Grain yield and N benefits to sequential wheat and barley crops from single-year alfalfa, berseem and red clover, chickling vetch and lentil
Bibliographic record
Abstract
Single-year hay alfalfas (Medicago sativa L.), berseem (Trifolium alexandrinum L.) and red clovers (Trifolium pratense L.), chickling vetch (Lathyrus sativus L.) and lentil (Lens culinaris Medik.) were evaluated for rotational yield and N benefits to the following first-year wheat (Triticum aestivum L.) and second-year barley (Hordeum vulgare L.) crops. Field experiments were initiated in 1997 and 1998 on a Riverdale silty clay soil at Winnipeg, Manitoba. Yield and N content of the following wheat crop were increased following legumes compared to wheat following a canola control. Wheat yield and N content averaged 2955 kg ha –1 and 76.1 kg ha –1 , respectively, following the chickling vetch and lentil, 2456 kg ha –1 and 56.4 kg ha –1 following single-year hay legumes, compared with 1706 kg ha –1 and 37.9 kg ha –1 following canola. Non-dormant alfalfas (dormancy rating of eight or greater) contributed to larger grain yields than the dormant alfalfas only in the first year of each experiment. The chickling vetch and lentil provided similar or higher subsequent crop yields and N content for 2 yr compared to a canola control or fallow treatment. This study shows that some increase in yield can be achieved by using a single-year alfalfa hay crop instead of fallow; however, exclusive green manuring of chickling vetch and lentil crops can produce the most increase in yield and N uptake in subsequent crops. Key words: Alfalfa (single-year), legumes (annual), green manure, nitrogen, cropping system
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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) | 0.001 | 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".