Effects of Soil Moisture Content on Germination and Physiological Characteristics of Rice Seeds with Different Specific Gravity
Bibliographic record
Abstract
Soil relative water content and seed plumpness have been shown to be the key factors affecting seed germination and seedling growth of rice under direct drought cropping. It remains to be determined whether seed germination and seedling growth of water-saving and drought-resistant rice (WDR) and conventional rice with the same proportion of rice seed have the same response to soil moisture changes. The purpose of this study was to investigate the seed germination and physiological characteristics of the rice cultivars Guangliangyou 1813 (GLY-1813,indica hybrid rice) and Hanyou 73 ((HY-73), WDR) with four different specific gravities (T1, T2, T3, and T4; the rice seeds were divided into four specific gravity levels by weight using saline water, the representative specific gravities were <1.0, 1.0–1.1, 1.1–1.2 and >1.2 kg m−3, respectively), at five soil moisture content gradients (soil relative water contents of 10–20%, 20–40%, 40–60%, 60–80%, and 80–100%), under dry direct seeding conditions. The results showed that GLY-1813 had a higher germination potential, germination and seedling emergence rates, greater root dry weight, seedling dry weight, root oxidation activity, and chlorophyll content, and lower malondialdehyde (MDA) content when the soil relative water content was 20–40% or 40–60%. Cultivar HY-73 had the highest germination rate and seedling physiological activity at 20–40% relative water content; its growth vigor was better than that of GLY-1813 at the same soil moisture level. In conclusion, the soil relative water content for seed germination of HY-73 was 20–40%, which was less than that of GLY-1813. When soil relative water content was sufficient for seed germination and growth, the higher the plumpness of the rice seed, the easier it was to resist the negative effects of an adverse growth environment.
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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 | 0.000 | 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) | 0.001 | 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 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".