Effect of water availability and genetic diversity on flowering phenology, synchrony, and reproductive investment in maize.
Bibliographic record
Abstract
Crop yield of monoecious species like maize (Zea mays) relies on simultaneous flowering of male and female inflorescences to ensure pollination. Yet productivity may be reduced if environmental conditions reduce floral synchrony or if plants within a field do not overlap sufficiently in flowering periods. We experimentally manipulated water availability and measured its effect on flowering, including the anthesis-silking interval (ASI) and crop yield components in open-pollinated (OP) and hybrid corn cultivars. Although watering treatments did not affect traits, we did detected cultivar-specific phenological and yield responses. Hybrid plants were earlier to silk than OP plants, which tasseled for longer, had a longer ASI, and lower yield components. The less diverse hybrids also expressed less variation in ASI. We suspect other methods for reducing moisture in the field, including earlier moisture removal, might have better elicited a biological response in maize. Nevertheless, because shorter ASI is genetically correlated with increased drought tolerance, we predict this hybrid may be more resilient than the OP under more extreme drought scenarios. Consideration for how genetic diversity found in OP varieties and crop landraces may respond to variation in moisture availability apparent with climate change may be warranted.
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 | 0.000 | 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 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".