Plant heat stress: Concepts directing future research
Bibliographic record
Abstract
Predicted increases in future global temperatures require us to better understand the dimensions of heat stress experienced by plants. Here we highlight four key areas for improving our approach towards understanding plant heat stress responses. First, although the term 'heat stress' is broadly used, that term encompasses heat shock, heat wave and warming experiments, which vary in the duration and magnitude of temperature increase imposed. A greater integration of results and tools across these approaches is needed to better understand how heat stress associated with global warming will affect plants. Secondly, there is a growing need to associate plant responses to tissue temperatures. We review how plant energy budgets determine tissue temperature and discuss the implications of using leaf versus air temperature for heat stress studies. Third, we need to better understand how heat stress affects reproduction, particularly understudied stages such as floral meristem initiation and development. Fourth, we emphasise the need to integrate heat stress recovery into breeding programs to complement recent progress in improving plant heat stress tolerance. Taken together, we provide insights into key research gaps in plant heat stress and provide suggestions on addressing these gaps to enhance heat stress resilience in plants.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".