Plasticity in Root Length and Volume Through the Alternate Wetting and Drying Water Management in Rice
Bibliographic record
Abstract
Saving water via rational management in paddy rice require efforts to minimize risks to food security, whether consider that its adoption by farmers generally lead to lower grain productivity. Recently, studies by meta-analysis approaches highlight that when soil water potential was higher than -20 kPa, grain yields are not significantly decreased. In this context, new efforts should be done by rice breeders aiming to improve the plant performance when submitted to a more severe alternate wetting and drying (AWD) aiming to face the increasingly extreme climatic events in the next decades. Thus, in this first-tier of the study, our main objective was to evaluate the responses of a genotypes set (cultivars and elite line) for some root traits plasticity and its potential to change gas exchange attributes and grain yield when plants are subjected to severe AWD irrigation management, even when soil water potential beyond this threshold (when soils dried beyond -20 kPa, even reaching -40 kPa). Our data highlight that the mean grain yield across genotypes ranged from 9.25 to 12.65 ton/ha when maintained under continuous flooding (CF) and from 9.52 to 11.67 ton/ha at AWD water management. Root plasticity responses across evaluated genotypes under AWD management were highlighted; BRS Pampa cultivar and Titan CL hybrid showed the greater plasticity index for total root length and total root volume. Data suggests that under severe AWD management, root plasticity in terms of more total root length and total root volume at 0-20 cm depth can leads to some contribution degree for higher grain yield and for its stability under AWD practice. These results can serves as a starting point to additional efforts via physiological breeding approaches aiming the construction of rice plant ideotypes more suitable for AWD management, especially take into account its contributions to mitigate potential impacts of future climate changes on food security.
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 | 0.001 |
| 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".