Linseed (Linum usitatissimum L.) Production Trends in the World and in Serbia
Bibliographic record
Abstract
The aim of this study was to examine the changes that have occurred in the production of linseed in the world, and as well the conditions that led to manifested trends. During the monitored period (2009-2013) linseed production in the world was 2.09 million tons and it was growing at an average rate of 1.48% per year and records stability, CV=7.28%. The growth in production of linseed was dominantly influenced by the growth area. Five countries (Canada, China, Russia, India and U.S.A) provide 72.50% of global linseed production. The European top producer is the Russian Federation (13.86%). A significant producer is the EU-European Union with a share of 7.13%. In the tested period, linseed in the world was sowing on the average area of 2.15 million ha, and showed an annual 3.08% trend rate increase, and stability (CV =7.09%). Average yield of linseed during the monitored period in world was 972 kg. There was evident tendency of decrease of yield growth rate (1.54%) and variation (CV = 8.18%).The highest average of yield, in the world, per continents, was inAmerica (1,377 kg ha-1), Australia (1,120 kg ha-1) and Europe (1,080 kg ha-1). The lowest yields were in Asia (685 kg ha-1). EU countries had high linseed yields (1,335 kg ha-1). During the examined period, there was a decline in yields in the world. The growth area had dominant influence on increase of production of linseed.
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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 | 0.001 |
| 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".