INCIDÊNCIA DE BICHO-MINEIRO E ÁCARO-VERMELHO EM LAVOURA CAFEEIRA CONDUZIDA COM MANEJO ORGÂNICO E CONVENCIONAL
Bibliographic record
Abstract
The coffee leaf miner is considered an important coffee pest and the red mite is the main phytophagous mite that attacks this crop. The control of these pests is carried out through the application of phytosanitary products, which, when used inefficiently, can lead to environmental problems. The aim of this study was to evaluate the incidence of leaf miner and red mite in organic and conventional coffee. The experiment was carried out in Monte Carmelo -MG, at Fazenda Araras 2 with the cultivar Catuca Amarelo 20/15 cv 479. A randomized block design was used, with five blocks and four treatments. Three organic fertilization treatments were carried out, where in all treatments, the fertilizations were managed in three ways: cover fertilization, drench and spraying. A control with the conventional treatment following the farm's management was also used. The evaluations were performed in the five central plants of each plot from January 2018 to May 2019, counting live caterpillars and red mites on a pair of leaves in each quadrant of the plant in the middle third of the coffee tree. The incidence data was adjusted to a Zero Inflated Mixed Generalized Linear Model. There was no significant difference between cultivation systems (organic and conventional) in the incidence of these pests. The population density peaks for leaf miner were recorded from June to September 2018 and March to April 2019 and for red mite in August 2018, due to conditions of low relative humidity and precipitation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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; both teacher heads agree on what is shown here.
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".