Agronomic and economic evaluation of fall cover crops and the natural fall plant community in on-farm experiments in Manitoba
Bibliographic record
Abstract
Fall cover crops are grown to protect soil from erosion from the time of cash crop harvest to the following cash crop and to benefit soil health. The adoption of fall cover crops in Manitoba has increased in recent years due to increasing interest in soil health building practices. Major barriers to cover crop adoption in Manitoba include the limited amount of previous research and the short growing season which limits the fall window for cover crop growth, and thus may limit the potential benefits of cover crops. This study assessed fall cover crops in the initial years of adoption in six multiyear on-farm experiments across Manitoba with four replicates in each environment. Fall cover crops were included in the annual cash crop rotation and were compared to the natural fall plant community (NFPC) from 2019 until 2021. This research assessed the fall dry matter production of fall cover crops, the effect on subsequent cash crop yield, along with effects on soil nitrate, moisture, and health. Additionally, the short-term economic cost benefit analysis of fall cover crops was explored. Cover crops were included after 13 of the 17 cash crops with seeding dates ranging from August 10th to September 14th. The mean fall cover crop dry matter ranged from 99 to 2146 kg ha-1. The cover crop and NFPC produced equivalent amounts of fall dry matter in 7 of 11 environments. Fall cover crops significantly decreased the overall subsequent mean cash crop yield by 2% compared to the NFPC. Spring soil nitrate was significantly lower in the cover crop treatment in 3 of 5 environments relative to the NFPC treatment. After 2 or 3 cover crops were grown in each environment, the mean Saskatchewan Soil Health Assessment score was significantly greater in the cover crop treatment. Fall cover crops resulted in a mean economic loss of $163 ha-1. The high mean economic loss observed in this study suggests incentive payments will be necessary for fall cover crops to be economically feasible in 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".