Engineering nitrogen use efficient crop plants: the current status
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the last 40 years the amount of synthetic nitrogen (N) applied to crops has risen drastically, resulting in significant increases in yield but with considerable impacts on the environment. A requirement for crops that require decreased N fertilizer levels has been recognized in the call for a 'Second Green Revolution' and research in the field of nitrogen use efficiency (NUE) has continued to grow. This has prompted a search to identify genes that improve the NUE of crop plants, with candidate NUE genes existing in pathways relating to N uptake, assimilation, amino acid biosynthesis, C/N storage and metabolism, signalling and regulation of N metabolism and translocation, remobilization and senescence. Herein is a review of the approaches taken to determine possible NUE candidate genes, an overview of experimental study of these genes as effectors of NUE in both cereal and non-cereal plants and the processes of commercialization of enhanced NUE crop plants. Patents issued regarding increased NUE in plants as well as gene pyramiding studies are also discussed as well as future directions of NUE research.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it