Physiological Effects of Insecticides and Fungicide, Applied in the Treatment of Seeds, on the Germination and Vigor of Soybean Seeds
Bibliographic record
Abstract
The initial protection of plants through the use of insecticides and fungicides has been shown to be efficient for a good management of pests and diseases, however the molecules used in seed treatment have demonstrated a physiological effect on germination and initial vegetative development. The present work had as objective the evaluation of the physiological effect caused by two insecticides and a fungicide on the germination and vigor of the seeds. A randomized block design with six treatments and four replications was used. The treatments were: T1-water; T2-Rocks® insecticide; T3-Insecticide Cruiser 350 FS®; T4-Maxim XL® fungicide; T5-Rocks® + Maxim XL® and T5-Cruiser 350 FS® + Maxim XL®. The application of the treatments was performed according to the manufacturers’ recommendations and the percentage of germination of the seeds was evaluated, on paper and sand roll substrates, the rate of emergence, the total length of seedlings, the electrical conductivity of the imbibition and aging solution accelerated, with a later pattern of germination. The data were submitted to Analysis of Variance and the means were compared by the Tukey test. The results indicated that there were statistically significant differences for all variables except paper germination. The treatments that received the application of the Maxim XL fungicide demonstrated superiority, both in the evaluation of germination in sand substrate, and in the vigor evaluations of seeds and seedlings, while the treatments that received application of Rocks insecticide were inferior to the other.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".