Potato and soil 15N recoveries from different labelled forage root and shoot
Bibliographic record
Abstract
Abstract An improved understanding of the contribution of a preceding forage crop to a subsequent potato crop can improve nitrogen (N) utilization in potato production. This study used two rotation experiments to estimate the N contribution from labelled shoot and root of red clover (RC, Trifolium pratense), timothy (T, Phleum pratense) and a red clover/timothy mixture (M) to a subsequent potato crop using microplots in the field. Forage crops were grown with 14NH414NO3 and 15NH415NO3 (98 atom %). The residue exchange technique was used to compare residue treatments of (i) whole plant labelled; (ii) labelled shoot only; and (iii) labelled root only in Experiment 1, and residue treatments of (i) whole plant labelled; (ii) labelled shoot/unlabelled root; and (iii) labelled root/unlabelled shoot in Experiment 2. Averaged across forage treatments, recoverable root biomass represented 64 and 37% of total forage biomass, and the total 15N recovery from labelled roots was 52 and 62% of the total 15N recovery from shoots, in Experiments 1 and 2, respectively. Therefore, forage roots represented a substantial source of N for the subsequent crop. However, less than 5% of the 15N from crop residues was recovered in the potato vines plus tubers, and most of the 15N was recovered in the soil, regardless of the forage or residue treatments. Potato tuber and vine dry matter was greater for the RC than the T treatment for all residue treatments, a finding attributed to greater potato N accumulation for the RC treatment. It is therefore important to consider the contribution of forage roots when studying N cycling in potato systems. Potato N requirements were satisfied more by soil-derived N rather than from fall incorporated forage residues.
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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".