Hydroalcoholic Extract of Crambe on Sitophilus zeamais Insects and Maize Seed Quality
Bibliographic record
Abstract
The objective of this work is to evaluate the insecticidal and attractiveness of concentrations of hydroalcoholic extract of crambe grains on Sitophilus zeamais, and its effect on the physiological quality of corn seeds. The experiments were conducted at the Laboratory of Entomology and Seeds of the Assis Gurgacz University Center, in Cascavel, PR. The evaluation of attractiveness and insecticidal effect were evaluated using DIC, with 4 treatments (0, 5, 15 and 25% extract concentration) and 10 or 5 replications, respectively, totaling 40 experimental plots for the insect attractiveness test and 20 Experimental plots for the test of the insecticidal effect. For the experiment on the physiological quality of corn seeds submitted to the extracts, a DIC was set up in a 4 × 4 factorial scheme, factor 1 being the storage time of the seeds (0, 30, 60 and 90 days) and factor 2, the concentrations (0, 5, 15 and 25%), with 4 replicates, totaling 64 plots. Data were submitted to ANAVA, and means adjusted to regression or submitted to the Tukey test at 5% of probability, using the statistical program ASSISTAT®. The results evidenced the treatment with a hydroalcoholic extract in the concentration of 25% as the one with the highest insecticidal effect, and extract at 15% concentration yields a higher percentage of germination, normal seedlings, and mass of seedlings than the control. At 25% concentration, the extract do not negatively influence any of the parameters analyzed. Storage time above 60 days stimulates germination, mass and length of maize seedlings.
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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".