Technology of spring durum wheat cultivation with application of secator turbo, bar-iton, falcon, nagro and others
Bibliographic record
Abstract
It has been described the possibility of a significant increase in the yield of spring durum wheat of the Saratovskaya Zolotistaya variety due to the integrated use of chemical plant pro-tection products. During four years of studies it has been studied of complex effect of preparations on the phytosanitary state of crops, yields and products’ quality in Povolzhye. High results in pests\control were obtained after complex application of Bariton disinfectant (1.5 l / ha), herbicides Secator Turbo (0.8 l / ha) + Puma Super (75 0.9 l / ha), fungicide Falkon (0.6 l / ha), insecticides Confidor Extra (50 g /ha) + Decis Profi (15 g/ha). In the experimen-tal variants, the incidence of root rot was 3.3 times less than in the control. Biological effec-tiveness against brown rust was 92.4%, stem rust - 85.8%, perennial dicotyledonous plants - 87.3%, annual dicotyledonous plants - 94.0%, annual monocotyledonous plants - 97.7%. The total contamination decreased by 94.1%. Treatment of crops with insecticides against larvae and adult thrips, sunn pest was 89.0 and 95.2%. Set of measures against harmful organisms increased significantly crop yields. The best results were obtained after complex application of disinfectant, herbicides, fungicide, insecticides - 56.6%; slightly less - 45.2% after application of a disinfectant, herbicide and insecticide. Application of disinfectant, fungicide and insecti-cide contributed to the preservation of 26.2% of the crop. The smallest increases were ob-tained after application of disinfectant and an insecticide - 14.9%. Chemical protection not only preserved the crop, but also improved the quality of the products. The protein content in-creased from 12.5 to 14.4%, gluten content – from 24.5 to 29.1%
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".