A novel technique utilizing enriched 15N2 to trace nitrogen transfer in grass and legume mixtures
Bibliographic record
Abstract
Legumes are a potentially important N source in pasture systems, but quantifying the transfer of biologically fixed N from the legume to the grass component is difficult. A greenhouse H-pot system was developed to directly estimate belowground N transfer from biological N 2 fixation (BNF) using 15 N 2 . The system was tested with ‘Prine’ annual ryegrass ( Lolium multiflorum L.) and ‘Dixie’ crimson clover ( Trifolium incarnatum L.). Legume and grass root systems growing in either individual or H pots were exposed to 15 N 2 . Control H pots were separated by mesh to prevent contact between roots from each side of the pot. To reduce enriched gas volume demand and avoid cross-contamination in the greenhouse, the gas was supplied through underground tubes in the root zone. Ryegrass and clover exhibited an enrichment of 15 N 2 when their respective root systems were supplied with 15 N 2 . Additionally, ryegrass also showed enrichment when clover roots received the gas, provided there was direct contact between the root systems on both sides of the H pot; however, this enrichment did not occur when such contact was prevented. Plants cultivated in monoculture without the application of 15 N 2 did not present enrichment. The H-pot facilitates the evaluation of belowground transmission, an essential mechanism for N transfer. The technique of gradually supplying 15 N 2 directly to the root system may serve as a valuable labeling method for tracking nitrogen transfer. The absence of enrichment when plants were not directly supplied indicates negligible atmospheric enrichment. However, the enrichment observed in ryegrass when supplied with the gas suggests BNF through alternative pathways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".