Response of varied rice genotypes on cell membrane stability, defense system, physio-morphological traits and yield under transplanting and aerobic cultivation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Aerobic rice cultivation progresses water productivity, and it can save almost 50% of irrigation water compared to lowland rice with the appropriate development of genotypes and management practices. Two field trials were conducted during 2020, and 2021 seasons to determine the validation of different rice varieties under aerobic cultivation based on their plant defense system, physio-morphological traits, stress indices, grain yield, and water productivity. The experiments were designed in a split-plot design with four replications. Two planting methods, transplanting and aerobic cultivation, were denoted as the main plots, and ten rice genotypes were distributed in the subplots. The results revealed that the planting method varied significantly in all measured parameters. The transplanting method with well watering had the highest value of all measured parameters except leaf rolling, membrane stability index, antioxidant, proline, and the number of unfilled grains. EHR1, Giza179 and GZ9399 as well as A22 genotypes a chief more antioxidant defense system that operated under aerobic conditions. Giza179, EHR1, GZ9399, and Giza178 showed high cell membrane stability and subsequently high validation under such conditions, and also showed efficiency in decreasing water consumption and improving water use efficiency. In conclusion, this study proves that Giza179, EHR1, GZ9399, Giza178, and A22 are valid genotypes for aerobic conditions.
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.
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 | 0.002 | 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 it