Breeding and seed production of oil crops in Serbia
Bibliographic record
Abstract
The most frequent oil crops in Serbia today are sunflower and soybean, planted on over 200,000 ha each, followed by rapeseed, which increases significantly in surfaces. Black and white mustard, hemp, oil pumpkin, castor bean, flax, poppy, sesame and safflower are grown on smaller surfaces. In Serbia, a total of 355 varieties of oil plant species were on the variety list in 2017, out of which 188 were sunflower, 83 soybean and 71 rapeseed, followed by oil pumpkin, hemp, white and black mustard and castor bean. Among the domestic and foreign seed companies, the Institute of Field and Vegetable Crops from Novi Sad prevails with 150 registered varieties. Camelina, flax, poppy and safflower are in the registration process. In the ten-year period 2008-2017, the seed production of oil crops averaged 9,955 ha per year, of which the highest were soybean (8,200 ha per year) and sunflower (1,732 ha per year), and on small areas: rapeseed, oil pumpkin, poppy and hemp. In the 2016/2017 season in Serbia, 19,657,116 kg of soybean, 1,666,267 kg of sunflower, 137,179 kg of rapeseed and small quantity of white mustard seed, cannabis and oil pumpkin seeds were certified (all seed categories). Over 86% of declared sunflower seed and over 94% of rapeseed is imported. Serbia belongs to bigger European producers of soy and sunflower, has favorable agroecological conditions for the cultivation of oil crops, long tradition of breeding, strong processing sector, quality human resources and capacities and developed system of state regulation in seed production. The advantages Serbia has in breeding, seed production and growing of oil crops, have not been adequately exploited.
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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".