Barley production in Russia and in the world
Bibliographic record
Abstract
Barley is one of the most important forage crops. The main barley producers are the European Union, Russia, Ukraine, Canada, Australia, Turkey and the USA. The share of the European Union is 42.3% of the total barley production in the world. The leading countries are France and Germany. In spite of decrease of the need of forage in husbandry, the Russian Federation is the first in the world in the acreage of barley. Saudi Arabia was the principal country of barley marketing for Russia in 2015 (57.3% of the total amount). The largest amounts of barley are sent from RF to Iran, Jordan, Kuwait, Libya and Tunisia. The Prevolzhsky and Central Federal Districts are the principal producers in Russia and the Voronezh region is the largest productive area in Russia. The Orenburg region is the first in Russia in the amount of acreage. The share of the Southern federal District is about 15% of the total barley production Russia. There is an increase of winter barley acreage and decrease of spring barley acreage in the Rostov region. The countries of EU are characterized with the largest productivity of barley in the world. On average in Russia winter barley productivity is 35.9 hwt/ha and spring barley productivity is 21.8 hwt/ha. In 2015 the Veselovsky, Myasnikovsky, Kagalnitsky and Zernogradsky districts obtained the largest yields of barley in the Rostov region (more than 5.0 t/ha). The Semikorokorsky, Myasnikovsky, Kagalnitsky and Zernogradsky districts harvested more than 3.0 t/ha of spring barley. One of the most important directions of stable production of barley is the introduction of new varieties. The varieties of FSBSI ARRIGC after I.G. Kalinenko due to their good adaptability to the local environment realize their productive potential well. Their use in production will play a definite part in increase of barley productivity, crop stability and a complete supply with valuable forage.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".