Phenotypic plasticity of bread wheat contributes to yield reliability under heat and drought stress
Bibliographic record
Abstract
Yield reliability under diverse environments is important to address climate stress consequences in wheat production systems. Breeding for reliability under a changing climate remains a challenge in wheat. We assessed the performance of 18 hexaploid (Triticum aestivum L.) genotypes in three field environments at a location within the semi-arid Canadian Prairies over four years with a primary aim to establish knowledge of the phenotypic plasticity and yield reliability in the parental lines as it relates to heat and drought stress tolerance. We collected data on various physiological traits along with some agronomic and morphological attributes, uncovering significant variation across early seeded rainfed, early seeded irrigated, and late seeded rainfed (hot and dry) environments. Eight high yielding hexaploid genotypes '01S0263-28', 'AC Foremost', AC Karma', 'Cutler', 'MN03358-4', 'Reeder', 'Stettler', and 'Superb' showed higher grain Δ13C. Six of these genotypes '01S0263-28', 'AC Foremost', 'MN03358-4', 'Reeder', 'Stettler', and 'Superb' showed higher water use efficiency under irrigated as well as hot and dry environment compared to the low yielding lines 'Red Fife','8021-V2' and 'BW278'. Only four genotypes '01S0263-28', 'MN03358-4', 'Reeder', and 'Stettler' were found with higher yield reliability index. The grain yield relationship with leaf rolling, glaucousness, and canopy temperature was found to be weak. The flag leaf stomatal numbers increased with water stress in high yielding lines which were otherwise low in stomatal numbers. Contrastingly, water stress significantly reduced the stomatal numbers in low yielding lines that were otherwise high in stomatal numbers. The results highlight the stomatal adaptability of different genotypes in response to drought. Taken together, these results provide baseline information that the genotypes with high grain Δ13C and WUE, and low stomata numbers are more yield reliable under variable field environments, and this information can guide the breeding of climate-resilient germplasm that expresses consistent and reliable grain yield production in the semi-arid Prairies.
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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) | 0.000 | 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".