Research Status of Upland Rice Worldwide and Its Enlightenment to Guangdong Province
Bibliographic record
Abstract
Upland rice, an ecological type formed by the long-term domestication of rice, is mainly distributed in dry land and hilly land with stable summer rainfall but insufficient irrigation conditions. Currently, the cultivated area of upland rice in the world is about 19 million hm2, accounting for about 12.7% of the total cultivated rice area. With rich resources and a long planting history, upland rice is distributed in different rice growing areas in China. Agriculture is one of the most important sources of greenhouse gas emissions, in which the long-term water layer needs to be established in the process of rice cultivation, accounting for about 16% of the greenhouse gas emissions from agriculture. Many studies have shown that planting upland rice plays an important role in reducing greenhouse gas emissions from paddy fields, which is of great significance for ensuring national food security and achieving national carbon peak and carbon neutrality goals. Due to the relative balance of light, temperature and rainfall in Guangdong Province, double-croping rice is the main planting pattern in each ecological region, and the development of upland rice is relatively lagging. With the decrease of the rural labor force, the shortage of water resources and the continuous occurrence of extreme weather such as high temperature and drought in Guangdong and South China, the market demand for upland rice varieties has increased year by year. This review introduces the drought resistance mechanism, breeding and supporting technologies of upland rice in China and abroad, analyzes the research and planting status of upland rice in Guangdong, and puts forward suggestions on upland rice researches, providing references for molecular breeding and low-carbon cultivation technology of upland rice varieties in Guangdong Province.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".