Potential of short‐duration millets as a post‐winter wheat crop in Ontario, Canada
Bibliographic record
Abstract
Abstract In northern latitudes, the diversity of the maize ( Zea mays L.)–soybean ( Glycine max L.) cropping system can be increased by including winter wheat as a rotation crop, providing long‐term benefits including improved nutrient availability, nutrient‐use efficiency, soil structure, and moisture holding. However, in Ontario, Canada, few farmers have adopted winter wheat ( Triticum aestivum L.) due to low profitability. After the wheat harvest, there is a 3‐month window with warm days and moist soil, sufficient to grow a short‐duration crop. Some millet varieties are short duration. Millets are increasingly valued economically as “ancient grains” for humans, as a nutritious forage, and as effective cover crops due to their fibrous roots and dense foliage. Though millets offer similar long‐term benefits to wheat in a rotation, they cannot economically compete with maize or soybean as a summer season crop. We hypothesized that the economic constraints of winter wheat and millets could be overcome by double cropping, specifically by adding a low‐input, short‐duration millet after winter wheat is harvested. The objective of this study was to evaluate the potential of millets as a post‐winter wheat crop in Ontario. Three years of field trials (2020–2022) were conducted in Elora and Essex, Ontario, starting with 81 accessions of five millet crops. Selected accessions of proso millet ( Panicum miliaceum L.) produced up to 0.5 t/ha grain yield, whereas foxtail millet [ Setaria italica (L.) P. Beav] and barnyard millet ( Echinochloa spp.) at Elora, and fonio ( Digitaria sp.) in Essex produced up to 0.9–1.6 t/ha dry shoot yield. However, planting date, initial soil moisture, weed management, and fall frost were observed to be critical for millet success.
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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 | 0.000 | 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) | 0.003 | 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".