Winter Cereal Cover Crops for Spring Forage in Temperate Climates
Bibliographic record
Abstract
Core Ideas Barley is not a suitable cover or forage crop for southern Ontario due to winter‐kill. Flag leaf, boot, and heading of cereal rye are about 1 wk earlier than for wheat or triticale. Forage quality of winter cereals was high from flag leaf to boot stages. Nitrogen fertilization (50–67 kg N ha −1 ) optimized forage yield without affecting quality. In this study four winter cereals commonly used as cover crops were evaluated for forage yield potential and nutritional quality when harvested in early spring. Wheat ( Triticum aestivum L.), triticale (X Triticosecale Wittm.), cereal rye ( Secale cereale L.), and barley ( Hordeum vulgare L.) were evaluated via experimental plots and on‐farm trials in southern Ontario, Canada, between 2013 and 2015. Barley was the only species that failed to overwinter. The average forage yield of all other winter cereal species was 2.9 Mg ha −1 dry matter (DM) at boot stage with total digestible nutrient (TDN) values above 700 g kg −1 at flag leaf and boot stages of development. At the flag leaf and boot stages of development the fiber content of cereal rye was higher and nonfiber carbohydrates lower than wheat or triticale. However, crude protein (CP) and TDN were indistinguishable among species. Across species and experimental plot site‐years, a spring N application of 50 kg N ha −1 increased forage yield by 0.9 Mg ha −1 DM and CP by 26 g kg −1 , but all other quality parameters were unaffected. Additional N fertilization, on‐farm, increased DM yield, but economically optimum N rates remained low, at 42, 50, and 65 kg N ha −1 for cereal rye, triticale, and wheat, respectively. While wheat and triticale may be used as spring forage, the approximately 7d earlier flag leaf or boot stage of cereal rye makes it a better fit for rotations with corn ( Zea mays L.) and soybean [ Glycine max (L.) Merr].
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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) | 0.001 | 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 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".