Growth, Productivity and Quality of Soybean Grains, Submitted to Different Seed Treatments
Bibliographic record
Abstract
The protection conferred via chemical treatment of seeds is indispensable to the normal development of crops, with a view to the best use of its productive potential. The objective of this study was to evaluate the soybean crop response, cultivate ‘FTS Paragominas RR’, to seed treatment. The study was conducted in an experimental area of the Center of Agrarian and Environmental Sciences of the Federal University of Maranhão, in Chapadinha (MA), from February to June 2018. A randomized complete block design was used, with split-plot in time. The plots consisted of five seed treatments: thiophanate-methyl + fluazinam fungicides, fludioxonil, carbendazim + thiram, the insecticide fipronil and the absence of the application. Throughout the crop cycle the agronomic characteristics were verified: plant height, stem diameter, and leaf area. And, at the time of harvesting, grain yield, the height of insertion of the first pod, the total number of pods and weight of 1000 grains. Seed treatments induced very variable responses on the growth and development of soybean ‘FTS Paragominas RR’. The best performances were obtained with the use of thiophanate-methyl + fluazinam fungicides (dose 198 mL) and fludioxonil (dose 200 mL). The application of carbendazim + thiram and fipronil, both at a dose of 200 mL, presented adverse effects throughout the vegetative and reproductive phases of soybean ‘FTS Paragominas RR’. None of the products provided significant increases in grain yield.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".