Increasing seedling number alleviates the adverse effects of warming on grain yield and reduces greenhouse gas emission in late-season rice
Bibliographic record
Abstract
To address the adverse effects of warming on late-season rice, we investigated the impact of increasing the number of seedlings planted on rice yield, quality, and greenhouse gas emissions under canopy warming conditions using the free-air temperature increase (FATI) system. Three treatments were implemented: ambient temperature with 2 seedlings per hill (CKS1), canopy warming with 2 seedlings per hill (WS1), and canopy warming with 4 seedlings per hill (WS2). FATI increased rice canopy temperature and soil temperature by an average of 1.9 o C–2.2 o C and 0.6 o C–0.8 o C, respectively, over the two years. The yield in WS1 was significantly reduced by 10.1%–12.1% compared to CKS1, which was attributed to a significant decrease in total spikelets per unit area and spikelets per panicle, despite a notable increase in filled grains in 2023. However, WS2 demonstrated no significant change in yield compared with CKS1. Analysis of yield components revealed that WS2 exhibited significantly higher panicles per m 2 relative to CKS1, while the spikelets per panicle were significantly lower than did CKS1. No significant changes were observed in grain weight and processing and appearance qualities. Compared with that under CKS1, CH 4 was significantly reduced under WS2 treatment in both years. Furthermore, the global warming potential (GWP) and greenhouse gas intensity (GHGI) showed a decrease, with notable differences observed in 2022. Therefore, increasing the number of seedlings per hill can alleviate the negative impacts of canopy warming on grain yield and reduce greenhouse gas emissions in late-season rice.
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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".