中国油菜籽和菜籽油的生产、进出口及供需分析Analysis on production, import,export, supply and demand of rapeseed and rapeseed oil in China
Bibliographic record
Abstract
分析我国油菜籽和菜籽油的生产、进出口及供需情况，以期为我国菜籽油产业发展提供参考。近年，我国油菜籽收获面积相对稳定、产量小幅增长，但在全球占比呈下降趋势；我国油菜籽压榨出油率低于其他菜籽油主要生产国，油菜籽压榨量和菜籽油产量在全球占比也呈下降趋势。2008年及以后，我国每年油菜籽进口量均在100万t以上，出口量均不到0.5万t。2018—2020年我国菜籽油进口量均在100万t以上，出口量3年累计不足3万t。我国油菜籽、菜籽油进口的最主要来源国是加拿大，2016—2020年间我国进口的油菜籽和菜籽油来自加拿大的分别占90%和70%。将我国油菜籽净进口折油与菜籽油净进口量合计考虑，2020/2021年度该数值达359万t。我国对油菜籽及菜籽油的需求将持续增长，国内油菜籽和菜籽油产量难以满足国内需求，需要大量进口。相对紧张的耕地资源对油菜生产的限制与乡村小榨坊菜籽油特殊市场的存在也是我国油菜产业的重要特点。对外，我国应对具有油菜生产潜力的国家进行长远投资，以丰富油菜籽和菜籽油的进口来源；对内，应重视国内乡村地区对小榨坊菜籽油的需求，并对其工艺和产品质量进行改进和提升。 The production, import, export, supply and demand of rapeseed and rapeseed oil in China were analyzed so as to provide reference for the development of rapeseed oil industry in China. In recent years, China’s rapeseed harvest area has been relatively stable and its output has increased slightly, but their proportions in the world have shown downward trends. The oil yield of rapeseed in China is lower than that of other major rapeseed oil producing countries, and the proportions of rapeseed crushing amount and rapeseed oil output in the world also show downward trends. From 2008 to now, China’s rapeseed import is more than 1 million tons and its export is less than 5 000 t for each year. From 2018 to 2020, China’s rapeseed oil import is more than 1 million tons each year, and the export is less than 30 000 t in total. Canada is the main source of China’s rapeseed and rapeseed oil imports. From 2016 to 2020, 90% and 70% of China’s rapeseed and rapeseed oil imports came from Canada respectively. Considering the total of China’s net import of oil equivalent rapeseed plus the net import of rapeseed oil, the value reached a new high of 3.59 million tons in 2020/2021. China’s demand for rapeseed and rapeseed oil will continue to grow. Domestic rapeseed and rapeseed oil production is difficult to meet domestic demand and this needs to be met through large imports. The restriction of relatively tight arable land resources on rape production and the existence of rural small crush rapeseed oil market are also important characteristics of China’s rapeseed industry. It is suggested that China should make long-term investment in countries with rapeseed production potential to enrich the import sources of rapeseed and rapeseed oil, and internally, pay attention to the demand of rural small crush rapeseed oil, and improve its process and product quality.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".