Italian Ryegrass Management Effects on Nitrogen Supply to a Subsequent Potato Crop
Bibliographic record
Abstract
There is increasing use of Italian ryegrass (Lolium multiflorum Lam.) as a green manure in potato (Solanum tuberosum L.) rotations; however, effects of its management on soil N supply to the subsequent potato crop are unknown. Fertilizer N management and plow‐down date for a preceding Italian ryegrass crop, ‘Lemtal’, on soil N supply to a subsequent potato crop, ‘Russet Burbank’, was determined over 2 yr. Application of N at 150 to 188 kg N ha−1 to ryegrass increased dry matter yield and N uptake of aboveground forage and stubble (i.e., stubble, crown, and large root) tissue. Delaying plow‐down from early September to early November increased dry matter yield and N uptake of stubble tissue, but not aboveground forage. Apparent recovery of applied N in harvested forage and stubble tissue averaged 55 and 12%, respectively. High N application to the ryegrass increased soil N supply to the subsequent unfertilized potato crop as indicated by increased tuber yield, mean tuber weight, and plant (i.e., vines plus tubers) dry matter yield and N uptake. However, the increase in soil N supply (i.e., N uptake of unfertilized potato plants at vine desiccation) was small (<20 kg N ha−1). Apparent recovery of N applied to the ryegrass crop in unfertilized potato plants was low (10%). Delayed ryegrass plow‐down had no effect on soil N supply to the subsequent potato crop. Italian ryegrass green manure crop can be effective in increasing soil organic matter inputs but has limited short‐term effects on soil N supply for potato.
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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".