Seedling Growth and Recovery in Response to Waterlogging of Wheat Cultivars Grown in the Yangtze River Basin of China from Three Different Decades
Bibliographic record
Abstract
Waterlogging is a major constraint on wheat (Triticum aestivum L.) production, especially in the Yangtze River Basin of China (YR). A container experiment was designed to investigate wheat-seedling growth and short-term recoveryin response to waterlogging. Cultivars commonly grown in theYR from three different decades, namely, Yangmai 1 (1970s), Yangmai 158 (1990s), and Yangfumai 4 (2010s), were selected. Seedling waterlogging significantly postponed leaf development, as well as decreased the number of tillers and adventitious roots per plant, seedling height, leaf area, specific leaf dry weight, shoot dry weight, root dry weight, and root/shoot ratio. After a 20-day recovery phase, the leaf stage, seedling height, and root/shoot ratio recovered to the control level, whereas the adverse effects of waterlogging on the number of tillers per plant, leaf area, and shoot dry weight intensified. Significant differences were found in seedling growth among the three wheat cultivars. Yangfumai 4 showed the highest number of adventitious rootsper plant and the highest specific leaf dry weightbut the lowest seedling height, leaf area, and dry weights of shoots and roots. However, Yangfumai 4 showed the lowest percentage decrease in all growth parameters after both waterlogging and recovery. These results suggested thatimprovement inadventitious root numberper plant and specific leaf dry weight may be indicators ofresistance to waterlogging in wheat.
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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) | 0.000 | 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".