THE EFFECT OF CHILLING TEMPERATURE ON GERMINATION AND EARLY GROWTH OF DOMESTIC AND CANADIAN SOYBEAN (Glycine max (L.) Merr.) CULTIVARS
Bibliographic record
Abstract
Low positive temperature, has an inhibiting effect on growth, development and other physiological processes of cold-sensitive plants which include soybean. An experiment in Petri dishes investigated the effect of temperature: 28/28°C (control), 10/28°C, 28/10°C, and 10/10°C (imbibition/germination), on germination of seeds of 8 soybean cultivars. Another experiment, carried out using pot cultures, investigated the response of 2-week soybean plants of the same cultivars to a 6-day chilling period. The following temperatures were used: 25/20°C (control), 25/0°C, 10/0°C (day/night). Both experiments tested the response of 6 domestic soybean cultivars (‘Aldana’, ‘Jutro’, ‘Progres’, ‘Mazowia’, ‘Nawiko’, and ‘Augusta’) and 2 Canadian cultivars (‘OAC Vision’, ‘Dorothea’) to chilling. The obtained results showed that a temperature of 10°C used during germination (28/10°C), and even to a larger extent during imbibition and germination (10/10°C), clearly reduced the speed of germination, percentage of germinated seeds, and radicle length relative to the control, but it increased catalase activity in sprouts. A chilling temperature of 25/0°C and 10/0°C (day/night) significantly increased leaf electrolyte leakage, free proline content and catalase activity relative to the control, but it decreased the photosynthetic rate and total plant leaf area. Seeds and seedlings of cvs. ‘Jutro’ and ‘Nawiko’ were generally the least sensitive to chilling, while ‘Aldana’ and ‘Dorothea’ were the most sensitive.
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 | 0.001 |
| 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".