Amino Acid and Protein Changes during Cold Acclimation of Green‐Type Annual Bluegrass (<i>Poa annua</i> L.) Ecotypes
Bibliographic record
Abstract
Cold acclimation is associated with many metabolic changes that lead to increase freezing tolerance. This study was conducted to assess amino acid and protein changes occurring during cold acclimation of green‐type annual bluegrass ecotypes cold hardened under both environmentally controlled and simulated‐winter conditions in an unheated greenhouse. These biochemical changes were monitored in three ecotypes of contrasting freezing tolerance originating from Western Pennsylvania (OK), Coastal Maryland (CO), and central Québec (CR). Cold hardening induced major changes in amino acid levels in overwintering crowns of the three ecotypes and the highest contributions to total amino acid accumulation after acclimation at subfreezing temperatures came from proline, glutamine, and glutamic acid. Higher levels of amino acid and greater differences among ecotypes were observed after acclimation at subzero temperatures. Amino acid levels, including proline, were not related to the differential freezing tolerance among the three annual bluegrass ecotypes tested. Specific soluble polypeptides and thermostable proteins showed cold responsiveness and in some cases, their peak accumulation coincided with maximum freezing tolerance of annual bluegrass. In plants hardened to winter conditions in a unheated greenhouse, there was a distinct accumulation of polypeptides from fall until midwinter with a subsequent decrease in the spring.
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) | 0.000 | 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 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".