Минимализация обработки почвы под ячмень яровой в Северной Степи Украины
Bibliographic record
Abstract
The effect of different tillage methods on soil agrophysical properties, water regime, weed infestation, as well as on growth and development, yield and economic efficiency of spring barley (Ilot variety) cultivation under the conditions of the Ukrainian Northern Steppe was studied. Experimental researches were carried out during 2011-2013 in a short crop rotation system: bare fallow- winter wheat -sunflower -spring barley- corn. The basic soil tillage for spring barley was performed using the plough PO-3-35 at a depth of 20-22 cm (control variant), chisel tillage – by Canadian chisel cultivator Conser Till Plow at a depth of 14-16 cm, and disc tillage – by heavy disk harrows BDT- 3 at a depth of 10-12 cm. It was found that chisel tillage provides the best conditions for moisture accumulation in the autumn-winter period due to crop residues and wavy nanorelief that ensures the maximum amount of moisture storage in spring compared to other tillage methods. Moldboard ploughing and chisel tillage influence the formation of the highest and almost identical grain yield – 2.51-2.90 and 2.36-2.88 t/ha respectively, which favourably affects total costs and profitability of barley grain production - 44.7-48.7 %.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".