Global trends in production and trade of major grain \nlegumes
Bibliographic record
Abstract
Production trends in grain legumes — pulses, groundnuts and soybean — have followed an increasing \ntrend with the global production doubling from 148 million tons in 1980-82 to 3 10 million tons in 2004-06. \nThe increase was led by increases in soybean production which increased from 87 million tons to 214 million \ntons due to an increase in the demand for protein meals and oils from the EU and the US feed sectors and \nthe appearance of new producers like India, China, Argentina and Brazil. Consequently, the share of developing \ncountries in global grain legume production has increased from 55% in 1980-82 to 65% in 2004-06. Growth \nin the global production of pulses has been the slowest among the grain legumes, growing at 1.05% per \nannum between 980 to 2006. The emergence of countries such as Canada and Australia, the area expansion \nunder pulses in Africa, and the export oriented production of the South East Asian countries have contributed \nto the increase in the global pulse production. The largest pulse producers are still the developing countries \nand their share of the global pulse production is largely unchanged at around 70%. However, yield levels and \nyield growth rates are considerably higher in the developed countries. Grain legumes are traded in different \nforms such as kernels/seeds, cakes and meals, and oils. Trade in seeds/kernels of grain legumes has increased \nwith nearly 20% of production quantities being traded in 2000-05. However, this figure masks the contrary \ntrends in the trade patterns of individual legumes and between regions. Among the legumes, exports in \nsoybean have increased with 31% of soybean being traded, owing to increased demand from the feed sector, \nwith Argentina, Brazil and Paraguay emerging as major exporters. In this paper, an analysis has been made \non the global and regional production, yield trends, global trade and price trends of grain legumes
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| 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".