Interactions between reserve mobilization and regulation of nitrate uptake during regrowth of <i>Lolium perenne</i> L.: putative roles of amino acids and carbohydrates
Bibliographic record
Abstract
In most forage grass and legume species the recovery of leaf growth following severe defoliation depends on mobilization of carbon and nitrogen reserves from the remaining tissues. Unusually, Lolium perenne L. is able to compensate for low levels of available N storage compounds by rapid up-regulation of mineral N uptake. To investigate the physiological basis of this behaviour, perennial ryegrass plants were exposed to a 10 d period of optimal mineral N (high-N plants) or zero N (low-N plants) supply before defoliation. N deprivation decreased total N and amino acid concentrations in roots, and increased root water soluble carbohydrate concentrations. Compared with high-N plants (control), fructans and fructose concentrations in roots of low-N plants were 74% and 49% higher, respectively. Low-N plants had higher rates of nitrate uptake following defoliation, and lower amino acid concentrations in the roots (mainly as asparagine and glutamine); a causal role was suggested by the inhibition of nitrate uptake by external root supply of amino acids to low-N plants or by a stimulation of N uptake of high-N plants by sucrose supply to the roots. The results suggest that down-regulation of nitrate uptake following defoliation of plants with high levels of N reserves, may be effected through an increased cycling of amino acids within the plant and by a shortage of carbohydrates. Results are discussed in relation to the proteolytic activities and mobilization of C and N reserves to leaf meristem.
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 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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".