The Effect of Temperature Stress on Seed Germination Physiological Indices in Asparagus Bean(Vigna unguiculata L.ssp.sesquipdalis Verdc.)
Bibliographic record
Abstract
Three yardlong bean cultivars were used as materials to carry out seeds germination experiments under 15 ℃(low temperature),25 ℃(control) and 35 ℃(high temperature),according to completely randomized design with 3 duplicates,respectively.To sample the radicles and cotyledons respectively while the radicles was 1 cm long,the total soluble protein(TSP),the malondialdehyde(MDA) content,the activites of superoxide dismutase(SOD),the catalase(CAT) and the peroxide enzyme(POD) were determined.The results indicated that MDA of both the radicles and cotyledons increased extremely significantly under the low and the high temperature treatments compared with the control,whereas the SOD activities decreased.TSP decreased in radicles either under low or under high temperature.As for cotyledons,TSP increased under low temperature,but decreased under high temperature.In cotyledons,the POD activities dropped down remarkably under the low temperature but increased under the high temperature,but the CAT activities increased significantly or extremely significantly under low temperature stress,but decreased under high temperature stress,whereas in radicles the changing tendencies were reverse.Therefore,most of indexes were influenced by temperature stresses,but the tendencies of influence by low and high temperature were not the same.
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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 | 0.000 | 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 | 0.001 |
| 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".