THE INFLUENCE OF HERBICIDES WITH VARIOUS RANGE OF EFFECTS FOR STRESS RESISTANCE AND YIELD OF WINTER WHEAT SEEDS
Bibliographic record
Abstract
The aim of the research is to substantiate the scheme of plant protection of winter wheat against perennial and annual weeds, including monocotyledonous weed species. This scheme provides high grain yield and quality standardized seeds output. To achieve this goal the production experiment was conducted. The experiment was repeated three times, the location of the plots was systematic. The predecessor was peas. The main weeds of winter wheat were representatives of the classes: Asteraceae (field sowthistle, Canada thistle, chamomile odorless), ranging from 15% to 24%, Cabbage – Brassicaceae Burnett (field pennycress) – 7-14%, Goosefoot family – Chenopodiaceae (pigweed white) – 1-6%, Vonkova – Convolvulaceae (convolvulus arvensis) – 10-8% and Poaceae (PPE foxtail, millet, chicken, wild oat common) – from 24 to 42%. The species composition of the weed is suppressed almost completely when using the tank mixture of graminicide together with the broad-spectrum herbicide (Lastik Top 0.5 l/ga + Balerina 0.4 l/ga). In average, per years of research the biological efficiency of this variant was 96%. The plants of winter wheat under treatment of crops with protection means against weeds receive stress, which is manifested in a sharp decrease of chlorophyll concentration in the leaves. The inhibition of plants is manifested regardless of the application of graminicide, herbicide or tank mixtures. Under favorable weather conditions for plant growth and development the chlorophyll concentration in leaves restores after 8 days of applying plant protection means up to normal. The highest yield of winter wheat, maximum yield of quality standardized seeds and the propagation coefficient factor of varieties is formed when using a tank mix Lastik Top (0.5 l/ga) + Balerina (0.4 l/ga), regardless of variety and year of growing. The use of graminicide Lastik Top (0.5 l/ga) in tank mix with herbicide Balerina (0.4 l/ga) suppresses the development of monocotyledonous species of weeds of the same Botanical group that includes winter wheat. The second component tank mix herbicide Balerina suppresses the entire spectrum of dicotyledonous weeds. This results in the improvement of conditions for the growth and development of plants, providing higher grain yield, quality standardized seeds output and the rate of reproduction of varieties.
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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 | 0.000 | 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) | 0.001 | 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 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".