Temporal Waterlogging and Physiological Performance of Wheat (Triticum aestivum L.) Seeds
Bibliographic record
Abstract
The aim of this work was to evaluate the physiological performance and some attributes of wheat seeds originated from plants submitted to soil flooding at different stages of development. The treatments consisted of periods of soil flooding, absence of flooding, two floods and three floods of the soil. Each flood lasted for three days. For the evaluation of the physiological quality, the seeds were submitted to the tests of germination and first germination count, germination speed index, shoot and primary root length, shoot and primary root dry matter mass, harvest index, thousand seed mass, electrical conductivity and isoenzymatic analysis. The increase of the soil flooding period did not affect germination, while the germination speed andindex, the harvest index and the thousand seed mass were lower in plants under the higher periods of soil flooding. The expression and intensity of bands of acid phosphatase and peroxidase isoenzymes were differently altered by periods of flooding. Thus, soil flooding negatively influences the physiological performance, the thousand seed mass and the harvest index when the plants are submitted to flooding of the soil.
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) | 0.001 | 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".