Characterization of two Winter wheat varieties' responses to freezing in a frigid region of China
Bibliographic record
Abstract
Cold stress is one of the main abiotic stresses faced by winter wheat, which results in significant yield loss, especially in the harsh winter of the Heilongjiang province. Glycine betaine (GB), an important osmolyte in higher plants, helps in the stabilization of the plasma membrane and its protection from cold stress. In the present study, two winter wheat varieties that differ in cold resistance, Dongnongdongmai1 (DM1) and Jimai22 (J22), were planted under natural conditions and used for analyzing relative electrical conductivity, malondialdehyde (MDA) content, betaine aldehyde dehydrogenase (BADH) activity, expression of BADH, and the content of GB. The cold-resistant variety, DM1, showed a greater increase in BADH activity and GB content and decrease in MDA content than J22 under freezing conditions. GB was observed to have an obvious role in inhibiting the MDA content. This was reflected by the expression of BADH and enhanced tolerance to cold stress upon GB accumulation, which helped membrane stabilization. The results of the present study confirmed the role of GB in conferring cold resistance in the DM1 winter cultivar and could benefit other studies aimed at improving the tolerance of other wheat cultivars and other crops.
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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 | 0.001 | 0.001 |
| 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".