Morphological and physiological responses of different wheat genotypes to chilling stress: a cue to explain yield loss
Bibliographic record
Abstract
BACKGROUND: The eco-physiological mechanism of wheat yield loss resulting from chilling stress is a fundamental scientific issue. However, previous studies have focused on hexaploid wheats, and few studies on the morphological and physiological plasticity of wheat plants. Six different wheat genotypes were tested under chilling stress to investigate the physio-morphological parameters as well as the loss of grain yield in growth chambers. RESULTS: Chilling stress resulted in significant loss in grain yield in all genotypes. Under chilling stress, diploid wheats generated zero harvest, and tetraploid genotypes also suffered from a pronounced loss in grain yield, compared with the control group. In contrast, hexaploid genotypes acquired relatively high maintenance rate of grain yield among three species. CONCLUSIONS: Diploid and tetraploid wheat genotypes maintained relatively large leaf area and high photosynthetic rates, but they were subjected to significant declines in vascular bundle number and productive tillers as a consequence of the inhibition by sink growth under chilling stress. The hexaploid wheats were found to have relatively low leaf area and photosynthetic rates. These genotypes also stored more soluble carbohydrates and exhibited stronger sink enhancement, ensuring the translocation and redistribution of assimilates. Our findings provided a new theoretical understanding of yield stabilization in the domestication process of wheat genotypes under chilling stress. © 2017 Her Majesty the Queen in Right of Canada. Journal of The Science of Food and Agriculture © 2017 Society of Chemical Industry.
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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 | 0.000 |
| 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".