Biological Pest Control in Maize Crop in Brazil: A Review
Bibliographic record
Abstract
The areas of maize production harbor a high number of insect species, some of which are considered pests that cause damage to the crop. The methods of pest control have been a cause of concern for the society since the use of chemicals and the environmental problems arising from this practice indicate the need to search for alternatives to control. In this sense, it is necessary to seek an agricultural production system that contemplates environmental sustainability and promotes biodiversity in the Agrosystem, among which the use of biological agents is highlighted. The objective of this research was to update through a bibliographic review the advances in the literature on biological control of maize crop pests. For the development of this article, we used the method of approach the analytical and as procedural method the monographic, through bibliographic research, using specialized doctrines, appropriate to the object of the study and legislations. Because of the observed aspects, it is possible to conclude that the group of natural enemies that act as biological control agents is formed by parasitoids, predators and entomopathogenic microorganisms. The rationalization of the use of chemicals should be associated with the use of biodefensives in integrated pest management. Advances in the legislation of biological products in Brazil are fundamental to give speed to the registration of new alternatives of biological control, aimed at the safety of the environment, human health and that are generated without the exploratory use of biodiversity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".