Association of Herbicides for Management of Weed Plants in Pre-emergence of Soybean Culture
Bibliographic record
Abstract
One of the big challenges to the soybean cultivation is the control of weed plants, because of the competitive potential that they presente and the resistance index in relation to the herbicides. In front of this, the work had as objective to evaluate the mix of herbicides in tanks to initial control of weed plants in the soybean culture. The experiment was installed in field in sistem of no-tillage in an área that presented the cultute of the wheat as precedente. The design used was that one of randomized blocks, with four repetitions. The herbicide’s treatments used in the test were: glyphosate, glyphosate + (diuron+sulfentrazone), glyphosate + diclosulam, glyphosate + (imazethapyr + flumioxazin), glyphosate + flumioxazin, glyphosate + 2,4-D, glyphosate + S-metolachlor, amônio-glufosinate + (diuron + sulfentrazone). The variable used was phytotoxicity in the culture, weed plants’ control Urochloa plantaginea and Raphanus sp., thousand grains weight and productivity of the soybean. The data were submitted to analysis of variance by the F test and the compared averages by the Scott-Knott test, in 5% of error probability. The phytotoxicity caused by the herbicides in the culture is not significative in the point of decrease the grains yield. The herbicides that presented better control of U. plantaginea were the associations of glyphosate with diuron + sulfetrazone, imazethapyr + flumioxazin and s-metolaclhor. Already in the control of Raphanus sp., the association of diclosulam and imazethapyr + flumioxazin with glyphosate presents results next of 100% of control. The variable thousand grains weight it was not affected by the association of the herbicides. In relation to the soybean grains productivity the herbicides (glyphosate + diclosulam and glyphosate + (imazethapyr + flumioxazin)) that provide low phytotoxicity and high control of the weed plants had their productivity compared to the weeded control.
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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 | 0.001 |
| 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".