Ovule and seed development of crop plants in response to climate change
Bibliographic record
Abstract
The ovule is a plant structure that upon fertilization, transforms into a seed. Successful fertilization is required for optimum crop productivity and is strongly affected by environmental conditions including temperature and precipitation. Climate change refers to sustained changes in global or regional climate patterns over an extended period, typically decades to millions of years. These shifts can result from natural processes like volcanic eruptions and solar radiation fluctuations, but in recent times, human activities—especially the burning of fossil fuels, deforestation, and industrial emissions—have accelerated the pace and scale of climate change. Human-induced climate change impacts the agricultural sector mainly through global warming and altering weather patterns, both of which create conditions that challenge agricultural production and food security. With food demand projected to sharply increase by 2050, urgent action is needed to prevent the worst impacts of climate change on food security and allow time for agricultural production systems to adapt and become more resilient. Gaining insights into the female reproductive part of the flower and seed development under extreme environmental conditions is important to oversee plant evolution, agricultural productivity, and food security in the face of climate change. This review summarizes the current knowledge on plant reproductive development and the effects of temperature and water stress, soil salinity, elevated carbon dioxide, and ozone pollution on the female reproductive structure and development across grain legumes, cereal, oilseed, and horticultural crops. It identifies gaps in existing studies for potential future research and suggests suitable mitigation strategies for sustaining crop productivity in a changing climate.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".