) stages that were distinct from mid-growing season samplings. Therefore, conducting soil health analysis at either of those two sampling stages would be helpful to identify the differences in crop management practices such as crop rotations in the soils of Manitoba.
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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 | 0.001 | 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".