Annual Cereal Cover Crops Following Winter Wheat Produce High Quality Fall Forage
Bibliographic record
Abstract
Core Ideas Forage quality of fall‐grown annual cereal cover crops was high in southern Ontario, Canada. Oat produced more forage than barley when disease pressure was high. Oat–pea forage had higher crude protein with similar yield and nutrient digestibility versus oat. Fertilization (50–67 kg N ha−1) increased yield without affecting quality. Oat seeded at 80 and 120 kg ha−1 had similar forage yield and quality. Fall‐grown cereal cover crops can serve dual purpose as forage in southwestern Ontario, Canada. Four experimental field trials and four on‐farm validation trials were conducted to evaluate yield and quality of late‐summer sown and fall harvested barley (Hordeum vulgare L.), oat (Avena sativa L.), and an oat–pea (Pisum sativum L.) mixture. Barley, oat, and the oat–pea mixture had similar yields where 50 to 67 kg N ha−1 was applied and when barley yields were not limited by Septoria (Septoria passerinii Sacc) leaf spot. Forage yields were increased at three of four experimental field trials by 0.3–0.7 Mg ha−1) when harvest was delayed from late October to mid‐November. Later harvest dates increased nonfiber carbohydrates (NFC) (51–99 g kg−1) and decreased neutral detergent fiber (NDF) (16–54 g kg−1) and crude protein (CP) (19–47 g kg−1) with minimal effect on total digestible nutrients (TDN). Mid‐fall harvested oat forage with 50 to 67 kg N ha−1 produced an average yield of 2.9 Mg ha−1. Oat forage quality was consistently high. Individual trial oat averages for NDF did not exceed 509 g kg−1, in‐vitro neutral detergent fiber digestibility (NDFD) was not less than 690 g kg−1, increased NFC was not less than 285 g kg−1 and TDN always exceeded 720 g kg−1. Addition of peas, increased CP by 28 g kg−1, with minimal impact on other nutritional quality characteristics. Oat or oat–pea mixtures, seeded as cover crops following winter cereal harvest are capable of producing satisfactory forage yields with excellent nutritional quality.
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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) | 0.002 | 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".